bench : add Q4_0 and Q4_1 mul_mat benchmarks

Just in case

.gitignore

@@ -10,6 +10,7 @@ build-em/
 build-debug/
 build-release/
 build-static/
+build-no-accel/
 build-sanitize-addr/
 build-sanitize-thread/
 

README.md

@@ -469,7 +469,8 @@ in [models](models).
 - [X] .NET: | [#422](https://github.com/ggerganov/whisper.cpp/discussions/422)
   - [sandrohanea/whisper.net](https://github.com/sandrohanea/whisper.net)
   - [NickDarvey/whisper](https://github.com/NickDarvey/whisper)
-- [ ] Python: soon | [WIP](https://github.com/ggerganov/whisper.cpp/issues/9)
+- [X] Python: | [#9](https://github.com/ggerganov/whisper.cpp/issues/9)
+  - [stlukey/whispercpp.py](https://github.com/stlukey/whispercpp.py) (Cython)
 
 ## Examples
 

examples/addon.node/addon.cpp

@@ -72,7 +72,7 @@ int timestamp_to_sample(int64_t t, int n_samples) {
     return std::max(0, std::min((int) n_samples - 1, (int) ((t*WHISPER_SAMPLE_RATE)/100)));
 }
 
-void whisper_print_segment(struct whisper_context * ctx, int n_new, void * user_data) {
+void whisper_print_segment_callback(struct whisper_context * ctx, int n_new, void * user_data) {
     const auto & params  = *((whisper_print_user_data *) user_data)->params;
     const auto & pcmf32s = *((whisper_print_user_data *) user_data)->pcmf32s;
 
@@ -250,7 +250,7 @@ int run(whisper_params &params, std::vector<std::vector<std::string>> &result) {
 
             // this callback is called on each new segment
             if (!wparams.print_realtime) {
-                wparams.new_segment_callback           = whisper_print_segment;
+                wparams.new_segment_callback           = whisper_print_segment_callback;
                 wparams.new_segment_callback_user_data = &user_data;
             }
 

examples/command/command.cpp

@@ -109,73 +109,6 @@ void whisper_print_usage(int /*argc*/, char ** argv, const whisper_params & para
     fprintf(stderr, "\n");
 }
 
-struct whisper_logits_filter_user_data {
-    std::vector<std::string>                * allowed_commands;
-    std::vector<std::vector<whisper_token>> * allowed_tokens;
-};
-
-void whisper_logits_filter(
-            struct whisper_context * ctx,
-          const whisper_token_data * tokens,
-                               int   n_tokens,
-                             float * logits,
-                              void * user_data){
-    const auto & allowed_tokens = *((whisper_logits_filter_user_data *) user_data)->allowed_tokens;
-
-    printf("n_tokens = %d\n", n_tokens);
-    for (int i = 0; i < n_tokens; i++) {
-        printf(" - '%s' (%.2f)\n", whisper_token_to_str(ctx, tokens[i].id), logits[i]);
-    }
-
-    if (n_tokens == 0) {
-        return;
-    }
-
-    std::vector<std::pair<whisper_token, float>> pool;
-    for (int i = 0; i < (int) allowed_tokens.size(); i++) {
-        const int n = (int) allowed_tokens[i].size();
-        if (n_tokens > n) {
-            continue;
-        }
-
-        const whisper_token id = allowed_tokens[i][n_tokens - 1];
-        pool.push_back({ id, logits[id] });
-    }
-
-    if (pool.empty()) {
-        return;
-    }
-
-    printf("applying logits filter, pool size = %d\n", (int) pool.size());
-
-    const int ibeg = whisper_token_beg(ctx);
-
-    double sum_all = 0.0;
-    for (int i = 0; i < ibeg; ++i) {
-        if (logits[i] == -INFINITY) {
-            continue;
-        }
-        sum_all += logits[i];
-    }
-
-    double sum_pool = 0.0;
-    for (int i = 0; i < (int) pool.size(); ++i) {
-        sum_pool += pool[i].second;
-    }
-
-    printf("sum_all = %.2f, sum_pool = %.2f\n", sum_all, sum_pool);
-
-    for (int i = 0; i < ibeg; ++i) {
-        logits[i] = -INFINITY;
-    }
-
-    for (int i = 0; i < (int) pool.size(); ++i) {
-        //logits[pool[i].first] = pool[i].second / sum_pool * sum_all;
-        logits[pool[i].first] = pool[i].second;
-        printf(" - '%s' (%.2f)\n", whisper_token_to_str(ctx, pool[i].first), logits[pool[i].first]);
-    }
-}
-
 std::string transcribe(whisper_context * ctx, const whisper_params & params, const std::vector<float> & pcmf32, float & prob, int64_t & t_ms) {
     const auto t_start = std::chrono::high_resolution_clock::now();
 
@@ -198,8 +131,6 @@ std::string transcribe(whisper_context * ctx, const whisper_params & params, con
     wparams.audio_ctx        = params.audio_ctx;
     wparams.speed_up         = params.speed_up;
 
-    wparams.temperature_inc  = -1.0f;
-
     if (whisper_full(ctx, wparams, pcmf32.data(), pcmf32.size()) != 0) {
         return "";
     }
@@ -403,31 +334,22 @@ int process_command_list(struct whisper_context * ctx, audio_async &audio, const
             wparams.translate        = params.translate;
             wparams.no_context       = true;
             wparams.single_segment   = true;
-            //wparams.max_tokens       = 1;
+            wparams.max_tokens       = 1;
             wparams.language         = params.language.c_str();
             wparams.n_threads        = params.n_threads;
 
             wparams.audio_ctx        = params.audio_ctx;
             wparams.speed_up         = params.speed_up;
 
-            wparams.temperature_inc  = -1.0f;
-
             wparams.prompt_tokens    = k_tokens.data();
             wparams.prompt_n_tokens  = k_tokens.size();
 
-            whisper_logits_filter_user_data user_data = { &allowed_commands, &allowed_tokens };
-
-            wparams.logits_filter_callback           = whisper_logits_filter;
-            wparams.logits_filter_callback_user_data = &user_data;
-
             // run the transformer and a single decoding pass
             if (whisper_full(ctx, wparams, pcmf32_cur.data(), pcmf32_cur.size()) != 0) {
                 fprintf(stderr, "%s: ERROR: whisper_full() failed\n", __func__);
                 break;
             }
 
-            fprintf(stdout, "%s: text - '%s'\n", __func__, whisper_full_get_segment_text(ctx, 0));
-
             // estimate command probability
             // NOTE: not optimal
             {
@@ -514,7 +436,7 @@ int process_command_list(struct whisper_context * ctx, audio_async &audio, const
 
 // always-prompt mode
 // transcribe the voice into text after valid prompt
-int process_always_prompt(struct whisper_context * ctx, audio_async & audio, const whisper_params & params) {
+int always_prompt_transcription(struct whisper_context * ctx, audio_async & audio, const whisper_params & params) {
     bool is_running = true;
     bool ask_prompt = true;
 
@@ -574,7 +496,7 @@ int process_always_prompt(struct whisper_context * ctx, audio_async & audio, con
                 const float sim = similarity(prompt, k_prompt);
 
                 //debug
-                //fprintf(stdout, "command size: %d, sim: %f\n", (int) command.size(), sim);
+                //fprintf(stdout, "command size: %i\n", command_length);
 
                 if ((sim > 0.7f) && (command.size() > 0)) {
                     fprintf(stdout, "%s: Command '%s%s%s', (t = %d ms)\n", __func__, "\033[1m", command.c_str(), "\033[0m", (int) t_ms);
@@ -754,7 +676,7 @@ int main(int argc, char ** argv) {
     if (!params.commands.empty()) {
         ret_val = process_command_list(ctx, audio, params);
     } else if (!params.prompt.empty()) {
-        ret_val = process_always_prompt(ctx, audio, params);
+        ret_val = always_prompt_transcription(ctx, audio, params);
     } else {
         ret_val = process_general_transcription(ctx, audio, params);
     }

examples/common-sdl.h

@@ -1,13 +1,13 @@
 #pragma once
 
+#include <SDL.h>
+#include <SDL_audio.h>
+
 #include <atomic>
 #include <cstdint>
 #include <vector>
 #include <mutex>
 
-#include <SDL.h>
-#include <SDL_audio.h>
-
 //
 // SDL Audio capture
 //

examples/helpers.js

@@ -145,7 +145,15 @@ function loadRemote(url, dst, size_mb, cbProgress, cbReady, cbCancel, cbPrint) {
                             var db = event.target.result;
                             var tx = db.transaction(['models'], 'readwrite');
                             var os = tx.objectStore('models');
+
+                            var rq = null;
+                            try {
                                 var rq = os.put(data, url);
+                            } catch (e) {
+                                cbPrint('loadRemote: failed to store "' + url + '" in the IndexedDB: \n' + e);
+                                cbCancel();
+                                return;
+                            }
 
                             rq.onsuccess = function (event) {
                                 cbPrint('loadRemote: "' + url + '" stored in the IndexedDB');
@@ -180,7 +188,6 @@ function loadRemote(url, dst, size_mb, cbProgress, cbReady, cbCancel, cbPrint) {
 
     rq.onabort = function (event) {
         cbPrint('loadRemote: failed to open IndexedDB: abort');
-
+        cbCancel();
     };
 }
-

examples/main/main.cpp

@@ -193,7 +193,7 @@ struct whisper_print_user_data {
     const std::vector<std::vector<float>> * pcmf32s;
 };
 
-void whisper_print_segment(struct whisper_context * ctx, int n_new, void * user_data) {
+void whisper_print_segment_callback(struct whisper_context * ctx, int n_new, void * user_data) {
     const auto & params  = *((whisper_print_user_data *) user_data)->params;
     const auto & pcmf32s = *((whisper_print_user_data *) user_data)->pcmf32s;
 
@@ -597,7 +597,7 @@ int main(int argc, char ** argv) {
 
             // this callback is called on each new segment
             if (!wparams.print_realtime) {
-                wparams.new_segment_callback           = whisper_print_segment;
+                wparams.new_segment_callback           = whisper_print_segment_callback;
                 wparams.new_segment_callback_user_data = &user_data;
             }
 

examples/whisper.wasm/CMakeLists.txt

@@ -31,9 +31,9 @@ endif()
 set_target_properties(${TARGET} PROPERTIES LINK_FLAGS " \
     --bind \
     -s USE_PTHREADS=1 \
-    -s PTHREAD_POOL_SIZE=8 \
+    -s PTHREAD_POOL_SIZE_STRICT=0 \
-    -s INITIAL_MEMORY=1500MB \
+    -s INITIAL_MEMORY=2000MB \
-    -s TOTAL_MEMORY=1500MB \
+    -s TOTAL_MEMORY=2000MB \
     -s FORCE_FILESYSTEM=1 \
     -s EXPORTED_RUNTIME_METHODS=\"['print', 'printErr', 'ccall', 'cwrap']\" \
     ${EXTRA_FLAGS} \

examples/whisper.wasm/emscripten.cpp

@@ -10,6 +10,12 @@ std::thread g_worker;
 
 std::vector<struct whisper_context *> g_contexts(4, nullptr);
 
+static inline int mpow2(int n) {
+    int p = 1;
+    while (p <= n) p *= 2;
+    return p/2;
+}
+
 EMSCRIPTEN_BINDINGS(whisper) {
     emscripten::function("init", emscripten::optional_override([](const std::string & path_model) {
         if (g_worker.joinable()) {
@@ -43,7 +49,7 @@ EMSCRIPTEN_BINDINGS(whisper) {
         }
     }));
 
-    emscripten::function("full_default", emscripten::optional_override([](size_t index, const emscripten::val & audio, const std::string & lang, bool translate) {
+    emscripten::function("full_default", emscripten::optional_override([](size_t index, const emscripten::val & audio, const std::string & lang, int nthreads, bool translate) {
         if (g_worker.joinable()) {
             g_worker.join();
         }
@@ -66,7 +72,7 @@ EMSCRIPTEN_BINDINGS(whisper) {
         params.print_special    = false;
         params.translate        = translate;
         params.language         = whisper_is_multilingual(g_contexts[index]) ? lang.c_str() : "en";
-        params.n_threads        = std::min(8, (int) std::thread::hardware_concurrency());
+        params.n_threads        = std::min(nthreads, std::min(16, mpow2(std::thread::hardware_concurrency())));
         params.offset_ms        = 0;
 
         std::vector<float> pcmf32;

examples/whisper.wasm/index-tmpl.html

@@ -40,21 +40,34 @@
 
             Note that the computation is quite heavy and may take a few seconds to complete.<br>
             The transcription results will be displayed in the text area below.<br><br>
-            <b>Important: your browser must support WASM SIMD instructions for this to work.</b>
+            <b>Important:</b>
+                <ul>
+                    <li>your browser must support WASM SIMD instructions for this to work</li>
+                    <li>quantized models are still in experimental stage (<a href="https://github.com/ggerganov/ggml/pull/27">more info</a>)</li>
+                    <li>Firefox cannot load files larger than 256 MB - use Chrome instead</li>
+                </ul>
 
-            <br><br><hr>
+            <hr>
 
             <div id="model">
-                Whisper model: <span id="model-whisper-status"></span>
+                Whisper models: <span id="model-whisper-status"></span><br><br>
                 <button id="fetch-whisper-tiny-en"  onclick="loadWhisper('tiny.en')">tiny.en (75 MB)</button>
                 <button id="fetch-whisper-tiny"     onclick="loadWhisper('tiny')">tiny (75 MB)</button>
                 <button id="fetch-whisper-base-en"  onclick="loadWhisper('base.en')">base.en (142 MB)</button>
                 <button id="fetch-whisper-base"     onclick="loadWhisper('base')">base (142 MB)</button>
                 <button id="fetch-whisper-small-en" onclick="loadWhisper('small.en')">small.en (466 MB)</button>
                 <button id="fetch-whisper-small"    onclick="loadWhisper('small')">small (466 MB)</button>
-                <span id="fetch-whisper-progress"></span>
-
                 <input type="file" id="whisper-file" name="file" onchange="loadFile(event, 'whisper.bin')" />
+                <br><br>
+                Quantized models:<br><br>
+                <button id="fetch-whisper-base-en-q4_0"   onclick="loadWhisper('base-en-q4_0')">base.en (4bit, 49 MB)</button>
+                <button id="fetch-whisper-base-q4_0"      onclick="loadWhisper('base-q4_0')">base (4bit, 49 MB)</button>
+                <button id="fetch-whisper-small-en-q4_0"  onclick="loadWhisper('small-en-q4_0')">small.en (4bit, 152 MB)</button>
+                <button id="fetch-whisper-small-q4_0"     onclick="loadWhisper('small-q4_0')">small (4bit, 152 MB)</button><br>
+                <button id="fetch-whisper-medium-en-q4_0" onclick="loadWhisper('medium-en-q4_0')">medium.en (4bit, 469 MB)</button>
+                <button id="fetch-whisper-medium-q4_0"    onclick="loadWhisper('medium-q4_0')">medium (4bit, 469 MB)</button>
+                <button id="fetch-whisper-large-q4_0"     onclick="loadWhisper('large-q4_0')">large (4bit, 985 MB)</button>
+                <span id="fetch-whisper-progress"></span>
             </div>
 
             <br>
@@ -161,6 +174,12 @@
                             <option value="yi">Yiddish</option>
                         </select>
                     </td>
+                    <!-- Slider to select number of threads between 1 and 16 -->
+                    <td>
+                        Threads:
+                        <input type="range" id="threads" name="threads" min="1" max="16" value="8" onchange="changeThreads(this.value)" />
+                        <span id="threads-value">8</span>
+                    </td>
                     <td>
                         <button onclick="onProcess(false);">Transcribe</button>
                     </td>
@@ -263,11 +282,13 @@
 
                 Module.FS_createDataFile("/", fname, buf, true, true);
 
-                model_whisper = fname;
+                //model_whisper = fname;
 
                 document.getElementById('model-whisper-status').innerHTML = 'loaded "' + model_whisper + '"!';
 
                 printTextarea('storeFS: stored model: ' + fname + ' size: ' + buf.length);
+
+                document.getElementById('model').innerHTML = 'Model fetched: ' + model_whisper;
             }
 
             function loadFile(event, fname) {
@@ -292,6 +313,15 @@
                 document.getElementById('fetch-whisper-tiny'    ).style.display = 'none';
                 document.getElementById('fetch-whisper-base'    ).style.display = 'none';
                 document.getElementById('fetch-whisper-small'   ).style.display = 'none';
+
+                document.getElementById('fetch-whisper-base-en-q4_0'  ).style.display = 'none';
+                document.getElementById('fetch-whisper-base-q4_0'     ).style.display = 'none';
+                document.getElementById('fetch-whisper-small-en-q4_0' ).style.display = 'none';
+                document.getElementById('fetch-whisper-small-q4_0'    ).style.display = 'none';
+                document.getElementById('fetch-whisper-medium-en-q4_0').style.display = 'none';
+                document.getElementById('fetch-whisper-medium-q4_0'   ).style.display = 'none';
+                document.getElementById('fetch-whisper-large-q4_0'    ).style.display = 'none';
+
                 document.getElementById('whisper-file'          ).style.display = 'none';
                 document.getElementById('model-whisper-status'  ).innerHTML = 'loaded model: ' + file.name;
             }
@@ -304,6 +334,14 @@
                     'base':     'https://whisper.ggerganov.com/ggml-model-whisper-base.bin',
                     'small.en': 'https://whisper.ggerganov.com/ggml-model-whisper-small.en.bin',
                     'small':    'https://whisper.ggerganov.com/ggml-model-whisper-small.bin',
+
+                    'base-en-q4_0':  'https://whisper.ggerganov.com/ggml-model-whisper-base.en-q4_0.bin',
+                    'base-q4_0':     'https://whisper.ggerganov.com/ggml-model-whisper-base-q4_0.bin',
+                    'small-en-q4_0': 'https://whisper.ggerganov.com/ggml-model-whisper-small.en-q4_0.bin',
+                    'small-q4_0':    'https://whisper.ggerganov.com/ggml-model-whisper-small-q4_0.bin',
+                    'medium-en-q4_0':'https://whisper.ggerganov.com/ggml-model-whisper-medium.en-q4_0.bin',
+                    'medium-q4_0':   'https://whisper.ggerganov.com/ggml-model-whisper-medium-q4_0.bin',
+                    'large-q4_0':    'https://whisper.ggerganov.com/ggml-model-whisper-large-q4_0.bin',
                 };
 
                 let sizes = {
@@ -313,6 +351,14 @@
                     'base':     142,
                     'small.en': 466,
                     'small':    466,
+
+                    'base-en-q4_0':   49,
+                    'base-q4_0':      49,
+                    'small-en-q4_0':  152,
+                    'small-q4_0':     152,
+                    'medium-en-q4_0': 469,
+                    'medium-q4_0':    469,
+                    'large-q4_0':     985,
                 };
 
                 let url     = urls[model];
@@ -327,6 +373,15 @@
                 document.getElementById('fetch-whisper-tiny'    ).style.display = 'none';
                 document.getElementById('fetch-whisper-base'    ).style.display = 'none';
                 document.getElementById('fetch-whisper-small'   ).style.display = 'none';
+
+                document.getElementById('fetch-whisper-base-en-q4_0'  ).style.display = 'none';
+                document.getElementById('fetch-whisper-base-q4_0'     ).style.display = 'none';
+                document.getElementById('fetch-whisper-small-en-q4_0' ).style.display = 'none';
+                document.getElementById('fetch-whisper-small-q4_0'    ).style.display = 'none';
+                document.getElementById('fetch-whisper-medium-en-q4_0').style.display = 'none';
+                document.getElementById('fetch-whisper-medium-q4_0'   ).style.display = 'none';
+                document.getElementById('fetch-whisper-large-q4_0'    ).style.display = 'none';
+
                 document.getElementById('whisper-file'          ).style.display = 'none';
                 document.getElementById('model-whisper-status'  ).innerHTML = 'loading model: ' + model;
 
@@ -337,12 +392,22 @@
 
                 cbCancel = function() {
                     var el;
+
                     el = document.getElementById('fetch-whisper-tiny-en' ); if (el) el.style.display = 'inline-block';
                     el = document.getElementById('fetch-whisper-base-en' ); if (el) el.style.display = 'inline-block';
                     el = document.getElementById('fetch-whisper-small-en'); if (el) el.style.display = 'inline-block';
                     el = document.getElementById('fetch-whisper-tiny'    ); if (el) el.style.display = 'inline-block';
                     el = document.getElementById('fetch-whisper-base'    ); if (el) el.style.display = 'inline-block';
                     el = document.getElementById('fetch-whisper-small'   ); if (el) el.style.display = 'inline-block';
+
+                    el = document.getElementById('fetch-whisper-base-en-q4_0'  ); if (el) el.style.display = 'inline-block';
+                    el = document.getElementById('fetch-whisper-base-q4_0'     ); if (el) el.style.display = 'inline-block';
+                    el = document.getElementById('fetch-whisper-small-en-q4_0' ); if (el) el.style.display = 'inline-block';
+                    el = document.getElementById('fetch-whisper-small-q4_0'    ); if (el) el.style.display = 'inline-block';
+                    el = document.getElementById('fetch-whisper-medium-en-q4_0'); if (el) el.style.display = 'inline-block';
+                    el = document.getElementById('fetch-whisper-medium-q4_0'   ); if (el) el.style.display = 'inline-block';
+                    el = document.getElementById('fetch-whisper-large-q4_0'    ); if (el) el.style.display = 'inline-block';
+
                     el = document.getElementById('whisper-file'          ); if (el) el.style.display = 'inline-block';
                     el = document.getElementById('model-whisper-status'  ); if (el) el.innerHTML = '';
                 };
@@ -354,7 +419,8 @@
             // audio file
             //
 
-            const kMaxAudio_s = 120;
+            const kMaxAudio_s = 30*60;
+            const kMaxRecording_s = 2*60;
             const kSampleRate = 16000;
 
             window.AudioContext = window.AudioContext || window.webkitAudioContext;
@@ -423,7 +489,7 @@
                 doRecording = false;
             }
 
-            // record up to kMaxAudio_s seconds of audio from the microphone
+            // record up to kMaxRecording_s seconds of audio from the microphone
             // check if doRecording is false every 1000 ms and stop recording if so
             // update progress information
             function startRecording() {
@@ -479,9 +545,9 @@
                                         printTextarea('js: audio recorded, size: ' + audio.length);
 
                                         // truncate to first 30 seconds
-                                        if (audio.length > kMaxAudio_s*kSampleRate) {
+                                        if (audio.length > kMaxRecording_s*kSampleRate) {
-                                            audio = audio.slice(0, kMaxAudio_s*kSampleRate);
+                                            audio = audio.slice(0, kMaxRecording_s*kSampleRate);
-                                            printTextarea('js: truncated audio to first ' + kMaxAudio_s + ' seconds');
+                                            printTextarea('js: truncated audio to first ' + kMaxRecording_s + ' seconds');
                                         }
                                         setAudio(audio);
                                     });
@@ -509,24 +575,31 @@
                         });
                     }
 
-                    document.getElementById('progress-bar').style.width = (100*(Date.now() - startTime)/1000/kMaxAudio_s) + '%';
+                    document.getElementById('progress-bar').style.width = (100*(Date.now() - startTime)/1000/kMaxRecording_s) + '%';
-                    document.getElementById('progress-text').innerHTML = (100*(Date.now() - startTime)/1000/kMaxAudio_s).toFixed(0) + '%';
+                    document.getElementById('progress-text').innerHTML = (100*(Date.now() - startTime)/1000/kMaxRecording_s).toFixed(0) + '%';
                 }, 1000);
 
                 printTextarea('js: recording ...');
 
                 setTimeout(function() {
                     if (doRecording) {
-                        printTextarea('js: recording stopped after ' + kMaxAudio_s + ' seconds');
+                        printTextarea('js: recording stopped after ' + kMaxRecording_s + ' seconds');
                         stopRecording();
                     }
-                }, kMaxAudio_s*1000);
+                }, kMaxRecording_s*1000);
             }
 
             //
             // transcribe
             //
 
+            var nthreads = 8;
+
+            function changeThreads(value) {
+                nthreads = value;
+                document.getElementById('threads-value').innerHTML = nthreads;
+            }
+
             function onProcess(translate) {
                 if (!instance) {
                     instance = Module.init('whisper.bin');
@@ -553,7 +626,7 @@
                     printTextarea('');
 
                     setTimeout(function() {
-                        var ret = Module.full_default(instance, audio, document.getElementById('language').value, translate);
+                        var ret = Module.full_default(instance, audio, document.getElementById('language').value, nthreads, translate);
                         console.log('js: full_default returned: ' + ret);
                         if (ret) {
                             printTextarea("js: whisper returned: " + ret);

ggml.h

@@ -198,6 +198,8 @@ struct ggml_object;
 struct ggml_context;
 
 enum ggml_type {
+    GGML_TYPE_Q4_0,
+    GGML_TYPE_Q4_1,
     GGML_TYPE_I8,
     GGML_TYPE_I16,
     GGML_TYPE_I32,
@@ -326,7 +328,10 @@ void ggml_print_objects(const struct ggml_context * ctx);
 int    ggml_nelements(const struct ggml_tensor * tensor);
 size_t ggml_nbytes   (const struct ggml_tensor * tensor);
 
-size_t ggml_type_size   (enum ggml_type type);
+int    ggml_blck_size (enum ggml_type type);
+size_t ggml_type_size (enum ggml_type type); // size in bytes for all elements in a block
+float  ggml_type_sizef(enum ggml_type type); // ggml_type_size()/ggml_blck_size() as float
+
 size_t ggml_element_size(const struct ggml_tensor * tensor);
 
 struct ggml_context * ggml_init(struct ggml_init_params params);

whisper.cpp

@@ -252,12 +252,34 @@ static const std::map<e_model, size_t> MEM_REQ_SCRATCH3 = {
     { MODEL_LARGE,     9ull*MB },
 };
 
-static const std::map<e_model, size_t> MEM_REQ_MODEL = {
+static const std::map<ggml_type, std::map<e_model, size_t>> MEM_REQ_MODEL = {
+    { GGML_TYPE_F16,
+        {
             { MODEL_TINY,     74ull*MB },
             { MODEL_BASE,    142ull*MB },
             { MODEL_SMALL,   466ull*MB },
             { MODEL_MEDIUM, 1464ull*MB },
             { MODEL_LARGE,  2952ull*MB },
+        },
+    },
+    { GGML_TYPE_Q4_0,
+        {
+            { MODEL_TINY,     26ull*MB },
+            { MODEL_BASE,     50ull*MB },
+            { MODEL_SMALL,   154ull*MB },
+            { MODEL_MEDIUM,  470ull*MB },
+            { MODEL_LARGE,   940ull*MB },
+        },
+    },
+    { GGML_TYPE_Q4_1,
+        {
+            { MODEL_TINY,     31ull*MB },
+            { MODEL_BASE,     57ull*MB },
+            { MODEL_SMALL,   181ull*MB },
+            { MODEL_MEDIUM,  559ull*MB },
+            { MODEL_LARGE,  1122ull*MB },
+        },
+    },
 };
 
 static const std::map<e_model, size_t> MEM_REQ_KV_SELF = {
@@ -592,16 +614,16 @@ struct whisper_context {
 
     mutable std::mt19937 rng; // used for sampling at t > 0.0
 
-    int lang_id;
+    int lang_id = 0; // english by default
 
     // [EXPERIMENTAL] token-level timestamps data
-    int64_t t_beg;
+    int64_t t_beg = 0;
-    int64_t t_last;
+    int64_t t_last = 0;
     whisper_token tid_last;
     std::vector<float> energy; // PCM signal energy
 
     // [EXPERIMENTAL] speed-up techniques
-    int32_t exp_n_audio_ctx; // 0 - use default
+    int32_t exp_n_audio_ctx = 0; // 0 - use default
 
     void use_buf(struct ggml_context * ctx, int i) {
 #if defined(WHISPER_USE_SCRATCH)
@@ -681,7 +703,7 @@ static bool kv_cache_reinit(struct whisper_kv_cache & cache) {
     const ggml_type wtype = cache.k->type;
     WHISPER_ASSERT(wtype == cache.v->type);
 
-    WHISPER_ASSERT(cache.buf.size() >= 2*n_elements*ggml_type_size(wtype));
+    WHISPER_ASSERT(cache.buf.size() >= 2*n_elements*ggml_type_sizef(wtype));
 
     struct ggml_init_params params;
     params.mem_size   = cache.buf.size();
@@ -776,12 +798,25 @@ static bool whisper_model_load(struct whisper_model_loader * loader, whisper_con
             model.type = e_model::MODEL_LARGE;
         }
 
-        // for the big tensors, we have the option to store the data in 16-bit floats
+        // for the big tensors, we have the option to store the data in 16-bit floats or quantized
         // in order to save memory and also to speed up the computation
-        wctx.wtype = model.hparams.f16 ? GGML_TYPE_F16 : GGML_TYPE_F32;
+        wctx.wtype = GGML_TYPE_COUNT;
+        switch (model.hparams.f16) {
+            case 0: wctx.wtype = GGML_TYPE_F32;  break;
+            case 1: wctx.wtype = GGML_TYPE_F16;  break;
+            case 2: wctx.wtype = GGML_TYPE_Q4_0; break;
+            case 3: wctx.wtype = GGML_TYPE_Q4_1; break;
+            default:
+                    {
+                        fprintf(stderr, "%s: invalid model (bad f16 value %d)\n", __func__, model.hparams.f16);
+                        return false;
+                    }
+        }
 
         const size_t scale = model.hparams.f16 ? 1 : 2;
 
+        static const char * ftype_str[] = { "f32", "f16", "q4_0", "q4_1", };
+
         fprintf(stderr, "%s: n_vocab       = %d\n", __func__, hparams.n_vocab);
         fprintf(stderr, "%s: n_audio_ctx   = %d\n", __func__, hparams.n_audio_ctx);
         fprintf(stderr, "%s: n_audio_state = %d\n", __func__, hparams.n_audio_state);
@@ -792,7 +827,7 @@ static bool whisper_model_load(struct whisper_model_loader * loader, whisper_con
         fprintf(stderr, "%s: n_text_head   = %d\n", __func__, hparams.n_text_head);
         fprintf(stderr, "%s: n_text_layer  = %d\n", __func__, hparams.n_text_layer);
         fprintf(stderr, "%s: n_mels        = %d\n", __func__, hparams.n_mels);
-        fprintf(stderr, "%s: f16           = %d\n", __func__, hparams.f16);
+        fprintf(stderr, "%s: ftype         = %s\n", __func__, ftype_str[model.hparams.f16]);
         fprintf(stderr, "%s: type          = %d\n", __func__, model.type);
 
         // print memory requirements
@@ -803,7 +838,7 @@ static bool whisper_model_load(struct whisper_model_loader * loader, whisper_con
                      MEM_REQ_SCRATCH1.at (model.type) +
                      MEM_REQ_SCRATCH2.at (model.type) +
                      MEM_REQ_SCRATCH3.at (model.type) +
-                scale*MEM_REQ_MODEL.at   (model.type) +
+                scale*MEM_REQ_MODEL.at(wctx.wtype).at(model.type) +
                 scale*MEM_REQ_KV_CROSS.at(model.type) +
                 scale*std::max(MEM_REQ_ENCODE.at(model.type), MEM_REQ_DECODE.at(model.type));
 
@@ -819,9 +854,9 @@ static bool whisper_model_load(struct whisper_model_loader * loader, whisper_con
         // always have at least one decoder
 
         wctx.model.buf = new std::vector<uint8_t>();
-        wctx.model.buf->resize(scale*MEM_REQ_MODEL.at(model.type));
+        wctx.model.buf->resize(scale*MEM_REQ_MODEL.at(wctx.wtype).at(model.type));
 
-        if (!kv_cache_init(model.hparams, scale*MEM_REQ_KV_SELF.at(model.type), wctx.decoders[0].kv_self, wctx.wtype, model.hparams.n_text_ctx)) {
+        if (!kv_cache_init(model.hparams, scale*MEM_REQ_KV_SELF.at(model.type), wctx.decoders[0].kv_self, GGML_TYPE_F16, model.hparams.n_text_ctx)) {
             fprintf(stderr, "%s: kv_cache_init() failed for self-attention cache\n", __func__);
             return false;
         }
@@ -831,7 +866,7 @@ static bool whisper_model_load(struct whisper_model_loader * loader, whisper_con
             fprintf(stderr, "%s: kv self size  = %7.2f MB\n", __func__, memory_size/1024.0/1024.0);
         }
 
-        if (!kv_cache_init(model.hparams, scale*MEM_REQ_KV_CROSS.at(model.type), wctx.kv_cross, wctx.wtype, model.hparams.n_audio_ctx)) {
+        if (!kv_cache_init(model.hparams, scale*MEM_REQ_KV_CROSS.at(model.type), wctx.kv_cross, GGML_TYPE_F16, model.hparams.n_audio_ctx)) {
             fprintf(stderr, "%s: kv_cache_init() failed for cross-attention cache\n", __func__);
             return false;
         }
@@ -963,92 +998,92 @@ static bool whisper_model_load(struct whisper_model_loader * loader, whisper_con
 
         // encoder
         {
-            ctx_size += n_audio_ctx*n_audio_state*ggml_type_size(GGML_TYPE_F32); // e_pe;
+            ctx_size += n_audio_ctx*n_audio_state*ggml_type_sizef(GGML_TYPE_F32); // e_pe;
 
-            ctx_size += 3*n_mels*n_audio_state*ggml_type_size(wtype);         // e_conv_1_w
+            ctx_size += 3*n_mels*n_audio_state*ggml_type_sizef(GGML_TYPE_F16); // e_conv_1_w
-            ctx_size +=          n_audio_state*ggml_type_size(GGML_TYPE_F32); // e_conv_1_b
+            ctx_size +=          n_audio_state*ggml_type_sizef(GGML_TYPE_F32); // e_conv_1_b
 
-            ctx_size += 3*n_audio_state*n_audio_state*ggml_type_size(wtype);         // e_conv_2_w
+            ctx_size += 3*n_audio_state*n_audio_state*ggml_type_sizef(GGML_TYPE_F16); // e_conv_2_w
-            ctx_size +=                 n_audio_state*ggml_type_size(GGML_TYPE_F32); // e_conv_2_b
+            ctx_size +=                 n_audio_state*ggml_type_sizef(GGML_TYPE_F32); // e_conv_2_b
 
-            ctx_size += n_audio_state*ggml_type_size(GGML_TYPE_F32); // e_ln_w;
+            ctx_size += n_audio_state*ggml_type_sizef(GGML_TYPE_F32); // e_ln_w;
-            ctx_size += n_audio_state*ggml_type_size(GGML_TYPE_F32); // e_ln_b;
+            ctx_size += n_audio_state*ggml_type_sizef(GGML_TYPE_F32); // e_ln_b;
         }
 
         // decoder
         {
-            ctx_size += n_text_ctx*n_text_state*ggml_type_size(GGML_TYPE_F32); // d_pe;
+            ctx_size += n_text_ctx*n_text_state*ggml_type_sizef(GGML_TYPE_F32); // d_pe;
 
-            ctx_size += n_vocab*n_text_state*ggml_type_size(wtype); // d_te;
+            ctx_size += n_vocab*n_text_state*ggml_type_sizef(wtype); // d_te;
 
-            ctx_size += n_text_state*ggml_type_size(GGML_TYPE_F32); // d_ln_w;
+            ctx_size += n_text_state*ggml_type_sizef(GGML_TYPE_F32); // d_ln_w;
-            ctx_size += n_text_state*ggml_type_size(GGML_TYPE_F32); // d_ln_b;
+            ctx_size += n_text_state*ggml_type_sizef(GGML_TYPE_F32); // d_ln_b;
         }
 
         // encoder layers
         {
-            ctx_size += n_audio_layer*(n_audio_state*ggml_type_size(GGML_TYPE_F32)); // mlp_ln_w
+            ctx_size += n_audio_layer*(n_audio_state*ggml_type_sizef(GGML_TYPE_F32)); // mlp_ln_w
-            ctx_size += n_audio_layer*(n_audio_state*ggml_type_size(GGML_TYPE_F32)); // mlp_ln_b
+            ctx_size += n_audio_layer*(n_audio_state*ggml_type_sizef(GGML_TYPE_F32)); // mlp_ln_b
 
-            ctx_size += n_audio_layer*(4*n_audio_state*n_audio_state*ggml_type_size(wtype));         // mlp_0_w
+            ctx_size += n_audio_layer*(4*n_audio_state*n_audio_state*ggml_type_sizef(wtype));         // mlp_0_w
-            ctx_size += n_audio_layer*(              4*n_audio_state*ggml_type_size(GGML_TYPE_F32)); // mlp_0_b
+            ctx_size += n_audio_layer*(              4*n_audio_state*ggml_type_sizef(GGML_TYPE_F32)); // mlp_0_b
 
-            ctx_size += n_audio_layer*(4*n_audio_state*n_audio_state*ggml_type_size(wtype));         // mlp_1_w
+            ctx_size += n_audio_layer*(4*n_audio_state*n_audio_state*ggml_type_sizef(wtype));         // mlp_1_w
-            ctx_size += n_audio_layer*(                n_audio_state*ggml_type_size(GGML_TYPE_F32)); // mlp_1_b
+            ctx_size += n_audio_layer*(                n_audio_state*ggml_type_sizef(GGML_TYPE_F32)); // mlp_1_b
 
-            ctx_size += n_audio_layer*(n_audio_state*ggml_type_size(GGML_TYPE_F32)); // attn_ln_0_w
+            ctx_size += n_audio_layer*(n_audio_state*ggml_type_sizef(GGML_TYPE_F32)); // attn_ln_0_w
-            ctx_size += n_audio_layer*(n_audio_state*ggml_type_size(GGML_TYPE_F32)); // attn_ln_0_b
+            ctx_size += n_audio_layer*(n_audio_state*ggml_type_sizef(GGML_TYPE_F32)); // attn_ln_0_b
 
-            ctx_size += n_audio_layer*(n_audio_state*n_audio_state*ggml_type_size(wtype));         // attn_q_w
+            ctx_size += n_audio_layer*(n_audio_state*n_audio_state*ggml_type_sizef(wtype));         // attn_q_w
-            ctx_size += n_audio_layer*(              n_audio_state*ggml_type_size(GGML_TYPE_F32)); // attn_q_b
+            ctx_size += n_audio_layer*(              n_audio_state*ggml_type_sizef(GGML_TYPE_F32)); // attn_q_b
 
-            ctx_size += n_audio_layer*(n_audio_state*n_audio_state*ggml_type_size(wtype)); // attn_k_w
+            ctx_size += n_audio_layer*(n_audio_state*n_audio_state*ggml_type_sizef(wtype)); // attn_k_w
 
-            ctx_size += n_audio_layer*(n_audio_state*n_audio_state*ggml_type_size(wtype));         // attn_v_w
+            ctx_size += n_audio_layer*(n_audio_state*n_audio_state*ggml_type_sizef(wtype));         // attn_v_w
-            ctx_size += n_audio_layer*(              n_audio_state*ggml_type_size(GGML_TYPE_F32)); // attn_v_b
+            ctx_size += n_audio_layer*(              n_audio_state*ggml_type_sizef(GGML_TYPE_F32)); // attn_v_b
 
-            ctx_size += n_audio_layer*(n_audio_state*n_audio_state*ggml_type_size(wtype));         // attn_ln_1_w
+            ctx_size += n_audio_layer*(n_audio_state*n_audio_state*ggml_type_sizef(wtype));         // attn_ln_1_w
-            ctx_size += n_audio_layer*(              n_audio_state*ggml_type_size(GGML_TYPE_F32)); // attn_ln_1_b
+            ctx_size += n_audio_layer*(              n_audio_state*ggml_type_sizef(GGML_TYPE_F32)); // attn_ln_1_b
         }
 
         // decoder layers
         {
-            ctx_size += n_text_layer*(n_text_state*ggml_type_size(GGML_TYPE_F32)); // mlp_ln_w
+            ctx_size += n_text_layer*(n_text_state*ggml_type_sizef(GGML_TYPE_F32)); // mlp_ln_w
-            ctx_size += n_text_layer*(n_text_state*ggml_type_size(GGML_TYPE_F32)); // mlp_ln_b
+            ctx_size += n_text_layer*(n_text_state*ggml_type_sizef(GGML_TYPE_F32)); // mlp_ln_b
 
-            ctx_size += n_text_layer*(4*n_text_state*n_text_state*ggml_type_size(wtype));         // mlp_0_w
+            ctx_size += n_text_layer*(4*n_text_state*n_text_state*ggml_type_sizef(wtype));         // mlp_0_w
-            ctx_size += n_text_layer*(             4*n_text_state*ggml_type_size(GGML_TYPE_F32)); // mlp_0_b
+            ctx_size += n_text_layer*(             4*n_text_state*ggml_type_sizef(GGML_TYPE_F32)); // mlp_0_b
 
-            ctx_size += n_text_layer*(4*n_text_state*n_text_state*ggml_type_size(wtype));         // mlp_1_w
+            ctx_size += n_text_layer*(4*n_text_state*n_text_state*ggml_type_sizef(wtype));         // mlp_1_w
-            ctx_size += n_text_layer*(               n_text_state*ggml_type_size(GGML_TYPE_F32)); // mlp_1_b
+            ctx_size += n_text_layer*(               n_text_state*ggml_type_sizef(GGML_TYPE_F32)); // mlp_1_b
 
-            ctx_size += n_text_layer*(n_text_state*ggml_type_size(GGML_TYPE_F32)); // attn_ln_0_w
+            ctx_size += n_text_layer*(n_text_state*ggml_type_sizef(GGML_TYPE_F32)); // attn_ln_0_w
-            ctx_size += n_text_layer*(n_text_state*ggml_type_size(GGML_TYPE_F32)); // attn_ln_0_b
+            ctx_size += n_text_layer*(n_text_state*ggml_type_sizef(GGML_TYPE_F32)); // attn_ln_0_b
 
-            ctx_size += n_text_layer*(n_text_state*n_text_state*ggml_type_size(wtype));         // attn_q_w
+            ctx_size += n_text_layer*(n_text_state*n_text_state*ggml_type_sizef(wtype));         // attn_q_w
-            ctx_size += n_text_layer*(             n_text_state*ggml_type_size(GGML_TYPE_F32)); // attn_q_b
+            ctx_size += n_text_layer*(             n_text_state*ggml_type_sizef(GGML_TYPE_F32)); // attn_q_b
 
-            ctx_size += n_text_layer*(n_text_state*n_text_state*ggml_type_size(wtype)); // attn_k_w
+            ctx_size += n_text_layer*(n_text_state*n_text_state*ggml_type_sizef(wtype)); // attn_k_w
 
-            ctx_size += n_text_layer*(n_text_state*n_text_state*ggml_type_size(wtype));         // attn_v_w
+            ctx_size += n_text_layer*(n_text_state*n_text_state*ggml_type_sizef(wtype));         // attn_v_w
-            ctx_size += n_text_layer*(             n_text_state*ggml_type_size(GGML_TYPE_F32)); // attn_v_b
+            ctx_size += n_text_layer*(             n_text_state*ggml_type_sizef(GGML_TYPE_F32)); // attn_v_b
 
-            ctx_size += n_text_layer*(n_text_state*n_text_state*ggml_type_size(wtype));         // attn_ln_1_w
+            ctx_size += n_text_layer*(n_text_state*n_text_state*ggml_type_sizef(wtype));         // attn_ln_1_w
-            ctx_size += n_text_layer*(             n_text_state*ggml_type_size(GGML_TYPE_F32)); // attn_ln_1_b
+            ctx_size += n_text_layer*(             n_text_state*ggml_type_sizef(GGML_TYPE_F32)); // attn_ln_1_b
                                                                                                 //
-            ctx_size += n_text_layer*(n_text_state*ggml_type_size(GGML_TYPE_F32)); // cross_attn_ln_0_w
+            ctx_size += n_text_layer*(n_text_state*ggml_type_sizef(GGML_TYPE_F32)); // cross_attn_ln_0_w
-            ctx_size += n_text_layer*(n_text_state*ggml_type_size(GGML_TYPE_F32)); // cross_attn_ln_0_b
+            ctx_size += n_text_layer*(n_text_state*ggml_type_sizef(GGML_TYPE_F32)); // cross_attn_ln_0_b
 
-            ctx_size += n_text_layer*(n_text_state*n_text_state*ggml_type_size(wtype));         // cross_attn_q_w
+            ctx_size += n_text_layer*(n_text_state*n_text_state*ggml_type_sizef(wtype));         // cross_attn_q_w
-            ctx_size += n_text_layer*(             n_text_state*ggml_type_size(GGML_TYPE_F32)); // cross_attn_q_b
+            ctx_size += n_text_layer*(             n_text_state*ggml_type_sizef(GGML_TYPE_F32)); // cross_attn_q_b
 
-            ctx_size += n_text_layer*(n_text_state*n_text_state*ggml_type_size(wtype)); // cross_attn_k_w
+            ctx_size += n_text_layer*(n_text_state*n_text_state*ggml_type_sizef(wtype)); // cross_attn_k_w
 
-            ctx_size += n_text_layer*(n_text_state*n_text_state*ggml_type_size(wtype));         // cross_attn_v_w
+            ctx_size += n_text_layer*(n_text_state*n_text_state*ggml_type_sizef(wtype));         // cross_attn_v_w
-            ctx_size += n_text_layer*(             n_text_state*ggml_type_size(GGML_TYPE_F32)); // cross_attn_v_b
+            ctx_size += n_text_layer*(             n_text_state*ggml_type_sizef(GGML_TYPE_F32)); // cross_attn_v_b
 
-            ctx_size += n_text_layer*(n_text_state*n_text_state*ggml_type_size(wtype));         // cross_attn_ln_1_w
+            ctx_size += n_text_layer*(n_text_state*n_text_state*ggml_type_sizef(wtype));         // cross_attn_ln_1_w
-            ctx_size += n_text_layer*(             n_text_state*ggml_type_size(GGML_TYPE_F32)); // cross_attn_ln_1_b
+            ctx_size += n_text_layer*(             n_text_state*ggml_type_sizef(GGML_TYPE_F32)); // cross_attn_ln_1_b
         }
 
         ctx_size += (15 + 15*n_audio_layer + 24*n_text_layer)*256; // object overhead
@@ -1094,10 +1129,10 @@ static bool whisper_model_load(struct whisper_model_loader * loader, whisper_con
         {
             model.e_pe = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, n_audio_state, n_audio_ctx);
 
-            model.e_conv_1_w = ggml_new_tensor_3d(ctx, wtype,         3, n_mels, n_audio_state);
+            model.e_conv_1_w = ggml_new_tensor_3d(ctx, GGML_TYPE_F16, 3, n_mels, n_audio_state);
             model.e_conv_1_b = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, 1, n_audio_state);
 
-            model.e_conv_2_w = ggml_new_tensor_3d(ctx, wtype,         3, n_audio_state, n_audio_state);
+            model.e_conv_2_w = ggml_new_tensor_3d(ctx, GGML_TYPE_F16, 3, n_audio_state, n_audio_state);
             model.e_conv_2_b = ggml_new_tensor_2d(ctx, GGML_TYPE_F32, 1, n_audio_state);
 
             model.e_ln_w = ggml_new_tensor_1d(ctx, GGML_TYPE_F32, n_audio_state);
@@ -1313,9 +1348,21 @@ static bool whisper_model_load(struct whisper_model_loader * loader, whisper_con
                 return false;
             }
 
-            const size_t bpe = (ftype == 0) ? sizeof(float) : sizeof(ggml_fp16_t);
+            size_t bpe = 0;
 
-            if (nelements*bpe != ggml_nbytes(tensor)) {
+            switch (ftype) {
+                case 0: bpe = ggml_type_size(GGML_TYPE_F32);  break;
+                case 1: bpe = ggml_type_size(GGML_TYPE_F16);  break;
+                case 2: bpe = ggml_type_size(GGML_TYPE_Q4_0); assert(ne[0] % 64 == 0); break;
+                case 3: bpe = ggml_type_size(GGML_TYPE_Q4_1); assert(ne[0] % 64 == 0); break;
+                default:
+                        {
+                            fprintf(stderr, "%s: unknown ftype %d in model file\n", __func__, ftype);
+                            return false;
+                        }
+            };
+
+            if ((nelements*bpe)/ggml_blck_size(tensor->type) != ggml_nbytes(tensor)) {
                 fprintf(stderr, "%s: tensor '%s' has wrong size in model file: got %zu, expected %zu\n",
                         __func__, name.data(), ggml_nbytes(tensor), nelements*bpe);
                 return false;
@@ -1513,14 +1560,14 @@ static bool whisper_encode(
                 ggml_permute(ctx0,
                         ggml_cpy(ctx0,
                             Qcur,
-                            ggml_new_tensor_3d(ctx0, wctx.wtype, n_state/n_head, n_head, n_ctx)),
+                            ggml_new_tensor_3d(ctx0, GGML_TYPE_F16, n_state/n_head, n_head, n_ctx)),
                         0, 2, 1, 3);
 
             struct ggml_tensor * K =
                 ggml_permute(ctx0,
                         ggml_cpy(ctx0,
                             Kcur,
-                            ggml_new_tensor_3d(ctx0, wctx.wtype, n_state/n_head, n_head, n_ctx)),
+                            ggml_new_tensor_3d(ctx0, GGML_TYPE_F16, n_state/n_head, n_head, n_ctx)),
                         0, 2, 1, 3);
 
             struct ggml_tensor * V =
@@ -1530,7 +1577,7 @@ static bool whisper_encode(
                                 Vcur,
                                 n_state/n_head, n_head, n_ctx),
                             1, 2, 0, 3),
-                        ggml_new_tensor_3d(ctx0, wctx.wtype, n_ctx, n_state/n_head, n_head)
+                        ggml_new_tensor_3d(ctx0, GGML_TYPE_F16, n_ctx, n_state/n_head, n_head)
                         );
 
             struct ggml_tensor * KQV = ggml_flash_attn(ctx0, Q, K, V, false);
@@ -1546,7 +1593,7 @@ static bool whisper_encode(
                 ggml_permute(ctx0,
                         ggml_cpy(ctx0,
                             Kcur,
-                            ggml_new_tensor_3d(ctx0, wctx.wtype, n_state/n_head, n_head, n_ctx)),
+                            ggml_new_tensor_3d(ctx0, GGML_TYPE_F16, n_state/n_head, n_head, n_ctx)),
                         0, 2, 1, 3);
 
             // K * Q
@@ -1564,7 +1611,7 @@ static bool whisper_encode(
             //    ggml_permute(ctx0,
             //            ggml_cpy(ctx0,
             //                Vcur,
-            //                ggml_new_tensor_3d(ctx0, wctx.wtype, n_state/n_head, n_head, n_ctx)),
+            //                ggml_new_tensor_3d(ctx0, GGML_TYPE_F16, n_state/n_head, n_head, n_ctx)),
             //            1, 2, 0, 3);
 
             //struct ggml_tensor * KQV = ggml_mul_mat(ctx0, V_trans, KQ_soft_max);
@@ -1576,7 +1623,7 @@ static bool whisper_encode(
                                 Vcur,
                                 n_state/n_head, n_head, n_ctx),
                             0, 2, 1, 3),
-                        ggml_new_tensor_3d(ctx0, wctx.wtype, n_state/n_head, n_ctx, n_head)
+                        ggml_new_tensor_3d(ctx0, GGML_TYPE_F16, n_state/n_head, n_ctx, n_head)
                         );
 
             struct ggml_tensor * KQV = ggml_mul_mat(ctx0, ggml_transpose(ctx0, V), KQ_soft_max);
@@ -1634,7 +1681,7 @@ static bool whisper_encode(
             wctx.use_buf(ctx0, 0);
 
             cur = ggml_flash_ff(ctx0,
-                    ggml_cpy(ctx0, cur, ggml_new_tensor_2d(ctx0, wctx.wtype, n_state, n_ctx)),
+                    ggml_cpy(ctx0, cur, ggml_new_tensor_2d(ctx0, GGML_TYPE_F16, n_state, n_ctx)),
                     layer.mlp_0_w, layer.mlp_0_b, layer.mlp_1_w, layer.mlp_1_b);
 #else
             wctx.use_buf(ctx0, 0);
@@ -4445,23 +4492,32 @@ WHISPER_API int whisper_bench_ggml_mul_mat(int n_threads) {
     // when F16 is used, there is an extra work buffer of size N*N*sizeof(float)
     std::vector<char> buf(4llu*N_max*N_max*sizeof(float) + 4*256);
 
+    // put a bunch of random data in the buffer
     for (size_t i = 0; i < buf.size(); i++) buf[i] = i;
 
     for (int j = 0; j < (int) sizes.size(); j++) {
+        int n_q4_0 = 0;
+        int n_q4_1 = 0;
         int n_fp16 = 0;
         int n_fp32 = 0;
 
         // GFLOPS/s
+        double s_q4_0 = 0.0;
+        double s_q4_1 = 0.0;
         double s_fp16 = 0.0;
         double s_fp32 = 0.0;
 
         const size_t N = sizes[j];
 
-        for (int k = 0; k < 2; ++k) {
+        for (int k = 0; k < 4; ++k) {
-            const ggml_type wtype = k == 0 ? GGML_TYPE_F16 : GGML_TYPE_F32;
+            const ggml_type wtype =
+                k == 0 ? GGML_TYPE_Q4_0 :
+                k == 1 ? GGML_TYPE_Q4_1 :
+                k == 2 ? GGML_TYPE_F16  :
+                         GGML_TYPE_F32;
 
-            double & s = k == 0 ? s_fp16 : s_fp32;
+            double & s = k == 0 ? s_q4_0 : k == 1 ? s_q4_1 : k == 2 ? s_fp16 : s_fp32;
-            int    & n = k == 0 ? n_fp16   : n_fp32;
+            int    & n = k == 0 ? n_q4_0 : k == 1 ? n_q4_1 : k == 2 ? n_fp16 : n_fp32;
 
             struct ggml_init_params gparams = {
                 /*.mem_size   =*/ buf.size(),
@@ -4504,8 +4560,8 @@ WHISPER_API int whisper_bench_ggml_mul_mat(int n_threads) {
             s = ((2.0*N*N*N*n)/tsum)*1e-9;
         }
 
-        fprintf(stderr, "ggml_mul_mat: %5zu x %5zu: F16 %8.1f GFLOPS (%3d runs) / F32 %8.1f GFLOPS (%3d runs)\n",
+        fprintf(stderr, "ggml_mul_mat: %4zu x %4zu: Q4_0 %7.1f GFLOPS (%3d runs) / Q4_1 %7.1f GFLOPS (%3d runs) / F16 %7.1f GFLOPS (%3d runs) / F32 %7.1f GFLOPS (%3d runs)\n",
-            N, N, s_fp16, n_fp16, s_fp32, n_fp32);
+                N, N, s_q4_0, n_q4_0, s_q4_1, n_q4_1, s_fp16, n_fp16, s_fp32, n_fp32);
     }
 
     return 0;