Leanstral 1.5: Proof Abundance for All

Since its launch, Leanstral has offered an open, practical approach to proof engineering in Lean 4 . Today, we are releasing Leanstral 1.5 , a free Apache-2.0 licensed model with 119B total and only 6B active parameters, delivering a performance upgrade that makes formal verification more powerful and accessible than ever.

Leanstral 1.5 saturates miniF2F, solves 587/672 PutnamBench problems, and achieves a new state-of-the-art of %87 on FATE-H and 34% on FATE-X . Beyond benchmarks, it verifies complex code properties and uncovers previously unknown bugs in open-source repositories —proving that rigorous formal methods can be both effective and practical for real-world use.

Leanstral 1.5 goes through a three-stage process: mid-training, supervised fine-tuning, and reinforcement learning with CISPO. Leanstral 1.5 leverages extensive training on two RL environments:

Leanstral 1.5 has a Apache-2.0 license. The weights can be found on Huggingface , while also being available now as a free API endpoint as leanstral-1-5 . We recommend using it in Mistral Vibe. To begin your journey, grab an API Key, and:

In the code agent environment , Leanstral operates like a developer in a raw filesystem: it edits files, runs bash commands, and uses the Lean language server to inspect goals, errors, and type information in real time. This allows it to tackle long-horizon tasks like completing partial proofs in a repository, building auxiliary lemmas, and persisting through multiple rounds of context compaction. The model learns to navigate the full proof-engineering workflow and is finally verified by our fork of SafeVerify for correctness given a list of target theorems.

FLTEval is based on real pull requests from the Fermat’s Last Theorem repository, testing practical proof engineering with real-world complexity.

One such bug was in the sign function for zigzag decoding of the datrs/varinteger library. On input Std.U64.MAX, the expression (value + 1) overflowed, causing crashes in debug mode and silent corruption in release mode—an edge case that testing and fuzzing would typically miss. Leanstral’s pipeline caught it automatically, demonstrating that formal verification can already be applied to real-world codebases and find bugs that some traditional methods overlook.

In the multiturn environment , the model is given a theorem statement and must either prove or disprove it. The model submits a proof, receives Lean compiler feedback, and refines its approach with each attempt. If the proof compiles it succeeds; otherwise the loop continues until the model either solves the problem or exhausts its budget.

miniF2F is a cross-system benchmark for formal mathematics, ranging from elementary problems to IMO-level challenges, testing diverse proof abilities across algebra, combinatorics, and number theory.

PutnamBench consists of 672 problems from the Putnam Mathematical Competition, requiring deep reasoning and long proof chains to solve challenging mathematical problems.