DeepSeek-V3.1 vs Gemini 2.5 Flash vs GPT-4.1 mini
Gemini 2.5 Flash comes out ahead, 68 to 60 and 55 on our weighted score, though DeepSeek-V3.1 is 29% cheaper per token.
DeepSeek
DeepSeek-V3.1
55/100- ECI139.9
- Price$0.385 / $1.25
- Context131K
- Our pick
Google
Gemini 2.5 Flash
68/100- ECI140.8
- Price$0.30 / $2.50
- Context1.05M
OpenAI
GPT-4.1 mini
60/100- ECI135.0
- Price$0.40 / $1.60
- Context1.05M
Gemini 2.5 Flash is our pick
Gemini 2.5 Flash is the better all-round choice, scoring 68/100 against GPT-4.1 mini (60) and DeepSeek-V3.1 (55). It leads on inputs & features. DeepSeek-V3.1 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGemini 2.5 FlashCapabilities Index (ECI): Gemini 2.5 Flash 140.8 · DeepSeek-V3.1 139.9 · GPT-4.1 mini 135.0
- Lowest priceDeepSeek-V3.1DeepSeek-V3.1 $0.601 · GPT-4.1 mini $0.70 · Gemini 2.5 Flash $0.85 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 Flash and GPT-4.1 miniGemini 2.5 Flash 1,048,576 · GPT-4.1 mini 1,047,576 · DeepSeek-V3.1 131,072 tokens
- Widest inputsGemini 2.5 FlashDeepSeek-V3.1: Text · Gemini 2.5 Flash: Text, Images, PDFs, Audio, Video · GPT-4.1 mini: Text, Images, PDFs
- Self-hostingDeepSeek-V3.1Publishes downloadable weights (MIT License)
| Measure | Weight | DeepSeek-V3.1 | Gemini 2.5 Flash | GPT-4.1 mini |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 65 | 67 | 59 |
| Price | 25% | 60 | 53 | 57 |
| Inputs & features | 15% | 35 | 100 | 70 |
| Context window | 10% | 24 | 61 | 61 |
| Overall | 100% | 55/100 | 68/100 | 60/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 139.9 | 140.8 (best) | 135.0 |
| ECI rank | #100 of 148 | #97 of 148 (best) | #115 of 148 |
| GPQA DiamondGraduate-level science questions | — | — | 65.9% |
| FrontierMath Tiers 1–3Research-level mathematics | — | — | 6.7% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | — | 44.7% |
| SimpleQA VerifiedShort factual questions | — | — | 12.7% |
| Price per million tokens | |||
| Input | $0.385 | $0.30 (best) | $0.40 |
| Output | $1.25 (best) | $2.50 | $1.60 |
| Cached input | — | $0.03 (best) | $0.10 |
| Blended (3:1) | $0.601 (best) | $0.85 | $0.70 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 8 providers | Official Google API | Official OpenAI API |
| Limits | |||
| Context window | 131,072 tokens | 1,048,576 tokens (best) | 1,047,576 tokens |
| Max output | 8,192 tokens | 65,536 tokens (best) | 32,768 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | Yes | Yes |
| PDFs | No | Yes | Yes |
| Audio | No | Yes | No |
| Video | No | Yes | No |
| Reasoning | Yes | Yes | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | OpenMIT License | Proprietary | Proprietary |
| API model ID | — | gemini-2.5-flash | gpt-4.1-mini |
| API providers | 8 | 22 | 24 (best) |
| Released | Aug 21, 2025 | Jun 17, 2025 | Apr 14, 2025 |
| Knowledge cutoff | — | Jan 2025 | Apr 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
DeepSeek-V3.1$6.35
Gemini 2.5 Flash$8.00
GPT-4.1 mini$7.20
Which should you choose?
Which is better: DeepSeek-V3.1, Gemini 2.5 Flash or GPT-4.1 mini?
Gemini 2.5 Flash is the better all-round choice, scoring 68/100 against GPT-4.1 mini (60) and DeepSeek-V3.1 (55). It leads on inputs & features. DeepSeek-V3.1 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, DeepSeek-V3.1, Gemini 2.5 Flash or GPT-4.1 mini?
DeepSeek-V3.1 is cheaper at $0.385 input / $1.25 output per million tokens (median across 8 API providers). GPT-4.1 mini costs $0.40 input / $1.60 output per million tokens (official OpenAI API price); 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 $0.70 for GPT-4.1 mini (1.2× as much) and $0.85 for Gemini 2.5 Flash (1.4× as much).
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 GPT-4.1 mini 135.0 (#115 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 DeepSeek-V3.1, Gemini 2.5 Flash and GPT-4.1 mini 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 GPT-4.1 mini have the largest context windows (1,048,576 and 1,047,576 tokens), against 131,072 for DeepSeek-V3.1. Maximum output per response: DeepSeek-V3.1 up to 8,192, Gemini 2.5 Flash up to 65,536, GPT-4.1 mini up to 32,768 tokens.
Which can read images, PDFs, audio or video?
DeepSeek-V3.1 accepts text; Gemini 2.5 Flash accepts text, images, PDFs, audio and video; GPT-4.1 mini accepts text, images and PDFs. 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 GPT-4.1 mini is proprietary.
Which is newer?
DeepSeek-V3.1 is the newest, released Aug 21, 2025. Gemini 2.5 Flash came out Jun 17, 2025; GPT-4.1 mini came out Apr 14, 2025. Knowledge cutoff: Gemini 2.5 Flash Jan 2025, GPT-4.1 mini Apr 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.