On 2 July 2026, Mistral AI announced Leanstral 1.5 119B-A6B. Mistral targeted Lean 4 theorem proving and proof repair with a specialist open model rather than a general coding endpoint.
This release brief was checked against first-party material on 10 August 2026. The date above is the public announcement date, not the date a repository was created or a third-party provider added the model. Where access or weights arrived later, that distinction is recorded below.
Release record
| Field | Verified detail |
|---|---|
| Announcement | 2 July 2026 |
| Availability or weight release | 2 July 2026 as Apache 2.0 weights |
| Release type | open-weight formal-proof and verified-code agent |
| Access | Apache 2.0 checkpoint on Hugging Face with Lean 4 tooling guidance |
| Architecture | a 119B-total sparse model activating about 6.5B parameters per token |
| Maximum stated context | 256K tokens, with 200K or less recommended in the card |
What changed
Leanstral 1.5 moves model evaluation into a domain with executable correctness. A generated proof either checks in Lean or it does not, which makes the release useful for measuring search, repair and specification quality without relying only on an LLM judge. The sparse active footprint is also small relative to its total capacity, although formal proof agents can still consume substantial search time and context.
The practical comparison is therefore not simply whether Leanstral 1.5 119B-A6B has the largest headline score. Teams need to ask whether its architecture, access terms, latency, tool behaviour and evaluation setup match the workload they actually intend to run. A model can lead one harness while losing on cost, refusal behaviour, multilingual quality or repeatability in another.
Benchmarks worth retaining
| Evaluation | Reported result | How to read it |
|---|---|---|
| PutnamBench | 587 solved items in the release chart | Formal-proof suite under Mistral’s agent setup |
| FATE-H | 87 solved items | Hard formalisation benchmark count |
| FATE-X | 34 solved items | Release chart result, narrowly above Seed-Prover 1.5 high |
These are release-time results, not independently reproduced guarantees. Mistral’s comparison chart reports solved-task counts across proof suites, and differences in theorem libraries, time budgets and proof search can change results materially. Scores should remain attached to the disclosed effort setting, agent harness, tool access, timeout, context-management policy and judge model. Moving a number into a procurement sheet without those conditions creates false comparability.
Architecture and access
Leanstral 1.5 119B-A6B is described as a 119B-total sparse model activating about 6.5B parameters per token with 256K tokens, with 200K or less recommended in the card of stated context. Its access position at verification time is Apache 2.0 checkpoint on Hugging Face with Lean 4 tooling guidance. That wording matters: open weights, source-available weights, an API, a product preview and a research demonstration give adopters very different rights and different levels of reproducibility.
Before deployment, record the exact model identifier or checkpoint, inference stack, quantisation, reasoning setting, region, price schedule and supplier terms. If the release uses a custom licence, read the licence itself rather than relying on the word “open” in launch copy. If it is API-only, preserve the dated documentation and change-notice route because the served snapshot can change without a downloadable artefact.
What an evaluation should test next
For Leanstral 1.5 119B-A6B, a credible internal gate should include:
- a frozen set of representative tasks with pass, fail and abstain criteria;
- a matched baseline using the same tools, timeout, prompt budget and reviewer rubric;
- repeated runs to expose variance rather than reporting a single best attempt;
- latency, token use and total task cost alongside task success;
- adversarial, multilingual and long-context cases relevant to the real deployment; and
- rollback evidence showing the previous model can be restored safely.
The wider model change-control guide explains how to keep model, prompt, tool and corpus changes reconstructable. The AI dependency inventory guide covers the release and supplier records needed after deployment.
AIEngine verdict
Leanstral 1.5 is a major specialist open model for verified mathematics and software. It should be judged on proof checking, search cost and maintainability, not prose fluency.
This is a launch assessment, not a certification. Benchmark leadership is useful evidence of where to test; it is not authorization to place the model in a high-impact workflow without domain evaluation, security review and an accountable owner.
Primary sources
Image provenance
Hero image: Mistral AI official release artwork. The locally served WebP is a crop of the first-party release or model-card asset recorded in the repository provenance manifest.
