Gemini 2.5 Flash vs Gemini 2.0 Flash vs DeepSeek-V3.1
Gemini 2.5 Flash comes out ahead, 72 to 65 and 54 on our weighted score, though DeepSeek-V3.1 is 29% cheaper per token.
- Our pick
GoogleGemini 2.5 Flash
72/100- ECI140.8
- Price$0.30 / $2.50
- Context1.05M
- Google
Gemini 2.0 Flash
65/100- ECI134.7
- Price—
- Context1.05M
DeepSeekDeepSeek-V3.1
54/100- ECI139.9
- Price$0.385 / $1.25
- Context131K
Gemini 2.5 Flash is our pick
Gemini 2.5 Flash is the better all-round choice, scoring 72/100 against Gemini 2.0 Flash (65) and DeepSeek-V3.1 (54). It leads on inputs & features. The score weighs capability 67%, inputs & features 20%, context window 13%.
- CapabilityGemini 2.5 FlashCapabilities Index (ECI): Gemini 2.5 Flash 140.8 · DeepSeek-V3.1 139.9 · Gemini 2.0 Flash 134.7
- Lowest priceDeepSeek-V3.1DeepSeek-V3.1 $0.601 · Gemini 2.5 Flash $0.85 per 1M tokens (3:1 blend) · Gemini 2.0 Flash unpriced
- Longest contextGemini 2.5 Flash and Gemini 2.0 FlashGemini 2.5 Flash 1,048,576 · Gemini 2.0 Flash 1,048,576 · DeepSeek-V3.1 131,072 tokens
- Widest inputsGemini 2.5 Flash and Gemini 2.0 FlashGemini 2.5 Flash: Text, Images, PDFs, Audio, Video · Gemini 2.0 Flash: Text, Images, PDFs, Audio, Video · DeepSeek-V3.1: Text
- Self-hostingDeepSeek-V3.1Publishes downloadable weights (MIT License)
| Measure | Weight | Gemini 2.5 Flash | Gemini 2.0 Flash | DeepSeek-V3.1 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 67% | 67 | 59 | 65 |
| Inputs & features | 20% | 100 | 90 | 35 |
| Context window | 13% | 61 | 61 | 24 |
| Overall | 100% | 72/100 | 65/100 | 54/100 |
Left out because at least one model lacks the data: price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Gemini 2.5 FlashGoogle | Gemini 2.0 FlashGoogle | DeepSeek-V3.1DeepSeek |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 140.8 (best) | 134.7 | 139.9 |
| ECI rank | #97 of 148 (best) | #116 of 148 | #100 of 148 |
| Price per million tokens | |||
| Input | $0.30 (best) | — | $0.385 |
| Output | $2.50 | — | $1.25 (best) |
| Cached input | $0.03 | — | — |
| Blended (3:1) | $0.85 | — | $0.601 (best) |
| Long-context rate | Same rate | — | Same rate |
| Price source | Official Google API | — | Median of 8 providers |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 1,048,576 tokens (best) | 131,072 tokens |
| Max output | 65,536 tokens (best) | 8,192 tokens | 8,192 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | No |
| PDFs | Yes | Yes | No |
| Audio | Yes | Yes | No |
| Video | Yes | Yes | No |
| Reasoning | Yes | No | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Proprietary | Proprietary | OpenMIT License |
| API model ID | gemini-2.5-flash | — | — |
| API providers | 22 (best) | — | 8 |
| Released | Jun 17, 2025 | Dec 11, 2024 | Aug 21, 2025 |
| Knowledge cutoff | Jan 2025 | Jun 2024 | — |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Gemini 2.5 Flash$8.00
- Gemini 2.0 Flash—
- DeepSeek-V3.1$6.35
Which should you choose?
Which is better: Gemini 2.5 Flash, Gemini 2.0 Flash or DeepSeek-V3.1?
Gemini 2.5 Flash is the better all-round choice, scoring 72/100 against Gemini 2.0 Flash (65) and DeepSeek-V3.1 (54). It leads on inputs & features. The score weighs capability 67%, inputs & features 20%, context window 13%.
Which is cheaper, Gemini 2.5 Flash, Gemini 2.0 Flash or DeepSeek-V3.1?
DeepSeek-V3.1 is cheaper at $0.385 input / $1.25 output per million tokens (median across 8 API providers). Gemini 2.5 Flash costs $0.30 input / $2.50 output per million tokens (official Google API price). At a typical mix of three input tokens to one output token, that is $0.601 per million tokens for DeepSeek-V3.1 versus $0.85 for Gemini 2.5 Flash (1.4× as much). Gemini 2.0 Flash has no published per-token price.
Which scores higher on benchmarks?
Gemini 2.5 Flash scores higher on the Capabilities Index (ECI): Gemini 2.5 Flash 140.8 (#97 of 148), DeepSeek-V3.1 139.9 (#100 of 148) and Gemini 2.0 Flash 134.7 (#116 of 148). The confidence ranges of the top two overlap (138.5–142.3 vs 136.1–143.3), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for Gemini 2.5 Flash, Gemini 2.0 Flash and DeepSeek-V3.1 yet, so there is no like-for-like coding score. On overall capability, Gemini 2.5 Flash leads, which tends to carry over to coding, but test on your own codebase. All three support tool calling for agent workflows.
Which has the bigger context window?
Gemini 2.5 Flash and Gemini 2.0 Flash have the largest context windows (1,048,576 and 1,048,576 tokens), against 131,072 for DeepSeek-V3.1. Maximum output per response: Gemini 2.5 Flash up to 65,536, Gemini 2.0 Flash up to 8,192, DeepSeek-V3.1 up to 8,192 tokens.
Which can read images, PDFs, audio or video?
Gemini 2.5 Flash accepts text, images, PDFs, audio and video; Gemini 2.0 Flash accepts text, images, PDFs, audio and video; DeepSeek-V3.1 accepts text. Gemini 2.5 Flash handles the widest range of inputs.
Are any of these open source?
DeepSeek-V3.1 publishes its weights (MIT License) and can be self-hosted; Gemini 2.5 Flash and Gemini 2.0 Flash is proprietary.
Which is newer?
DeepSeek-V3.1 is the newest, released Aug 21, 2025. Gemini 2.5 Flash came out Jun 17, 2025; Gemini 2.0 Flash came out Dec 11, 2024. Knowledge cutoff: Gemini 2.5 Flash Jan 2025, Gemini 2.0 Flash Jun 2024.
How do you decide the winner?
Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.
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