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ModelCap

Voxtral Small 24B 2507

Official publisher releaseOpen weights

Mistral AI

Voxtral Small 24B 2507 is a language model from Mistral AI. It does not hold a position on ModelCap's current board yet; it is placed automatically once its model card or a public benchmark compares it with ranked models. It is listed at $0.10 per million input tokens and $0.30 per million output tokens from one provider. It reads up to 33K tokens of context, and its weights are openly downloadable.

Figures as of 6 Nov 2026, 20:32 UTC · download the public dataset · methodology

ModelCap Index · Current board
—
Index position pending
Market Gravity
10.6Decreased by 0.2
Secondary market signal
Input
$0.10
per 1M tokens
Output
$0.30
per 1M tokens
Context
33K
tokens
Providers
1
2 endpoints

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
MistralzdrCheapest$0.10$0.3033K—100.0%
Mistraleu$0.11$0.3332K—100.0%

Reported evaluation leads (15)

Not independent measurement

Structured rows reported in this exact model repository at the pinned revision below. They are the publisher talking about itself: never measured evidence, never a score input on their own. They remain quarantined until dataset revision, harness, configuration and identity pass ModelCap’s independent admission review.

Dataset / taskMetricValueRevisionProvenance
hf-audio/open-asr-leaderboard
mean_wer
—6.62
Unpinned
not published
Reported
Quarantined
hf-audio/open-asr-leaderboard
rtfx
—54.09
Unpinned
not published
Reported
Quarantined
hf-audio/open-asr-leaderboard
ami_wer
—15.27
Unpinned
not published
Reported
Quarantined
hf-audio/open-asr-leaderboard
earnings22_wer
—10.5
Unpinned
not published
Reported
Quarantined
hf-audio/open-asr-leaderboard
gigaspeech_wer
—9.81
Unpinned
not published
Reported
Quarantined
hf-audio/open-asr-leaderboard
librispeech_clean_wer
—1.59
Unpinned
not published
Reported
Quarantined
hf-audio/open-asr-leaderboard
librispeech_other_wer
—3.26
Unpinned
not published
Reported
Quarantined
hf-audio/open-asr-leaderboard
spgispeech_wer
—2.02
Unpinned
not published
Reported
Quarantined
hf-audio/open-asr-leaderboard
tedlium_wer
—3.52
Unpinned
not published
Reported
Quarantined
hf-audio/open-asr-leaderboard
voxpopuli_wer
—6.96
Unpinned
not published
Reported
Quarantined
MBZUAI/longshot-bench
overall
—48.56
Unpinned
not published
Reported
Quarantined
MBZUAI/longshot-bench
core_perception
—39.66
Unpinned
not published
Reported
Quarantined
MBZUAI/longshot-bench
reasoning
—56.12
Unpinned
not published
Reported
Quarantined
MBZUAI/longshot-bench
information
—49.93
Unpinned
not published
Reported
Quarantined
MBZUAI/longshot-bench
multimodal
—48.54
Unpinned
not published
Reported
Quarantined

ModelCap Index · Current board

Methodology
—
Index position pending
Technical details
Public rank basis
Index position pending (abstained)
Evidence label
Index position pending · placement uncalibrated
Index support
0.0% · not applicable
Identity binding
Exact catalogue product · mistralai/mistralai/voxtral-small-24b-2507 · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata mistralai/Voxtral-Small-24B-2507@da5b42409f279fdd92febee0511a6c32828569c1 (not the evaluation revision)
Index observations used
0
Architecture fallback
abstained · 0% coverage · 0 anchors
Bayesian Evidence Score · measured evidence input only

BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.

Observed capability
—
Evidence status
No admitted measured evidence
General preference
—
Coding
—
Agents & tools
—
Reasoning
—
Evidence breadth
0%
Evidence coverage
0%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
3.2
Liquidity (providers × uptime)
24.3
Open reach (HF downloads)
10.7
Surface (context / tools / modalities)
50.1
Freshness
24.2
  • · OpenRouter popularity #282
  • · 1 live provider
  • · HF 30d downloads 6653
  • · Catalogue: context 32768, tools, modalities Text/Audio/File
  • · First seen 2025-10-30

These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.

The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.

Experimental capability estimate

Estimate policy
22.9
8.7–37.0 uncertainty interval
Excluded from rank
Confidence
77%
Training support
221 models · 129 lineages
Out-of-domain check
in domain
Feature coverage
100%
Lineage-held-out error
8.3 MAE

Experimental estimate. This layer predicts from admitted evidence and safe metadata only. It never enters ModelCap Score or rank.

Deployment readiness

Metadata index
74.0
partial · 80% metadata coverage
Not capability
Artifact reproducibility
100.0
Access & legal clarity
100.0
Deployability
80.0
Evaluation provenance
0.0

Not yet published: admitted benchmark results, results across several capability areas, results from more than one source, a confident match to its benchmark entries, pinned evaluation dataset versions.

A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.

Market activity

Venue coverage
Market Gravity
10.6
OpenRouter weekly popularity
#282 of 339

Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.

Arena preference

No matched Arena rating

This model is visible because it is available in the live catalogue, but it has no trustworthy community result yet. ModelCap does not infer a quality score from price, features, or market activity.

Market Gravity breakdown

Usage55%
3.2

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
24.3

Independent providers versus the model's open or closed cohort, weighted by uptime.

Open reach15%
10.7

Hugging Face 30-day downloads for open models; neutral for closed models.

Freshness5%
24.2

Time since first public availability, on a six-month half-life.

Specification

Model ID
mistralai/voxtral-small-24b-2507
Context window
33K tokens
Declared output cap
26K tokens

OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata

Inputs
Text, Audio, File
Outputs
Text
Tokenizer
Mistral
Cached input tokens
$0.01 / 1M
First seen on OpenRouter
30 Oct 2025

Capabilities

  • Not supported: Reasoning
  • Supported: Tool use
  • Supported: Structured output
  • Supported: Response format
  • Not supported: Moderated

Weights & access

Open weights. Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI.

Access
Open weights
Licence
apache-2.0
Pinned revision
da5b42409f27
Parameters
24.3B
Architecture
VoxtralForConditionalGeneration
Model type
voxtral
Hugging Face downloads (30d)
7K
Downloads (all time)
996K
Likes
556
Repository updated
20 Dec 2025, 23:34 UTC

Voxtral Small 24B 2507: common questions

How does Voxtral Small 24B 2507 rank among AI models?

Voxtral Small 24B 2507 has no public ModelCap Index position as of 6 November 2026: the snapshot lacks enough matched benchmark evidence, or the identity match is unresolved. Its catalogue facts (price, context, providers) are shown without a rank.

How much does Voxtral Small 24B 2507 cost per 1M tokens?

Voxtral Small 24B 2507 is listed at $0.10 per 1M input tokens and $0.30 per 1M output tokens as of 6 November 2026. Prices come from the OpenRouter catalogue and re-observe on every refresh. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $0.35 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.

What is the context window of Voxtral Small 24B 2507?

Voxtral Small 24B 2507 has a published context window of 33K tokens (32,768). The snapshot lists a 26,214 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context limit.

Is Voxtral Small 24B 2507 open-weight?

Open weights (apache-2.0). Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI. The repository is mistralai/Voxtral-Small-24B-2507 on Hugging Face.

Which API providers serve Voxtral Small 24B 2507?

One provider serves Voxtral Small 24B 2507 through OpenRouter as of 6 November 2026: Mistral. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

When was Voxtral Small 24B 2507 released?

Voxtral Small 24B 2507 first appeared in the catalogue on 30 Oct 2025. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.