Tasks and inputs
mistralai/Voxtral-Small-24B-2507 is listed for Audio-text-to-text, Text generation. It accepts audio, text and produces text. Use the publisher’s input format and preprocessing for your chosen deployment.
SyncDev model directory · Profile updated Oct 13, 2026
mistralai/Voxtral-Small-24B-2507 is a source-linked Hugging Face repository assigned to Audio-text-to-text. Its recorded task interface accepts audio, text and produces text.
The specification score summarizes recorded features and limits. It is not a benchmark result.
Recorded modality support shows what this model can accept and produce. An undocumented modality is shown as unknown rather than assumed to be unsupported.
Accepts
Produces
mistralai/Voxtral-Small-24B-2507 is a Hugging Face repository returned by the public Audio-text-to-text task feed. Its recorded download count is 277,952 and it has 519 likes when the repository snapshot was collected. Popularity is useful for discovery, but it is not a performance ranking or a guarantee of suitability.
This record is categorized for Audio-text-to-text. A task category describes the intended machine-learning problem; it does not prove that every version, checkpoint, quantization, or deployment method produces the same quality. Teams should read the model card and test representative inputs before choosing it.
The public repository lists vllm as its library metadata. Its recorded tags include vllm, safetensors, voxtral, audio-text-to-text, en, fr, de, es. These source details are retained so readers can trace this directory entry back to the repository instead of relying on copied descriptions.
Use inputs that resemble deployment traffic, including difficult and out-of-domain cases. Compare output correctness, the response format, latency and memory requirements with a simple baseline under the same conditions.
The Hugging Face task assignment records audio, text as input and text as output for mistralai/Voxtral-Small-24B-2507. This interface summary comes from the repository’s recorded Audio-text-to-text task classification. It helps readers distinguish a text, image, audio, video, document, embedding, or prediction workflow without inferring undocumented API behavior. Model wrappers can expose different preprocessing and response formats, so verify the upstream model card and the exact runtime before deployment.
Explore mistralai models and the audio-text-to-text collection. Use the comparison tool to inspect a second candidate.
Compare the model on the work you need to complete.
mistralai/Voxtral-Small-24B-2507 is listed for Audio-text-to-text, Text generation. It accepts audio, text and produces text. Use the publisher’s input format and preprocessing for your chosen deployment.
Documented limits: 32.77K context and 16.38K maximum output. The listed route charges $0.228 input and $0.513 output per million tokens. Measure a completed task using the prompts, documents and tools your application will use. Include reasoning and retries in the result.
The weights are downloadable under the publisher’s model licence. Check runtime support and size the complete model and working context for your expected concurrency.
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