Curiosity · AI Model
DeepSeek-Math 7B
DeepSeek-Math 7B is a math-specialised open-weight LLM from DeepSeek AI, continue-pretrained on roughly 120 billion math-heavy tokens scraped from Common Crawl. Despite only 7B parameters, it rivals or exceeds much larger models on MATH and GSM8K, and was an early demonstration that data quality can punch above model scale for maths reasoning.
Model specs
- Vendor
- DeepSeek
- Family
- DeepSeek-Math
- Released
- 2024-02
- Context window
- 4,096 tokens
- Modalities
- text
Strengths
- Best-in-class MATH scores for a 7B model at release
- Small enough for single-GPU inference
- MIT-licensed weights make it easy to fine-tune
Limitations
- Small context window (4k) limits multi-step chain-of-thought
- Not tuned for conversational chat — needs instruction wrapping
- Outclassed by 2026 reasoning models (o1-style) on hardest benchmarks
Use cases
- Math tutoring at the school / undergraduate level
- Benchmarking research on math-specific pretraining
- STEM assistants where a small, cheap, accurate math model suffices
- Fine-tuning base for domain-specific math RL
Benchmarks
| Benchmark | Score | As of |
|---|---|---|
| MATH | ~51% | 2026-04 |
| GSM8K | ~88% | 2026-04 |
| OCW | ~30% | 2026-04 |
Frequently asked questions
What is DeepSeek-Math 7B?
DeepSeek-Math 7B is DeepSeek's open-weight small language model specialised for mathematics. It was pretrained on a curated 120B-token math corpus and matches much larger general-purpose models on GSM8K and MATH.
Is DeepSeek-Math 7B still competitive in 2026?
For its size it remains strong, but 2025-2026 reasoning-tuned models (DeepSeek-R1, OpenAI o1) now lead hardest math benchmarks. DeepSeek-Math 7B is best seen as an efficient, cheap math workhorse.
Sources
- DeepSeek-Math on HuggingFace — accessed 2026-04-20
- DeepSeek-Math paper (arXiv) — accessed 2026-04-20