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whisper-large-v3-turbo-russian
MECHUK/whisper-large-v3-turbo-russian
whisper-large-v3-turbo-russian is a automatic speech recognition model from MECHUK. Use it when you need speech turned into text. It is set up for whisper.cpp. The card lists the license as mit.
GGML artifacts for running dvislobokov/whisper-large-v3-turbo-russian with whisper.cpp in the whisper-ru local ASR server.
Access
Public
Updated Jul 3, 2026
Repo size
2.2 GB
Likes
1
Public
Repo makeup
Click a slice to open those files.
.bin2.2 GB · 100%
At a glance
- Task
- Automatic Speech Recognition
- Library
- whisper.cpp
- License
- mit
- Access
- Public
- Created
- Jul 3, 2026
- Updated
- Jul 3, 2026
- SHA
- 33196872
Base models
Model card
From the Hugging Face model README
whisper-ru GGML artifacts
GGML artifacts for running
dvislobokov/whisper-large-v3-turbo-russian
with whisper.cpp in the whisper-ru local ASR server.
Files
| File | Purpose |
|---|---|
ggml-large-v3-turbo-russian-q5_k.bin | Recommended runtime model; Q5_K quantized GGML |
ggml-large-v3-turbo-russian-f16.bin | Optional conversion artifact; useful for re-quantization |
For public distribution, publishing only the Q5_K file is enough for normal API users. Keep F16 private unless you explicitly want to support downstream re-quantization.
Source model
- Base/fine-tuned model:
dvislobokov/whisper-large-v3-turbo-russian - Declared license of the source model card: MIT
- Base model lineage:
openai/whisper-large-v3-turbo
Usage
The code repo's idempotent setup command downloads this ready-to-run Q5_K file by default:
docker compose run --rm whisper-api prepare-model
To rebuild from the source Hugging Face model instead:
PREPARE_MODEL_FROM_SOURCE=true docker compose run --rm whisper-api prepare-model
Source rebuild pipeline:
- Download the Hugging Face model snapshot.
- Convert Transformers/Safetensors weights to GGML F16 with whisper.cpp.
- Quantize F16 to Q5_K with
whisper-quantize.
Runtime behavior
The whisper-ru API server uses Silero VAD by default before decoding. This
prevents non-speech audio, silence, and microphone tails from reaching Whisper
and producing subtitle-like hallucinations such as Продолжение следует....
Clients can explicitly request raw Whisper decoding with vad=false or
X-VAD: false.
Reference benchmark
AMD Radeon 780M / Vulkan / Q5_K:
Audio duration: 60.000s
Wall time: 3.534s
RTF: 0.059
Benchmarks are hardware- and driver-dependent.
- Task
- Automatic Speech Recognition
- Library
- whisper.cpp
- License
- mit
- Languages
- ru
- Created
- Jul 3, 2026
- Updated
- Jul 3, 2026