Model comparison
DeepSeek-V3.1-Terminus vs Gemini 2.5 Flash-Lite
- Input
- $0.27 / 1M tokens
- Output
- $0.95 / 1M tokens
- Context
- 128K
- Released
- 2025-09-22
- Input
- $0.10 / 1M tokens (text / image / video)
- Output
- $0.40 / 1M tokens
- Context
- 1M
- Released
- 2025-06-17
DeepSeek-V3.1-Terminus scores higher on 5 of the 5 benchmarks both models report; Gemini 2.5 Flash-Lite is cheaper on input tokens ($0.1 vs $0.3 per 1M, 2.7×); Gemini 2.5 Flash-Lite has the larger context window (1M vs 128K); DeepSeek-V3.1-Terminus ships open weights while Gemini 2.5 Flash-Lite is API-only.
Specs and pricing side by side
| Spec | DeepSeek-V3.1-Terminus | Gemini 2.5 Flash-Lite |
|---|---|---|
| Maker | DeepSeek | |
| Released | 2025-09-22 | 2025-06-17 |
| Context window | 128K | 1M |
| Max output | 32K | 64K |
| Input price | $0.27 / 1M tokens | $0.10 / 1M tokens (text / image / video) |
| Output price | $0.95 / 1M tokens | $0.40 / 1M tokens |
| Parameters | 685B total, 37B active (MoE) | Undisclosed |
| License | MIT | Proprietary (Google), API-only |
| Weights | Open weights | API only |
| Modalities | Text | Text, Vision, Audio, Video, PDF |
| Knowledge cutoff | not published | January 2025 |
Benchmarks both models report
| Benchmark | DeepSeek-V3.1-Terminus | Gemini 2.5 Flash-Lite |
|---|---|---|
| GPQA-Diamond | 80.7% | 64.6% |
| Humanity's Last Exam | 21.7% | 5.1% |
| Aider-Polyglot | 76.1% | 26.7% |
| SWE-bench Verified | 68.4% | 31.6% |
| SimpleQA | 96.8% | 10.7% |
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 DeepSeek-V3.1-Terminus if…
- You care about GPQA-Diamond, Humanity's Last Exam, Aider-Polyglot (it scores higher on 5 shared benchmarks).
- You want to self-host or fine-tune (open weights, MIT).
- Your use case is: agentic coding assistants and autonomous software-engineering loops (SWE-bench-style tasks).
Pick Gemini 2.5 Flash-Lite if…
- Cost matters: input tokens cost 2.7× less ($0.1 vs $0.3 per 1M).
- You need the longer context (1M vs 128K).
- You need Vision / Audio / Video / PDF input, which DeepSeek-V3.1-Terminus lacks.
- Your use case is: high-volume classification and intelligent request routing.
FAQ
Which is better, DeepSeek-V3.1-Terminus or Gemini 2.5 Flash-Lite?
DeepSeek-V3.1-Terminus scores higher on 5 of the 5 benchmarks both models report; Gemini 2.5 Flash-Lite is cheaper on input tokens ($0.1 vs $0.3 per 1M, 2.7×); Gemini 2.5 Flash-Lite has the larger context window (1M vs 128K); DeepSeek-V3.1-Terminus ships open weights while Gemini 2.5 Flash-Lite is API-only. The better pick depends on whether you value benchmark scores, price per token, context length or openness for your workload.
How much cheaper is Gemini 2.5 Flash-Lite?
DeepSeek-V3.1-Terminus: $0.27 / 1M tokens input, $0.95 / 1M tokens output. Gemini 2.5 Flash-Lite: $0.10 / 1M tokens (text / image / video) input, $0.40 / 1M tokens output (list API prices as published by each maker).
What are the context windows of DeepSeek-V3.1-Terminus and Gemini 2.5 Flash-Lite?
DeepSeek-V3.1-Terminus offers 128K with up to 32K output; Gemini 2.5 Flash-Lite offers 1M with up to 64K output.
Is DeepSeek-V3.1-Terminus newer than Gemini 2.5 Flash-Lite?
DeepSeek-V3.1-Terminus was released 2025-09-22; Gemini 2.5 Flash-Lite was released 2025-06-17.
Go deeper
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