Two open-source powerhouses compared
DeepSeek R1 wins on pure reasoning, Llama wins on ecosystem and general balance. Both are excellent.
Choose DeepSeek for math, complex reasoning, or when you need MIT licensing.
Choose Llama for general use, better documentation, and wider tool support.
DeepSeek has emerged as a serious Llama competitor, especially with its R1 reasoning model. Here's how they compare.
| Specification | DeepSeek V3 | Llama 3.1 70B |
|---|---|---|
| Developer | DeepSeek | Meta |
| Parameters | 671B (MoE, 37B active) | 70B |
| Context Length | 128K | 128K |
| VRAM (Minimum) | 24GB (distilled 7B) | 40GB (Q4) |
| VRAM (Recommended) | Full model: multi-GPU | 48GB+ |
| Release Date | December 2024 | July 2024 |
| License | MIT | Llama 3.1 Community License |
| Category | DeepSeek V3 | Llama 3.1 70B | Winner |
|---|---|---|---|
| AIME (Math) | 79.8% | 54.0% | DeepSeek V3 |
| MMLU (Knowledge) | 88.5% | 82.0% | DeepSeek V3 |
| Coding | 85.0% | 80.5% | DeepSeek V3 |
| Community/Tooling | Growing | Excellent | Llama 3.1 70B |
| License | MIT (fully open) | Community License | DeepSeek V3 |
Check our GPU buying guides to find the right hardware for running LLMs locally.