Model comparison
DeepSeek-Coder-V2 vs Gemini 1.0 Pro
- Input
- Free (open weights)
- Output
- Free (open weights)
- Context
- 128K
- Released
- 2024-06-17
- Input
- $0.50
- Output
- $1.50
- Context
- 32K tokens (~32,760 input)
- Released
- 2023-12-13
DeepSeek-Coder-V2 scores higher on 4 of the 4 benchmarks both models report; DeepSeek-Coder-V2 has the larger context window (128K vs 32K); DeepSeek-Coder-V2 ships open weights while Gemini 1.0 Pro is API-only.
Specs and pricing side by side
| Spec | DeepSeek-Coder-V2 | Gemini 1.0 Pro |
|---|---|---|
| Maker | DeepSeek | |
| Released | 2024-06-17 | 2023-12-13 |
| Context window | 128K | 32K tokens (~32,760 input) |
| Max output | Undisclosed | 8,192 tokens |
| Input price | Free (open weights) | $0.50 |
| Output price | Free (open weights) | $1.50 |
| Parameters | 236B total · 21B active (Lite: 16B total · 2.4B active) | Undisclosed |
| License | MIT (code) + DeepSeek Model License — commercial use permitted | Proprietary |
| Weights | Open weights | API only |
| Modalities | Text | Text, Vision (image input, via Gemini 1.0 Pro Vision) |
| Knowledge cutoff | November 2023 | Early 2023 (around April 2023) |
Benchmarks both models report
| Benchmark | DeepSeek-Coder-V2 | Gemini 1.0 Pro |
|---|---|---|
| HumanEval | 90.2% | 67.7% |
| MATH | 75.7% | 32.6% |
| GSM8K | 94.9% | 86.5% |
| MMLU | 79.2% | 71.8% |
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 DeepSeek-Coder-V2 if…
- You care about HumanEval, MATH, GSM8K (it scores higher on 4 shared benchmarks).
- You need the longer context (128K vs 32K).
- You want to self-host or fine-tune (open weights, MIT (code) + DeepSeek Model License — commercial use permitted).
- Your use case is: code generation and autocompletion across many languages.
Pick Gemini 1.0 Pro if…
- You need Vision (image input, via Gemini 1.0 Pro Vision) input, which DeepSeek-Coder-V2 lacks.
- Your use case is: multi-turn text and code chat assistants.
FAQ
Which is better, DeepSeek-Coder-V2 or Gemini 1.0 Pro?
DeepSeek-Coder-V2 scores higher on 4 of the 4 benchmarks both models report; DeepSeek-Coder-V2 has the larger context window (128K vs 32K); DeepSeek-Coder-V2 ships open weights while Gemini 1.0 Pro is API-only. 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 DeepSeek-Coder-V2 and Gemini 1.0 Pro?
DeepSeek-Coder-V2 offers 128K with up to Undisclosed output; Gemini 1.0 Pro offers 32K tokens (~32,760 input) with up to 8,192 tokens output.
Is DeepSeek-Coder-V2 newer than Gemini 1.0 Pro?
DeepSeek-Coder-V2 was released 2024-06-17; Gemini 1.0 Pro was released 2023-12-13.
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