alt.freeweights.mistral / Voxtral-Mini-3B-2507-ONNX
From: onnx-community <huggingface.co/onnx-community>Newsgroups: alt.freeweights.mistralSubject:

Voxtral-Mini-3B-2507-ONNX

Date: 2026-11-15Commit: d2c87bbSigned: 2DC28CC7B26A283B ✓

Audio text to text model. Onnx weights, 36.5 GB in all. Published by onnx-community under Apache-2.0.

mistral36.5GBVoxtral-Mini-3B-2507-ONNXonnxpermissive
FactsParamsnot statedSize36.5 GBFormatsonnxTaskaudio text to textLicenseApache-2.0From sourcepermissive
$ fw get onnx-community/Voxtral-Mini-3B-2507-ONNX
# manifest sha256 76e17faf79d3… · 36.5 GB · 54 files
$ fw verify ./Voxtral-Mini-3B-2507-ONNX onnx-community/Voxtral-Mini-3B-2507-ONNX
From sourceHosted (signed)onnx-community/Voxtral-Mini-3B-2507-ONNXLast check: 2026-11-15 05:12 UTC

Get help: custom fine-tune or private deploy. We review your setup before we quote.

Quantized of Voxtral-Mini-3B-2507.

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Overview

Size
36.5 GB
Weights
252 MB (smallest of 16 ONNX variants)
Parameters
not stated
Formats
onnx
Task
audio text to text
License
Apache-2.0 (permissive)
Files
54, each with a sha256
Publisher
onnx-community
Added
2026-11-15
Section
alt.freeweights.mistral
Lineage

Original release from the publisher.

Base model: mistralai/Voxtral-Mini-3B-2507

Where these bytes come from
Publisher at the pinned commit→You

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From sourcehuggingface.co2026-11-15 05:12 UTCpassed

Model card

From the publisher at commit d2c87bb. Shown as plain text with links; images open at the publisher.

Voxtral Mini 1.0 (3B) - 2507#

Voxtral Mini is an enhancement of Ministral 3B, incorporating state-of-the-art audio input capabilities while retaining best-in-class text performance. It excels at speech transcription, translation and audio understanding.

This repository contains ONNX weights for the original model, mistralai/Voxtral-Mini-3B-2507.

Learn more about Voxtral in their blog post here.

Key Features#

Voxtral builds upon Ministral-3B with powerful audio understanding capabilities.

  • Dedicated transcription mode: Voxtral can operate in a pure speech transcription mode to maximize performance. By default, Voxtral automatically predicts the source audio language and transcribes the text accordingly
  • Long-form context: With a 32k token context length, Voxtral handles audios up to 30 minutes for transcription, or 40 minutes for understanding
  • Built-in Q&A and summarization: Supports asking questions directly through audio. Analyze audio and generate structured summaries without the need for separate ASR and language models
  • Natively multilingual: Automatic language detection and state-of-the-art performance in the world’s most widely used languages (English, Spanish, French, Portuguese, Hindi, German, Dutch, Italian)
  • Function-calling straight from voice: Enables direct triggering of backend functions, workflows, or API calls based on spoken user intents
  • Highly capable at text: Retains the text understanding capabilities of its language model backbone, Ministral-3B

Benchmark Results#

Audio#

Average word error rate (WER) over the FLEURS, Mozilla Common Voice and Multilingual LibriSpeech benchmarks:

Image: image/png

Text#

Image: image/png

Usage#

Notes:

  • temperature=0.2 and top_p=0.95 for chat completion (e.g. Audio Understanding) and temperature=0.0 for transcription
  • Multiple audios per message and multiple user turns with audio are supported
  • System prompts are not yet supported
Transformers.js#
Online demo#

Try it out with our online demo:

Code snippets#

If you haven't already, you can install the Transformers.js JavaScript library from NPM using:

npm i @huggingface/transformers

Example: Transcription

import { VoxtralForConditionalGeneration, VoxtralProcessor, TextStreamer, read_audio } from "@huggingface/transformers";

// Load the processor and model
const model_id = "onnx-community/Voxtral-Mini-3B-2507-ONNX";
const processor = await VoxtralProcessor.from_pretrained(model_id);
const model = await VoxtralForConditionalGeneration.from_pretrained(
    model_id,
    {
        dtype: {
            embed_tokens: "fp16", // "fp32", "fp16", "q8", "q4"
            audio_encoder: "q4", // "fp32", "fp16", "q8", "q4", "q4f16"
            decoder_model_merged: "q4", // "q4", "q4f16"
        },
        device: "webgpu",
    },
);

// Prepare the conversation
const conversation = [
    {
        "role": "user",
        "content": [
            { "type": "audio" },
            { "type": "text", "text": "lang:en [TRANSCRIBE]" },
        ],
    }
];
const text = processor.apply_chat_template(conversation, { tokenize: false });
const audio = await read_audio("http://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/mlk.wav", 16000);
const inputs = await processor(text, audio);

// Generate the response
const generated_ids = await model.generate({
    ...inputs,
    max_new_tokens: 256,
    streamer: new TextStreamer(processor.tokenizer, { skip_special_tokens: true, skip_prompt: true }),
});

// Decode the generated tokens
const new_tokens = generated_ids.slice(null, [inputs.input_ids.dims.at(-1), null]);
const generated_texts = processor.batch_decode(
    new_tokens,
    { skip_special_tokens: true },
);
console.log(generated_texts[0]);
// I have a dream that one day this nation will rise up and live out the true meaning of its creed.

Example: Audio understanding

import { VoxtralForConditionalGeneration, VoxtralProcessor, TextStreamer, read_audio } from "@huggingface/transformers";

// Load the processor and model
const model_id = "onnx-community/Voxtral-Mini-3B-2507-ONNX";
const processor = await VoxtralProcessor.from_pretrained(model_id);
const model = await VoxtralForConditionalGeneration.from_pretrained(
    model_id,
    {
        dtype: {
            embed_tokens: "fp16", // "fp32", "fp16", "q8", "q4"
            audio_encoder: "q4", // "fp32", "fp16", "q8", "q4", "q4f16"
            decoder_model_merged: "q4", // "q4", "q4f16"
        },
        device: "webgpu",
    },
);

// Prepare the conversation
const conversation = [
    {
        "role": "user",
        "content": [
            { "type": "audio" },
            { "type": "audio" },
            { "type": "text", "text": "Describe these two audio clips in detail." },
        ],
    }
];
const text = processor.apply_chat_template(conversation, { tokenize: false });
const audio = await Promise.all([
    read_audio("https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/jfk.wav", 16000),
    read_audio("https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/mlk.wav", 16000),
]);
const inputs = await processor(text, audio);

// Generate the response
const generated_ids = await model.generate({
    ...inputs,
    max_new_tokens: 256,
    streamer: new TextStreamer(processor.tokenizer, { skip_special_tokens: true, skip_prompt: true }),
});

// Decode the generated tokens
const new_tokens = generated_ids.slice(null, [inputs.input_ids.dims.at(-1), null]);
const generated_texts = processor.batch_decode(
    new_tokens,
    { skip_special_tokens: true },
);
console.log(generated_texts[0]);
// The first audio clip is a speech by a leader, likely a politician or a public figure, addressing a large audience. The speaker begins by encouraging the listeners to ask not what their country can do for them, but what they can do for their country. This is a call to action and a reminder of the individual's responsibility to contribute to the nation's well-being. The second audio clip is a passionate speech by a different leader, possibly a civil rights activist or a community organizer. This speaker expresses a dream of a nation that will rise up and live out the true meaning of its creed, suggesting a vision of a more just and equitable society.

Files

54 files · 36.5 GBWeights 252 MB (smallest of 16 ONNX variants). Sizes and sha256 from the signed manifest.
Show all 54 files with their sha256
FileSizesha256
.gitattributes3.65 KBe519b6437f6e231c046a46f40f04fd847d3ee877ad3ba32ed3bacbeb1665e6ac
README.md7.21 KBd99f84788b8ca48691af7c80d6b242509a7bc1e44ad417fca040dc00066c7cec
chat_template.jinja989 B0432c899a473d514a8c3dda5f33eafc9f346313c65e3ae181a0fc82195d4fa37
config.json2.16 KBe1b7a6c5f656e7069e72a803a524561c8d4f18d13765a06883d21c98869a51ab
generation_config.json107 Bcbeb6d6c2be7099112785f0676a3d4d5afea49fe5f7c1c7cc41e2d43a954b560
onnx/audio_encoder.onnx357 KB47fc3e2c046b8c9ba19dc4ffe195b6606840edc74179e69bd4f7261686cff511
onnx/audio_encoder.onnx_data2.10 GBfb1a2baa8eb44a51cbef5cc91ead26a7226c8004d0084b873dedbc4efd1712ba
onnx/audio_encoder.onnx_data_1553 MB2125dbd94d2405064f503c9ca13c1efdddfdd9df2854aeb76e0a2ac77111dc29
onnx/audio_encoder_bnb4.onnx405 KBe4418e53b50540e6581cbce958a1d705c31741965ed01fd42346d47254006d6a
onnx/audio_encoder_bnb4.onnx_data399 MB5652ecf0027b5e65f797c1f444c538e6673940fe9116c769c426890f8d54fd9e
onnx/audio_encoder_fp16.onnx360 KBc8367654c6e1b64e799fd581bc607aca3aa77b6bcb0a532a6326a1932aa6728b
onnx/audio_encoder_fp16.onnx_data1.32 GBb1c5a7fb2d6784483943d30040b2c17d5186cbd5f7ab14e027c3abd7e566a32e
onnx/audio_encoder_int8.onnx601 KBddb743e492888cf8eb3fbc77efbfd6a5154f4b21a39a8d3e22cf29832719d283
onnx/audio_encoder_int8.onnx_data669 MBbf06e83302b02f9fb59751eaf594d8677c1d3d5ae2541d8b28cceedaeeb0f819
onnx/audio_encoder_q4.onnx402 KB38b4e8bc6b7dda75a3c52e358a44a8c4e144b4878ff8867bd0cb41a402d4af81
onnx/audio_encoder_q4.onnx_data440 MB07537c1791da2d198edca192b7b15c4199c1c70c3eb095d7a432431bc52e1ae5
onnx/audio_encoder_q4f16.onnx404 KB156a6291053180757636c0caf5f6be3a4e08b90afd93d77646a6bd609ace206e
onnx/audio_encoder_q4f16.onnx_data384 MB62eba37624325b3b21c51edf6c6823aaa8ce9657979dbffc31751c7f0d8d9709
onnx/audio_encoder_quantized.onnx603 KB4db2e57b57f836f3f12deecba456785c888ddc4768cbe1d6c28e379ee479dc79
onnx/audio_encoder_quantized.onnx_data669 MB29a112e764c22a77d20fe5b4925c709a2188a3e5264ef76116420db469fb7fdf
onnx/audio_encoder_uint8.onnx601 KB644e50318802c691623b85fd940ac60164cd904b72d1d81f658fbbab22c6506d
onnx/audio_encoder_uint8.onnx_data669 MB29a112e764c22a77d20fe5b4925c709a2188a3e5264ef76116420db469fb7fdf
onnx/decoder_model_merged.onnx227 KB4e101f5f00fad06ff4de9ba06a18e529b1b238c77cecbaf7a83f2dd21f336209
onnx/decoder_model_merged.onnx_data2.01 GBf08d2cb408774380ae5f25aedb2b29f08b2a67167bfaddb83833127d0988272d
onnx/decoder_model_merged.onnx_data_12.04 GB8824af4dd1a6bda4c348924701d2b78e9b9b982eee6e79c00c311fbe71436720
onnx/decoder_model_merged.onnx_data_22.09 GB906367bee2870dedf649e48c59cbba1602b0c009b80a2fe75d1e3ead80ed4eee
onnx/decoder_model_merged.onnx_data_32.06 GB5f0dd468461fb57d33b5a3cca33442bcf7f53c73d9a5818419d0cdb16c6340e5
onnx/decoder_model_merged.onnx_data_42.04 GB7e8db09e022033239103c7ab042e8297b0768d0c4566d6fa9b64611dd62f3c13
onnx/decoder_model_merged.onnx_data_52.04 GB531cd0d701944232b7487648b7154e19fab693b9ee120469543362e380923fb8
onnx/decoder_model_merged.onnx_data_6629 MB19ce9b0777369a103d6c6f2700909b11c3ed9ac8c17ced14730829482d3d4a6a
onnx/decoder_model_merged.onnx_data_71.61 GB152030f3a13ed418571c431be4275b634eb40ea554ef74f917526ee896413962
onnx/decoder_model_merged_fp16.onnx228 KBc77e254b27448c04b6f027c8040ce4f2429f999453b496ea2af8e79aa4a9c195
onnx/decoder_model_merged_fp16.onnx_data2.07 GB5ae4f71eb0994d28e915b5a5e12c3b1bbfb81b7ced25be4bd6698d60e71cb276
onnx/decoder_model_merged_fp16.onnx_data_12.09 GBf207b9da920da6f837d35f38611c65ef3e28e089b91d19272273c4deac797204
onnx/decoder_model_merged_fp16.onnx_data_22.08 GBcf5cab82a3871665c485cf00d199aa55cac4249487219928cb0632527ea7228f
onnx/decoder_model_merged_fp16.onnx_data_31.02 GB28b309c4dde22701d67a210b1c90bca5ae143fc2de33b98ed43ef14488880fa6
onnx/decoder_model_merged_q4.onnx307 KB25b33b24b1737410defd6035e84664f3810d73b1591b4f350dda1911910c0175
onnx/decoder_model_merged_q4.onnx_data2.07 GB224f9159d5c1843babd6cc99f220c14ce42f7400c56a1cf5102adea8ec029b08
onnx/decoder_model_merged_q4.onnx_data_1252 MBbdd87806c69de54c19576e425639109e2961196c4618843e0c0ce389af93b531
onnx/decoder_model_merged_q4f16.onnx308 KB00ef33f598043ce7640b2353ca13511bb40c2ce0ecc049cc4930f8fa515cd8c2
onnx/decoder_model_merged_q4f16.onnx_data2.07 GB35f8d88fe9d0af7759bbcd7e34843687e8768a4088c229757601aa6a1be1dc2a
onnx/embed_tokens.onnx299 Bd1b1350a79d62150ebb3899cbf824ccf74820b94ca23b9f0ff67b69834499944
onnx/embed_tokens.onnx_data1.61 GB3801b085f29d922117bcc4e0c484f1652de50b015d8ff6721303584a0d3e914f
onnx/embed_tokens_fp16.onnx494 Bed64cab8592c4731ac4c8b4fc59baad6756f040a642390ee07c7e9c9ec56879a
onnx/embed_tokens_fp16.onnx_data805 MB5f8ec7534e487edaec0d707980ecf4cd4bf66db7ecc6ef8cfb5f717a565a0616
onnx/embed_tokens_q4.onnx542 B0aced72ee68efcb5feaccbe5d3bb454e8a6d44cec9cfd6f5aece7272255d43a3
onnx/embed_tokens_q4.onnx_data252 MB6a2dbc92241c261aa99b0fb920ccfdcf9c4f2d3b97ed51c06d670c99e633e594
onnx/embed_tokens_quantized.onnx552 B198b066c7f5bef2776e001934ac2eff76ea89e93d072d577ace5ba16ab08281e
onnx/embed_tokens_quantized.onnx_data403 MB681ef4fdd1f9e7857872405b174dc68955cd75428e35591376c2630f7b5bdc01
preprocessor_config.json357 B86d67d926e17d3a9bb0bae334c9fc46bc163181992357a0357c0aec2c7e131d1
special_tokens_map.json414 B6fa06efa2785e450051989a6f8fb4416b10149ded485ddd3f127a40734f5cfd0
tekken.json14.9 MB4aaf3836c2a5332f029ce85a7a62255c966f47b6797ef81dedd0ade9c862e4a8
tokenizer.json12.6 MB7e18748766f9c939f2ec40506e922b46e89f5aef8bc6ce13ec12b1a11c597550
tokenizer_config.json178 KBd76d4d7e13f3acc40bd1d83a7543c6ab6944e7f8a30f05f0ca9a0d81f57726bd
VersionsEach time the pinned upstream commit or file list changed in this repo. Newest first.
Upstream commitDateContents
d2c87bb634 pinned now2026-11-15 05:12 UTC54 files · 36.5 GB

Use it

$ fw get onnx-community/Voxtral-Mini-3B-2507-ONNX
# manifest sha256 76e17faf79d3… · 36.5 GB · 54 files
$ fw verify ./Voxtral-Mini-3B-2507-ONNX onnx-community/Voxtral-Mini-3B-2507-ONNX
fw.pyChecks the signature and every sha256, tries each source in order, resumes.
$ python3 fw.py get https://freeweights.allternit.com/manifests/onnx-community/Voxtral-Mini-3B-2507-ONNX.json --dir ./Voxtral-Mini-3B-2507-ONNX $ python3 fw.py verify ./Voxtral-Mini-3B-2507-ONNX ./onnx-community__Voxtral-Mini-3B-2507-ONNX.json
hfThe Hugging Face CLI with one setting. Same repo id.
$ HF_ENDPOINT=https://freeweights.allternit.com hf download onnx-community/Voxtral-Mini-3B-2507-ONNX --revision d2c87bb634d1dfaeea8b5eb388704d657f2ff8e9 --local-dir ./Voxtral-Mini-3B-2507-ONNX

License

Name
Apache License 2.0
Id
Apache-2.0
Class
Permissive
Redistribution
yes
Listing
Hosted (signed)
Decided
License as declared by the publisher. No person read it. 2026-11-15
Text in
README.md
Text sha256
d99f84788b8ca48691af7c80d6b242509a7bc1e44ad417fca040dc00066c7cec
Terms gate
No extra terms beyond the license.

Read the license text

Licenses are checked against the license table. A custom license passes only after a person reads it.

Provenance

From: onnx-community <huggingface.co/onnx-community>Newsgroups: alt.freeweights.mistralSubject: Voxtral-Mini-3B-2507-ONNXDate: 2026-11-15Commit: d2c87bbSigned: 2DC28CC7B26A283B ✓
Upstream
onnx-community/Voxtral-Mini-3B-2507-ONNX
Pinned commit
d2c87bb634d1dfaeea8b5eb388704d657f2ff8e9
Manifest
Voxtral-Mini-3B-2507-ONNX.json · .minisig
Manifest sha256
76e17faf79d33df373c71c88a9fad12abae3bbf4953dc9af037eab4a537f5fa6
Signature
minisign, Ed25519, key 2DC28CC7B26A283B
Created
2026-11-15 05:12 UTC
Generator
freeweights-manifest/0.1.0
Takedowns
None.

How to verify

$ curl -O https://freeweights.allternit.com/manifests/onnx-community/Voxtral-Mini-3B-2507-ONNX.json $ curl -O https://freeweights.allternit.com/manifests/onnx-community/Voxtral-Mini-3B-2507-ONNX.json.minisig $ minisign -Vm Voxtral-Mini-3B-2507-ONNX.json -P RWQ7KGqyx4zCLXtUFOqvfv8L3g+8fpKJ1FsuxPyOYMF+4KufbUxKq1Oq $ shasum -a 256 <file> # compare with the Files tab

A manifest whose signature fails must be rejected. A file whose size or sha256 does not match must be discarded. Verify a download

Model tree

Parent

mistralai/Voxtral-Mini-3B-2507 · this model is a quantization of it

No model in the catalog names this one as its parent.

Get it
Download
$ HF_ENDPOINT=https://freeweights.allternit.com hf download onnx-community/Voxtral-Mini-3B-2507-ONNX
Open in Freeweights Studio

Pull, verify and run it in the Allternit app on Desktop, web or phone.

Signed manifest
minisign, key 2DC28CC7B26A283B. Voxtral-Mini-3B-2507-ONNX.json. Provenance. Takedown history: none.
From: bartowski <huggingface.co/bartowski>Subject: alamios_Mistral-Small-3.1-DRAFT-0.5B-GGUF
From: microsoft <huggingface.co/microsoft>Subject: chatbench-mistral-7b
From: NousResearch <huggingface.co/NousResearch>Subject: DeepHermes-3-Mistral-24B-Preview
From: mistralai <huggingface.co/mistralai>Subject: Devstral-Small-2-24B-Instruct-2512
From: mlx-community <huggingface.co/mlx-community>Subject: Devstral-Small-2-24B-Instruct-2512-4bit
From: mlx-community <huggingface.co/mlx-community>Subject: Devstral-Small-2-24B-Instruct-2512-6bit