Gemini 2.0 Flash vs GPT-4.1 mini vs Mistral Medium 3
Gemini 2.0 Flash comes out ahead, 65 to 61 and 52 on our weighted score.
- Our pick
GoogleGemini 2.0 Flash
65/100- ECI134.7
- Price—
- Context1.05M
OpenAIGPT-4.1 mini
61/100- ECI135.0
- Price$0.40 / $1.60
- Context1.05M
Mistral AIMistral Medium 3
52/100- ECI134.1
- Price$0.40 / $2.00
- Context131K
Gemini 2.0 Flash is our pick
Gemini 2.0 Flash is the better all-round choice, scoring 65/100 against GPT-4.1 mini (61) and Mistral Medium 3 (52). It leads on inputs & features. The score weighs capability 67%, inputs & features 20%, context window 13%.
- CapabilityGPT-4.1 miniCapabilities Index (ECI): GPT-4.1 mini 135.0 · Gemini 2.0 Flash 134.7 · Mistral Medium 3 134.1
- Lowest priceGPT-4.1 miniGPT-4.1 mini $0.70 · Mistral Medium 3 $0.80 per 1M tokens (3:1 blend) · Gemini 2.0 Flash unpriced
- Longest contextGemini 2.0 Flash and GPT-4.1 miniGemini 2.0 Flash 1,048,576 · GPT-4.1 mini 1,047,576 · Mistral Medium 3 131,072 tokens
- Widest inputsGemini 2.0 FlashGemini 2.0 Flash: Text, Images, PDFs, Audio, Video · GPT-4.1 mini: Text, Images, PDFs · Mistral Medium 3: Text, Images
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | Gemini 2.0 Flash | GPT-4.1 mini | Mistral Medium 3 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 67% | 59 | 59 | 58 |
| Inputs & features | 20% | 90 | 70 | 50 |
| Context window | 13% | 61 | 61 | 24 |
| Overall | 100% | 65/100 | 61/100 | 52/100 |
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 2.0 FlashGoogle | GPT-4.1 miniOpenAI | Mistral Medium 3Mistral AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 134.7 | 135.0 (best) | 134.1 |
| ECI rank | #116 of 148 | #115 of 148 (best) | #117 of 148 |
| GPQA DiamondGraduate-level science questions | — | 65.9% (best) | 59.5% |
| FrontierMath Tiers 1–3Research-level mathematics | — | 6.7% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 44.7% (best) | 32.2% |
| SimpleQA VerifiedShort factual questions | — | 12.7% | — |
| Price per million tokens | |||
| Input | — | $0.40 | $0.40 |
| Output | — | $1.60 (best) | $2.00 |
| Cached input | — | $0.10 | — |
| Blended (3:1) | — | $0.70 (best) | $0.80 |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Official OpenAI API | Official Mistral API |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 1,047,576 tokens | 131,072 tokens |
| Max output | 8,192 tokens | 32,768 tokens | 131,072 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | Yes | Yes | No |
| Audio | Yes | No | No |
| Video | Yes | No | No |
| Reasoning | No | No | No |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | — | gpt-4.1-mini | mistral-medium-2505 |
| API providers | — | 24 (best) | 5 |
| Released | Dec 11, 2024 | Apr 14, 2025 | May 7, 2025 |
| Knowledge cutoff | Jun 2024 | Apr 2024 | May 2025 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Gemini 2.0 Flash—
- GPT-4.1 mini$7.20
- Mistral Medium 3$8.00
Which should you choose?
Which is better: Gemini 2.0 Flash, GPT-4.1 mini or Mistral Medium 3?
Gemini 2.0 Flash is the better all-round choice, scoring 65/100 against GPT-4.1 mini (61) and Mistral Medium 3 (52). It leads on inputs & features. The score weighs capability 67%, inputs & features 20%, context window 13%.
Which is cheaper, Gemini 2.0 Flash, GPT-4.1 mini or Mistral Medium 3?
GPT-4.1 mini is cheaper at $0.40 input / $1.60 output per million tokens (official OpenAI API price). Mistral Medium 3 costs $0.40 input / $2.00 output per million tokens (official Mistral API price). At a typical mix of three input tokens to one output token, that is $0.70 per million tokens for GPT-4.1 mini versus $0.80 for Mistral Medium 3 (1.1× as much). Gemini 2.0 Flash has no published per-token price.
Which scores higher on benchmarks?
GPT-4.1 mini scores higher on the Capabilities Index (ECI): GPT-4.1 mini 135.0 (#115 of 148), Gemini 2.0 Flash 134.7 (#116 of 148) and Mistral Medium 3 134.1 (#117 of 148). The confidence ranges of the top two overlap (131.2–136.6 vs 124.3–136.7), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for Gemini 2.0 Flash, GPT-4.1 mini and Mistral Medium 3 yet, so there is no like-for-like coding score. On overall capability, GPT-4.1 mini 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 2.0 Flash and GPT-4.1 mini have the largest context windows (1,048,576 and 1,047,576 tokens), against 131,072 for Mistral Medium 3. Maximum output per response: Gemini 2.0 Flash up to 8,192, GPT-4.1 mini up to 32,768, Mistral Medium 3 up to 131,072 tokens.
Which can read images, PDFs, audio or video?
Gemini 2.0 Flash accepts text, images, PDFs, audio and video; GPT-4.1 mini accepts text, images and PDFs; Mistral Medium 3 accepts text and images. Gemini 2.0 Flash handles the widest range of inputs.
Are any of these open source?
No. Gemini 2.0 Flash, GPT-4.1 mini and Mistral Medium 3 are proprietary and only available through APIs and apps.
Which is newer?
Mistral Medium 3 is the newest, released May 7, 2025. GPT-4.1 mini came out Apr 14, 2025; Gemini 2.0 Flash came out Dec 11, 2024. Knowledge cutoff: Gemini 2.0 Flash Jun 2024, GPT-4.1 mini Apr 2024, Mistral Medium 3 May 2025.
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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