ModelRefs / Mistral Small 3.1 by Mistral AI — Benchmarks, Pricing & Rev…

Mistral Small 3.1 by Mistral AI — Benchmarks, Pricing & Rev…

Mistral Small 3.1 (Mistral AI): Mistral Small 3.1 by Mistral AI.. 128K context. Pricing: from $0.00010/1K in. Specs, benchmarks and code examples.

What this reference supports

Mistral Small 3.1 is Mistral AI's 24B open-weight model released under Apache 2.0, adding image understanding and an expanded context window to the Small family's low-latency positioning. It targets teams that want a permissively licensed, self-hostable workhorse and are willing to validate quality against larger hosted models per task.

Mistral Small 3.1 is attributed to Mistral AI in ModelRefs' canonical registry. Tracked modalities: Text input and output, Image input. Primary use cases considered on ModelRefs: Low-latency assistants, extraction, and classification on self-managed or hosted endpoints; Permissive-license deployments where Apache 2.0 simplifies commercial use.

This ModelRefs profile is Provisional and pending review — decision-support material, not a final or universal ranking. Confirm current behavior, access, pricing, limits, licensing, and lifecycle in Mistral AI's own documentation, and evaluate Mistral Small 3.1 on representative workloads before implementation.

Benchmark & Evaluation

ModelRefs currently has partial, narrow benchmark coverage for Mistral Small 3.1. Treat the available benchmark evidence as one input to the decision, not a guarantee that Mistral Small 3.1 is the strongest option for your workload, and evaluate it on representative workloads before selecting it.

  • No benchmark score is imported into this editorial record. Provider-reported evaluations support scoped notes only; canonical score records are governed separately with their own provenance.
  • Mistral's release notes report provider-run evaluations against peer small models; runtime and template differences affect reproduction.

Implementation considerations

  • Validate multimodal and long-context behavior on your runtime; small-model quality varies more across tasks than family marketing suggests.
  • Compare self-hosted serving cost against Mistral's hosted endpoint for your volume before committing infrastructure.
  • Open weights distributed via Hugging Face under Apache 2.0; also served through Mistral's hosted platform and third-party hosts.
  • Hosted and self-hosted deployments differ in version pinning, quotas, and data controls; map the exact artifact or endpoint before comparing.

Risks and limitations

  • Open-weight results depend on the exact runtime, precision, quantization, and prompt template; reference results do not transfer automatically.
  • The release-specific license and acceptable-use policy must be reviewed before commercial deployment.

Source coverage

This reference is Provisional. Model behavior, access, pricing, limits, and lifecycle can change; verify the linked provider documentation and run task-specific evaluations before implementation.

Known coverage gaps:

  • Independent multimodal and long-context evaluation reproduction is not attached.
  • Hosted-versus-self-hosted total-cost evidence is incomplete.

Sources

Continue your research

Use these connected ModelRefs sections to compare alternatives, inspect implementation paths, and review the evidence and governance boundaries relevant to Mistral Small 3.1 by Mistral AI — Benchmarks, Pricing & Rev….