Model comparison
Gemma 2 vs DeepSeek-Coder-V2
- Input
- Free to download and self-host
- Output
- Free to download and self-host
- Context
- 8,192 tokens
- Released
- 2024-06-27
- Input
- Free (open weights)
- Output
- Free (open weights)
- Context
- 128K
- Released
- 2024-06-17
DeepSeek-Coder-V2 scores higher on 4 of the 4 benchmarks both models report; DeepSeek-Coder-V2 has the larger context window (128K vs 8K).
Specs and pricing side by side
| Spec | Gemma 2 | DeepSeek-Coder-V2 |
|---|---|---|
| Maker | DeepSeek | |
| Released | 2024-06-27 | 2024-06-17 |
| Context window | 8,192 tokens | 128K |
| Max output | Not separately specified; output shares the… | Undisclosed |
| Input price | Free to download and self-host | Free (open weights) |
| Output price | Free to download and self-host | Free (open weights) |
| Parameters | Three sizes: 2B (2.6B), 9B, and 27B parameters | 236B total · 21B active (Lite: 16B total · 2.4B active) |
| License | Gemma (Gemma Terms of Use) — a custom, commercially permissive license that allows redistribution, fine-tuning, commercial use, and derivative works subject to a prohibited-use policy. Not OSI-approved (not Apache 2.0). | MIT (code) + DeepSeek Model License — commercial use permitted |
| Weights | Open weights | Open weightssame |
| Modalities | text | Text |
| Knowledge cutoff | Not officially published by Google for Gemma 2 | November 2023 |
Benchmarks both models report
| Benchmark | Gemma 2 | DeepSeek-Coder-V2 |
|---|---|---|
| MMLU | 75.2% | 79.2% |
| GSM8K | 74% | 94.9% |
| HumanEval | 51.8% | 90.2% |
| MATH | 42.3% | 75.7% |
Scores are as published by each maker or its cited source; harness, reasoning effort and date can differ between rows, so treat small gaps as ties. Sources are listed on each model page.
Which one should you pick?
Pick Gemma 2 if…
- You need text input, which DeepSeek-Coder-V2 lacks.
- Your use case is: on-device and self-hosted text generation, summarization, and extraction where data must stay local.
Pick DeepSeek-Coder-V2 if…
- You care about MMLU, GSM8K, HumanEval (it scores higher on 4 shared benchmarks).
- You need the longer context (128K vs 8K).
- You need Text input, which Gemma 2 lacks.
- Your use case is: code generation and autocompletion across many languages.
FAQ
Which is better, Gemma 2 or DeepSeek-Coder-V2?
DeepSeek-Coder-V2 scores higher on 4 of the 4 benchmarks both models report; DeepSeek-Coder-V2 has the larger context window (128K vs 8K). The better pick depends on whether you value benchmark scores, price per token, context length or openness for your workload.
What are the context windows of Gemma 2 and DeepSeek-Coder-V2?
Gemma 2 offers 8,192 tokens with up to Not separately specified; output shares the 8,192-token context window output; DeepSeek-Coder-V2 offers 128K with up to Undisclosed output.
Is Gemma 2 newer than DeepSeek-Coder-V2?
Gemma 2 was released 2024-06-27; DeepSeek-Coder-V2 was released 2024-06-17.