Ethical Stack.

Mistral Small 4

119B mixture-of-experts model with 6.5B active parameters, text-and-image input, reasoning modes, function calling and a 256k context.

Score calculation

(3 + 1 + 7 + 2 + 3) ÷ 5 = 3.2

5 of six dimensions rated. Unrated dimensions are excluded from the average.

Full scoring method ↗
Setup details

Mistral Small 4 release v26.03 weights and Mistral-hosted API model mistral-small-2603; local and hosted handling are separate.

What fits your needs

Mistral Small 4 release v26.03 weights and Mistral-hosted API model mistral-small-2603; local and hosted handling are separate.

Reasoning and instruction

One checkpoint combines instruct, reasoning and coding modes; reasoning effort can be selected per request.

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Vision and tools

Accepts image and text input, supports function calling and structured outputs.

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Multilingual input

Model card lists 24 languages, including English, Portuguese, Chinese, Arabic and Japanese.

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Tradeoffs to expect

Local hardware

Mistral recommends at least an H100 80GB at FP8 for this 119B checkpoint; lower precision or shorter contexts change the setup.

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Hosted API route

API model `mistral-small-2603` and the downloadable checkpoint are distinct delivery routes with different prompt handling.

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How to switch

Use locally

Download the Apache 2.0 weights, run a supported server such as vLLM, then point Vibe or another client to its OpenAI-compatible endpoint.

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Practical questions

Local data path

A local server can keep prompts within your infrastructure when configured without remote tools; Mistral documents telemetry and update-check disable settings for fully offline Vibe.

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Tool permissions

The model provides function calling, but approval and execution boundaries are controlled by the harness or application.

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API retention

Mistral’s consumer privacy policy is not a universal policy for every business/API route; review the account and contract path selected.

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Energy practices

3/10↑

This grades disclosed operating practices, not the electricity or emissions of a particular generation.

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The release gives limited runtime or control details but no comparable per-task footprint or electricity-source evidence. Mistral documents a local inference boundary and recommends hardware for a 119B checkpoint. Mistral’s offline guide says to reduce context length or use 4-bit precision for lower-memory configurations; these are documented runtime controls, not measured energy savings.

1 + 1 reporting + 0 electricity + 1 controls = 3/10. This grades documented practices and transparency.

Per-task energy, serving region, facility electricity mix, water and independent footprint review are not established in the cited release sources.

Reporting1/3
Mistral documents a local inference boundary and recommends hardware for a 119B checkpoint.
Electricity sourcing0/3
The release materials do not report matched regional electricity sourcing or carbon-free supply for training or inference.
Resource controls1/3
Mistral’s offline guide says to reduce context length or use 4-bit precision for lower-memory configurations; these are documented runtime controls, not measured energy savings.

Water disclosure

Water reporting has not been assessed for this choice.

Training data

1/10↑

The model release does not provide a complete inspectable training-source permission record.

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The model card describes architecture, modalities and license but does not identify training data sources or permissions. It provides no source-level permission ledger or creator remedy; a model-weight license governs downstream use, not the material used to train the model.

1 base + 0 source transparency + 0 documented permission + 0 creator controls = 1/10.

Named source inventory, source-level licenses, creator remedies, and independent verification remain unestablished for this release.

Source transparency0/3
The model card describes architecture, modalities and license but does not identify training data sources or permissions.
Documented permission0/4
The release sources do not publish a training-source permission basis or rights ledger; the weight license doesn’t settle training-data permission.
Creator controls0/2
No training-source creator permission-before-use, opt-out, removal or retraining route is documented for this release.
Data-rights rubric ↗

Your data & privacy

—Not enough evidence↑

Privacy has no single score for these downloadable weights because handling depends on the inference host and integrations.

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The release can be run locally, but it also appears in hosted provider routes; those operators set their own request retention, training and region terms. A cloud API, where offered, is a separate policy route and is not inherited from the local weights.

A selected host, network path, telemetry, logging, external prompt enhancement, and data retention need route-specific review.

Openness

7/10↑

Apache 2.0 weights and inference instructions are public, but no release-specific full training recipe or training data is published.

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The model card provides downloadable weights, an Apache 2.0 license and executable Transformers/vLLM instructions. It describes the architecture, but not a complete training recipe or dataset inventory. This rating concerns release artifacts and reproducibility, not training-data permission.

7/10 reflects permissive weights and reproducible inference, with training data and full training recipe unavailable.

Training data provenance and the full pretraining/post-training recipe are not disclosed for this release.

Worker protections

2/10↑

Mistral publicly says its supplier code applies to goods and services and its Trust Center shows contractors acknowledge a code, but labor-specific provisions and outcomes were not publicly inspectable.

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Mistral’s August 2026 help page states that its Code of Conduct sets standards suppliers are expected to follow for Mistral business and all supplier goods/services; the Trust Center lists contractor acknowledgment of the Code of Conduct. The public interface did not expose the code’s labor clauses or worker procedures, and no worker survey, audit, pay/conditions disclosure or remediation results were located. This supports limited credit for a supplier-code commitment only. These findings concern the developer or operator. This product’s use in a particular deployment needs separate evidence.

1 + 1 pay & conditions + 0 worker voice & remedy + 0 evidence & follow-through = 2/10. This grades documented worker safeguards, not a measured rate of mistreatment.

The supplier code’s detailed labor language and coverage of AI data workers, grievance route, monitoring and outcomes were not accessible from the public Trust Center.

Pay & conditions1/3
A supplier code is a stated business requirement, but its labor content and implementation were not publicly inspectable in this review.
Worker voice & remedy0/3
No public worker-specific voice or grievance mechanism was established in the accessible sources.
Evidence & follow-through0/3
The Trust Center shows contractor code acknowledgment but no labor-specific audits, remediation or outcomes.
Workers rubric ↗

Military ties

3/10Broad defense ties↑

Mistral AI publicly partners with defense AI company Helsing on joint development of vision-language-action models, and its current company page says it serves defense customers. A separate Airbus agreement includes military aerospace applications; specific Mistral model deployments in weapons systems are not established.

See the evidence

Mistral's announcement with Helsing describes joint development of next-generation AI systems for European defense, while Helsing's announcement links its military AI portfolio to Ukraine-deployed strike drones and fighter electronic-warfare capabilities. Mistral also identifies defense as a customer sector and Airbus says the partnership includes military aerospace applications. This is broad defense enablement, capped at 3/10; no binding weapons/surveillance prohibitions or military-use oversight outcomes are public in these sources. These findings concern the developer or operator. This product’s use in a particular deployment needs separate evidence.

1 + 0 use restrictions + 0 enforcement & oversight + 2 relationship disclosure = 3/10. Known defense ties lower this rating; safeguards can improve it within the relationship’s cap.

The sources don’t confirm which Mistral models, if any, are deployed in specific military systems, the operational purpose or safeguards, contract restrictions, or independent oversight. Helsing's existing strike systems are not evidence that Mistral models themselves control or target weapons.

Use restrictions0/4
The reviewed public partnership and company materials do not disclose binding restrictions on weapons, harmful surveillance, or military-intelligence use.
Enforcement & oversight0/3
No public military-specific review, enforcement mechanism, or independent outcome assessment was identified in the reviewed partnership materials.
Relationship disclosure2/2
Mistral and its partners identify the defense relationships and intended applications, including VLA model development and military aerospace, though no model-level deployment details or outcomes are disclosed.

Mistral publicly confirms joint defense-AI development and military-aerospace partnerships, but no source establishes its model in actual targeting or combat intelligence use. The relationship limits this grade to 3/10.

Military rubric ↗

BDS targets

Not listed↑

We did not find Mistral AI among the named targets in the two official BNC campaign lists. This is a limited list check, not BDS approval.

See the evidence

Mistral AI is not a named target in the checked lists, but BDS uses selective campaigns, so absence cannot establish a clean record. Running downloaded weights locally is a different decision from paying the developer or a cloud host; check the host as well. These findings concern the developer or operator. This product’s use in a particular deployment needs separate evidence.

This review covers the named targets in the BNC consumer/pressure guide and No Tech campaign, not every BDS campaign, local group, investment or supplier. Lists and ownership can change. A company’s absence from these lists is not an endorsement or proof that it has no relevant relationships.

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