# Spec for the HF README of handy-computer/Voxtral-Small-24B-2507-gguf.
# Consumed by scripts/hf_cards/generate.py.

hf_repo: mistralai/Voxtral-Small-24B-2507
target_repo: handy-computer/Voxtral-Small-24B-2507-gguf
transcribe_docs_url: https://github.com/handy-computer/transcribe.cpp/blob/main/docs/models/voxtral-small-24b-2507.md

upstream_commit: da5b424
pin_date: 2026-06-05

# Validation pin for the most recent upload. Updated on each release —
# older HF revisions carry whatever value was current at their upload time.
validation:
  reference: Transformers
  commit: dac22fa
  date: 2026-06-05

license: apache-2.0
license_display: Apache-2.0
pipeline_tag: automatic-speech-recognition
languages:
  - en
  - fr
  - de
  - es
  - it
  - pt
  - nl
  - hi
tags:
  - gguf
  - transcribe.cpp
  - asr
  - speech-to-text
  - voxtral
  - audio-llm
  - multilingual

summary: |
  Offline audio-LLM speech-to-text and speech translation. A Whisper-large-v3
  bidirectional audio encoder feeds a 4-frame-group projector (375 audio tokens
  per 30 s chunk) into a Mistral-Small-24B causal LM (40 layers, GQA 32/8, NEOX
  RoPE, SwiGLU) via audio-token injection. Takes a 16 kHz mono WAV and produces a
  transcript via greedy decoding. The larger sibling of Voxtral Mini 3B — same
  encoder, projector, frontend, and tokenizer, with a scaled-up decoder.

default_quant_index: 2  # Q8_0

# Capability flags for the transcribe_cpp metadata block.
capabilities:
  streaming: false
  translate: true
  lang_detect: true
  timestamps: none  # none | segment | word | token

# Speedup-over-realtime (×RT) per rig/backend, from docs/models; published
# raw as rtf_<machine> in the metadata block.
perf:
  m4-max:
    metal: 3.2

wer:
  source: LibriSpeech test-clean
  notes: |
    WER measured on the full LibriSpeech test-clean split (2620 utterances) with
    the Whisper English text normalizer, greedy decoding, batch size 8 on an
    NVIDIA A100 80 GB. Same-machine HuggingFace transformers reference
    (VoxtralForConditionalGeneration, BF16, greedy): 1.57%; the BF16 GGUF matches
    at 1.56%. Validation for this variant is end-to-end by WER — the family's
    tensor-level numerical parity is established by the Voxtral Mini 3B sibling
    (identical architecture).

quants:
  - name: BF16
    filename: Voxtral-Small-24B-2507-BF16.gguf
    size: 48.54 GB
    wer: 1.56%
  - name: F16
    filename: Voxtral-Small-24B-2507-F16.gguf
    size: 48.55 GB
    wer: 1.57%
  - name: Q8_0
    filename: Voxtral-Small-24B-2507-Q8_0.gguf
    size: 25.81 GB
    wer: 1.56%
  - name: Q6_K
    filename: Voxtral-Small-24B-2507-Q6_K.gguf
    size: 19.94 GB
    wer: 1.58%
  - name: Q5_K_M
    filename: Voxtral-Small-24B-2507-Q5_K_M.gguf
    size: 17.14 GB
    wer: 1.60%
  - name: Q4_K_M
    filename: Voxtral-Small-24B-2507-Q4_K_M.gguf
    size: 14.30 GB
    wer: 2.11%
