Curiosity · AI Model
Google MathGemma
MathGemma is a math-specialised variant of the Gemma open-weights family from Google DeepMind, continuing the RecurrentGemma / CodeGemma / PaliGemma 'specialist Gemma' strategy. Released alongside Gemma 2/3, it is fine-tuned on curated mathematics corpora, MathPile-style datasets, and synthetic Lean / Isabelle proofs, producing stronger step-by-step reasoning on GSM8K, MATH, and olympiad-style benchmarks than the base Gemma models at matching size. Targeted at academic and educational deployments rather than frontier reasoning research.
Model specs
- Vendor
- Google DeepMind
- Family
- Gemma (specialist)
- Released
- 2025-03
- Context window
- 8,192 tokens
- Modalities
- text, code
Strengths
- Much stronger math performance than base Gemma at matched size
- Step-by-step reasoning tuned for classroom explanations
- Open weights under Gemma licence
- Pairs well with Lean / Isabelle toolchains
Limitations
- Weaker on non-math tasks than base Gemma
- Smaller than frontier math models like Minerva and DeepSeek-Math
- No image/diagram input
- Licence has Gemma-style usage conditions
Use cases
- Open-weights math tutoring apps
- Step-by-step solutions for homework platforms
- Proof-sketch generation feeding into Lean / Isabelle
- Education-focused fine-tuning targets
Benchmarks
| Benchmark | Score | As of |
|---|---|---|
| GSM8K (math word problems) | ≈80% (small variant) | 2025-03 |
| MATH | ≈45% | 2025-03 |
Frequently asked questions
What is MathGemma?
MathGemma is a math-specialised Gemma family fine-tune from Google DeepMind, optimised for step-by-step math reasoning and proof-sketch generation.
How does MathGemma compare to AlphaProof?
AlphaProof is a frontier RL-trained Lean prover; MathGemma is a smaller open fine-tune intended for reasoning and education, not competition-level formal proofs.
Can I fine-tune MathGemma further?
Yes — weights are open under the Gemma licence, and LoRA / full fine-tuning recipes work like any other Gemma checkpoint.
Sources
- Google AI — Gemma family — accessed 2026-04-20
- MathPile dataset (reference training corpus) — accessed 2026-04-20