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ModelCap

Mistral Nemo

Open weights

Mistral AI·mistralai/mistral-nemo

Mistral Nemo is a language model published by Mistral AI. 4 OpenRouter endpoints are published in the latest snapshot. It accepts text input and returns text. The published context limit is 131K tokens. The catalogue declares support for tool use, structured outputs.

ModelCap Index · Current board
—
Not scored · 0% support · score interval not available
Market Gravity
39.4
Secondary market signal
Input
$0.019
per 1M tokens
Output
$0.03
per 1M tokens
Context
131K
tokens
Providers
4
endpoints
Gateway spend
—
latest · Vercel share

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
DeepInfrafp8Cheapest$0.019$0.03131Kfp896.82%
Parasailfp8$0.03$0.03131Kfp8—
Io Netfp16$0.042$0.16128Kfp1698.13%
Novitafp8$0.04$0.1760Kfp875.73%

Reported evaluation leads (7)

Excluded from score

Structured rows reported in this exact model repository at the pinned revision below. They are useful research leads, but remain quarantined until dataset revision, harness, configuration and identity pass ModelCap’s independent admission review.

Dataset / taskMetricValueRevisionProvenance
thamilvendhan/signalbench
src
—0.3167
Unpinned
not published
Reported
Quarantined
thamilvendhan/signalbench
time
—0.5833
Unpinned
not published
Reported
Quarantined
thamilvendhan/signalbench
access_deny
—0.0833
Unpinned
not published
Reported
Quarantined
thamilvendhan/signalbench
memory_label
—0.3333
Unpinned
not published
Reported
Quarantined
thamilvendhan/signalbench
injection
—0.5
Unpinned
not published
Reported
Quarantined
thamilvendhan/signalbench
bot_policy
—0.0833
Unpinned
not published
Reported
Quarantined
TIGER-Lab/MMLU-Pro
mmlu_pro
—44.81
Unpinned
not published
Reported
Quarantined

ModelCap Index · Current board

Methodology
—
Not scored · excessive distance
Public rank basis
Not scored (abstained)
Index support
0.0% · not applicable
Index interval
Not available
Rank posterior
Not available
Top 5 / Top 10 probability
Not available / Not available
Posterior as of
Snapshot timestamp unavailable
Identity binding
Exact catalogue product · mistralai/mistralai/mistral-nemo · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata mistralai/Mistral-Nemo-Instruct-2407@04d8a90549d23fc6bd7f642064003592df51e9b3 (not the evaluation revision)
Direct benchmark observations
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)
30.0
Liquidity (providers × uptime)
57.2
Open reach (HF downloads)
55.1
Surface (context / tools / modalities)
45.2
Freshness
5.8
  • · OpenRouter popularity #54
  • · 4 live providers
  • · HF 30d downloads 458617
  • · Catalogue: context 131072, tools
  • · First seen 2024-07-19

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
37.5
22.0–52.9 uncertainty interval
Excluded from rank
Confidence
75%
Training support
156 models · 94 lineages
Out-of-domain check
in domain
Feature coverage
100%
Lineage-held-out error
9.1 MAE

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

Deployment readiness

Metadata index
79.6
strong · 80% metadata coverage
Not capability
Artifact reproducibility
100.0
Access & legal clarity
100.0
Deployability
98.5
Evaluation provenance
0.0

Missing: evaluationProvenance.admitted-evaluation-observations, evaluationProvenance.capability-family-breadth, evaluationProvenance.evaluation-source-diversity, evaluationProvenance.identity-and-source-confidence, evaluationProvenance.evaluation-dataset-revisions.

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

Market activity

Venue coverage
Market Gravity
39.4
OpenRouter weekly popularity
#54 of 298

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

Awaiting evaluation

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%
30.0

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
57.2

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

Open reach15%
55.1

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

Freshness5%
5.8

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

Specification

Context window
131K tokens
Max output
16K tokens
Inputs
Text
Outputs
Text
Tokenizer
Mistral
Cached input tokens
Not offered
First seen on OpenRouter
19 Jul 2024
Knowledge cutoff
2024-04-30

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
04d8a90549d2
Parameters
12.2B
Architecture
MistralForCausalLM
Model type
mistral
Hugging Face downloads (30d)
459K
Downloads (all time)
9.8M
Likes
2K
Repository
mistralai/Mistral-Nemo-Instruct-2407
Repository updated
28 Jul 2025, 17:16 UTC
Base lineage
mistralai/Mistral-Nemo-Base-2407