Gemini 2.5 Pro vs Mistral Medium 3.5 vs Claude Sonnet 4
Gemini 2.5 Pro comes out ahead, 63 to 55 and 51 on our weighted score, though Mistral Medium 3.5 is 13% cheaper per token.
- Our pick
GoogleGemini 2.5 Pro
63/100- ECI145.3
- Price$1.25 / $10.00
- Context1.05M
Mistral AIMistral Medium 3.5
55/100- ECI141.4
- Price$1.50 / $7.50
- Context262K
AnthropicClaude Sonnet 4
51/100- ECI141.7
- Price$3.00 / $15.00
- Context200K
Gemini 2.5 Pro is our pick
Gemini 2.5 Pro is the better all-round choice, scoring 63/100 against Mistral Medium 3.5 (55) and Claude Sonnet 4 (51). It leads on capability, inputs & features and context window. Mistral Medium 3.5 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- CapabilityGemini 2.5 ProCapabilities Index (ECI): Gemini 2.5 Pro 145.3 · Claude Sonnet 4 141.7 · Mistral Medium 3.5 141.4
- Lowest priceMistral Medium 3.5Mistral Medium 3.5 $3.00 · Gemini 2.5 Pro $3.44 · Claude Sonnet 4 $6.00 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 ProGemini 2.5 Pro 1,048,576 · Mistral Medium 3.5 262,144 · Claude Sonnet 4 200,000 tokens
- Widest inputsGemini 2.5 ProGemini 2.5 Pro: Text, Images, PDFs, Audio, Video · Mistral Medium 3.5: Text, Images · Claude Sonnet 4: Text, Images, PDFs
- Self-hostingMistral Medium 3.5Publishes downloadable weights
| Measure | Weight | Gemini 2.5 Pro | Mistral Medium 3.5 | Claude Sonnet 4 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 72 | 67 | 68 |
| Price | 25% | 24 | 27 | 13 |
| Inputs & features | 15% | 100 | 70 | 70 |
| Context window | 10% | 61 | 37 | 32 |
| Overall | 100% | 63/100 | 55/100 | 51/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Gemini 2.5 ProGoogle | Mistral Medium 3.5Mistral AI | Claude Sonnet 4Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 145.3 (best) | 141.4 | 141.7 |
| ECI rank | #78 of 148 (best) | #95 of 148 | #94 of 148 |
| GPQA DiamondGraduate-level science questions | 85.3% (best) | — | 79.2% |
| FrontierMath Tiers 1–3Research-level mathematics | 24.6% | — | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 84.7% (best) | — | 71.1% |
| SWE-bench VerifiedFixing real GitHub issues | 57.6% | — | — |
| Price per million tokens | |||
| Input | $1.25 (best) | $1.50 | $3.00 |
| Output | $10.00 | $7.50 (best) | $15.00 |
| Cached input | $0.125 (best) | $0.15 | — |
| Blended (3:1) | $3.44 | $3.00 (best) | $6.00 |
| Long-context rate | Over 200K: $2.50 / $15.00 | Same rate | Same rate |
| Price source | Official Google API | Official Mistral API | Median of 9 providers |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 262,144 tokens | 200,000 tokens |
| Max output | 65,536 tokens | 262,144 tokens (best) | 64,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | Yes | No | Yes |
| Audio | Yes | No | No |
| Video | Yes | No | No |
| Reasoning | Yes | Yeshigh | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | gemini-2.5-pro | mistral-medium-2604 | — |
| API providers | 22 (best) | 12 | 9 |
| Released | Jun 17, 2025 | Apr 29, 2026 | May 22, 2025 |
| Knowledge cutoff | Jan 2025 | — | Mar 31, 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 2.5 Pro$32.50
- Mistral Medium 3.5$30.00
- Claude Sonnet 4$60.00
Which should you choose?
Which is better: Gemini 2.5 Pro, Mistral Medium 3.5 or Claude Sonnet 4?
Gemini 2.5 Pro is the better all-round choice, scoring 63/100 against Mistral Medium 3.5 (55) and Claude Sonnet 4 (51). It leads on capability, inputs & features and context window. Mistral Medium 3.5 wins on price. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, Gemini 2.5 Pro, Mistral Medium 3.5 or Claude Sonnet 4?
Mistral Medium 3.5 is cheaper at $1.50 input / $7.50 output per million tokens (official Mistral API price). Gemini 2.5 Pro costs $1.25 input / $10.00 output per million tokens (official Google API price); Claude Sonnet 4 costs $3.00 input / $15.00 output per million tokens (median across 9 API providers). At a typical mix of three input tokens to one output token, that is $3.00 per million tokens for Mistral Medium 3.5 versus $3.44 for Gemini 2.5 Pro (1.1× as much) and $6.00 for Claude Sonnet 4 (2× as much).
Which scores higher on benchmarks?
Gemini 2.5 Pro scores higher on the Capabilities Index (ECI): Gemini 2.5 Pro 145.3 (#78 of 148), Claude Sonnet 4 141.7 (#94 of 148) and Mistral Medium 3.5 141.4 (#95 of 148). Their confidence ranges do not overlap (143.6–146.9 vs 139.2–142.9), so the gap is a real one.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Medium 3.5 and Claude Sonnet 4 yet, so there is no like-for-like coding score. On overall capability, Gemini 2.5 Pro 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 Pro has the largest context window at 1,048,576 tokens, against 262,144 for Mistral Medium 3.5 and 200,000 for Claude Sonnet 4. Maximum output per response: Gemini 2.5 Pro up to 65,536, Mistral Medium 3.5 up to 262,144, Claude Sonnet 4 up to 64,000 tokens.
Which can read images, PDFs, audio or video?
Gemini 2.5 Pro accepts text, images, PDFs, audio and video; Mistral Medium 3.5 accepts text and images; Claude Sonnet 4 accepts text, images and PDFs. Gemini 2.5 Pro handles the widest range of inputs.
Are any of these open source?
Mistral Medium 3.5 publishes its weights and can be self-hosted; Gemini 2.5 Pro and Claude Sonnet 4 is proprietary.
Which is newer?
Mistral Medium 3.5 is the newest, released Apr 29, 2026. Gemini 2.5 Pro came out Jun 17, 2025; Claude Sonnet 4 came out May 22, 2025. Knowledge cutoff: Gemini 2.5 Pro Jan 2025, Claude Sonnet 4 Mar 31, 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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