snapshot of https://github.com/ggml-org/whisper.cpp.git @ da54572229bcf64ba367d96c7ef15770376c4280 (2026-09-15)

examples/server/CMakeLists.txt

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+set(CMAKE_CXX_STANDARD 17)
+set(CMAKE_CXX_STANDARD_REQUIRED ON)
+
+set(TARGET whisper-server)
+add_executable(${TARGET} server.cpp httplib.h)
+
+include(DefaultTargetOptions)
+
+target_link_libraries(${TARGET} PRIVATE common json_cpp whisper ${CMAKE_THREAD_LIBS_INIT})
+
+if (WIN32)
+    target_link_libraries(${TARGET} PRIVATE ws2_32)
+endif()
+
+install(TARGETS ${TARGET} RUNTIME)

examples/server/README.md

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+# whisper.cpp/examples/server
+
+Simple http server. WAV Files are passed to the inference model via http requests.
+
+https://github.com/ggerganov/whisper.cpp/assets/1991296/e983ee53-8741-4eb5-9048-afe5e4594b8f
+
+## Usage
+
+```
+./build/bin/whisper-server -h
+
+usage: ./build/bin/whisper-server [options]
+
+options:
+  -h,        --help              [default] show this help message and exit
+  -t N,      --threads N         [4      ] number of threads to use during computation
+  -p N,      --processors N      [1      ] number of processors to use during computation
+  -ot N,     --offset-t N        [0      ] time offset in milliseconds
+  -on N,     --offset-n N        [0      ] segment index offset
+  -d  N,     --duration N        [0      ] duration of audio to process in milliseconds
+  -mc N,     --max-context N     [-1     ] maximum number of text context tokens to store
+  -ml N,     --max-len N         [0      ] maximum segment length in characters
+  -sow,      --split-on-word     [false  ] split on word rather than on token
+  -bo N,     --best-of N         [2      ] number of best candidates to keep
+  -bs N,     --beam-size N       [-1     ] beam size for beam search
+  -ac N,     --audio-ctx N       [0      ] audio context size (0 - all)
+  -wt N,     --word-thold N      [0.01   ] word timestamp probability threshold
+  -et N,     --entropy-thold N   [2.40   ] entropy threshold for decoder fail
+  -lpt N,    --logprob-thold N   [-1.00  ] log probability threshold for decoder fail
+  -debug,    --debug-mode        [false  ] enable debug mode (eg. dump log_mel)
+  -tr,       --translate         [false  ] translate from source language to english
+  -di,       --diarize           [false  ] stereo audio diarization
+  -tdrz,     --tinydiarize       [false  ] enable tinydiarize (requires a tdrz model)
+  -nf,       --no-fallback       [false  ] do not use temperature fallback while decoding
+  -ps,       --print-special     [false  ] print special tokens
+  -pc,       --print-colors      [false  ] print colors
+  -pr,       --print-realtime    [false  ] print output in realtime
+  -pp,       --print-progress    [false  ] print progress
+  -nt,       --no-timestamps     [false  ] do not print timestamps
+  -l LANG,   --language LANG     [en     ] spoken language ('auto' for auto-detect)
+  -dl,       --detect-language   [false  ] exit after automatically detecting language
+             --prompt PROMPT     [       ] initial prompt
+             --carry-initial-prompt [false  ] always prepend initial prompt
+  -m FNAME,  --model FNAME       [models/ggml-base.en.bin] model path
+  -oved D,   --ov-e-device DNAME [CPU    ] the OpenVINO device used for encode inference
+  -dtw MODEL --dtw MODEL         [       ] compute token-level timestamps
+  --host HOST,                   [127.0.0.1] Hostname/ip-adress for the server
+  --port PORT,                   [8080   ] Port number for the server
+  --public PATH,                 [examples/server/public] Path to the public folder
+  --request-path PATH,           [       ] Request path for all requests
+  --inference-path PATH,         [/inference] Inference path for all requests
+  --convert,                     [false  ] Convert audio to WAV, requires ffmpeg on the server
+  -sns,      --suppress-nst      [false  ] suppress non-speech tokens
+  -nth N,    --no-speech-thold N [0.60   ] no speech threshold
+  -nc,       --no-context        [false  ] do not use previous audio context
+  -ng,       --no-gpu            [false  ] do not use gpu
+  -fa,       --flash-attn        [false  ] flash attention
+
+Voice Activity Detection (VAD) options:
+             --vad                           [false  ] enable Voice Activity Detection (VAD)
+  -vm FNAME, --vad-model FNAME               [       ] VAD model path
+  -vt N,     --vad-threshold N               [0.50   ] VAD threshold for speech recognition
+  -vspd N,   --vad-min-speech-duration-ms  N [250    ] VAD min speech duration (0.0-1.0)
+  -vsd N,    --vad-min-silence-duration-ms N [100    ] VAD min silence duration (to split segments)
+  -vmsd N,   --vad-max-speech-duration-s   N [FLT_MAX] VAD max speech duration (auto-split longer)
+  -vp N,     --vad-speech-pad-ms           N [30     ] VAD speech padding (extend segments)
+  -vo N,     --vad-samples-overlap         N [0.10   ] VAD samples overlap (seconds between segments)
+```
+
+> [!WARNING]
+> **Do not run the server example with administrative privileges and ensure it's operated in a sandbox environment, especially since it involves risky operations like accepting user file uploads and using ffmpeg for format conversions. Always validate and sanitize inputs to guard against potential security threats.**
+
+## request examples
+
+**/inference**
+```
+curl 127.0.0.1:8080/inference \
+-H "Content-Type: multipart/form-data" \
+-F file="@<file-path>" \
+-F temperature="0.0" \
+-F temperature_inc="0.2" \
+-F prompt="<prompt>" \
+-F carry_initial_prompt="true" \
+-F response_format="json"
+```
+
+**/load**
+```
+curl 127.0.0.1:8080/load \
+-H "Content-Type: multipart/form-data" \
+-F model="<path-to-model-file>"
+```
+
+## Load testing with k6
+
+> **Note:** Install [k6](https://k6.io/docs/get-started/installation/) before running the benchmark script.
+
+You can benchmark the Whisper server using the provided bench.js script with [k6](https://k6.io/). This script sends concurrent multipart requests to the /inference endpoint and is fully configurable via environment variables.
+
+**Example usage:**
+
+```
+k6 run bench.js \
+  --env FILE_PATH=/absolute/path/to/samples/jfk.wav \
+  --env BASE_URL=http://127.0.0.1:8080 \
+  --env ENDPOINT=/inference \
+  --env CONCURRENCY=4 \
+  --env TEMPERATURE=0.0 \
+  --env TEMPERATURE_INC=0.2 \
+  --env RESPONSE_FORMAT=json
+```
+
+**Environment variables:**
+- `FILE_PATH`: Path to the audio file to send (must be absolute or relative to the k6 working directory)
+- `BASE_URL`: Server base URL (default: `http://127.0.0.1:8080`)
+- `ENDPOINT`: API endpoint (default: `/inference`)
+- `CONCURRENCY`: Number of concurrent requests (default: 4)
+- `TEMPERATURE`: Decoding temperature (default: 0.0)
+- `TEMPERATURE_INC`: Temperature increment (default: 0.2)
+- `RESPONSE_FORMAT`: Response format (default: `json`)
+
+**Note:**
+- The server must be running and accessible at the specified `BASE_URL` and `ENDPOINT`.
+- The script is located in the same directory as this README: `bench.js`.

examples/server/bench.js

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+import http from 'k6/http'
+import { check } from 'k6'
+
+export let options = {
+  vus: parseInt(__ENV.CONCURRENCY) || 4,
+  iterations: parseInt(__ENV.CONCURRENCY) || 4,
+}
+
+const filePath        = __ENV.FILE_PATH
+const baseURL         = __ENV.BASE_URL        || 'http://127.0.0.1:8080'
+const endpoint        = __ENV.ENDPOINT        || '/inference'
+const temperature     = __ENV.TEMPERATURE     || '0.0'
+const temperatureInc  = __ENV.TEMPERATURE_INC || '0.2'
+const responseFormat  = __ENV.RESPONSE_FORMAT || 'json'
+
+// Read the file ONCE at init time
+const fileBin = open(filePath, 'b')
+
+export default function () {
+  const payload = {
+    file:           http.file(fileBin, filePath),
+    temperature:    temperature,
+    temperature_inc: temperatureInc,
+    response_format: responseFormat,
+  }
+
+  const res = http.post(`${baseURL}${endpoint}`, payload)
+  check(res, { 'status is 200': r => r.status === 200 })
+}