Gemini 2.5 Pro vs Mistral Medium 3.5 vs o3
Gemini 2.5 Pro comes out ahead, 63 to 58 and 55 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
OpenAIo3
58/100- ECI146.9
- Price$2.00 / $8.00
- Context200K
Gemini 2.5 Pro is our pick
Gemini 2.5 Pro is the better all-round choice, scoring 63/100 against o3 (58) and Mistral Medium 3.5 (55). It leads on inputs & features and context window. Mistral Medium 3.5 wins on price. o3 wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- Capabilityo3Capabilities Index (ECI): o3 146.9 · Gemini 2.5 Pro 145.3 · Mistral Medium 3.5 141.4
- Lowest priceMistral Medium 3.5Mistral Medium 3.5 $3.00 · Gemini 2.5 Pro $3.44 · o3 $3.50 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 ProGemini 2.5 Pro 1,048,576 · Mistral Medium 3.5 262,144 · o3 200,000 tokens
- Widest inputsGemini 2.5 ProGemini 2.5 Pro: Text, Images, PDFs, Audio, Video · Mistral Medium 3.5: Text, Images · o3: Text, Images, PDFs
- Self-hostingMistral Medium 3.5Publishes downloadable weights
| Measure | Weight | Gemini 2.5 Pro | Mistral Medium 3.5 | o3 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 72 | 67 | 74 |
| Price | 25% | 24 | 27 | 24 |
| Inputs & features | 15% | 100 | 70 | 80 |
| Context window | 10% | 61 | 37 | 32 |
| Overall | 100% | 63/100 | 55/100 | 58/100 |
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 | o3OpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 145.3 | 141.4 | 146.9 (best) |
| ECI rank | #78 of 148 | #95 of 148 | #63 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 85.3% (best) | — | 81.8% |
| FrontierMath Tiers 1–3Research-level mathematics | 24.6% | — | 33.3% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 84.7% (best) | — | 84.4% |
| SWE-bench VerifiedFixing real GitHub issues | 57.6% | — | 62.3% (best) |
| SimpleQA VerifiedShort factual questions | — | — | 49.4% |
| Price per million tokens | |||
| Input | $1.25 (best) | $1.50 | $2.00 |
| Output | $10.00 | $7.50 (best) | $8.00 |
| Cached input | $0.125 (best) | $0.15 | $0.50 |
| Blended (3:1) | $3.44 | $3.00 (best) | $3.50 |
| Long-context rate | Over 200K: $2.50 / $15.00 | Same rate | Same rate |
| Price source | Official Google API | Official Mistral API | Official OpenAI API |
| Limits | |||
| Context window | 1,048,576 tokens (best) | 262,144 tokens | 200,000 tokens |
| Max output | 65,536 tokens | 262,144 tokens (best) | 100,000 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 | Yeslow · medium · high |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Open | Proprietary |
| API model ID | gemini-2.5-pro | mistral-medium-2604 | o3 |
| API providers | 22 (best) | 12 | 18 |
| Released | Jun 17, 2025 | Apr 29, 2026 | Apr 16, 2025 |
| Knowledge cutoff | Jan 2025 | — | May 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 Pro$32.50
- Mistral Medium 3.5$30.00
- o3$36.00
Which should you choose?
Which is better: Gemini 2.5 Pro, Mistral Medium 3.5 or o3?
Gemini 2.5 Pro is the better all-round choice, scoring 63/100 against o3 (58) and Mistral Medium 3.5 (55). It leads on inputs & features and context window. Mistral Medium 3.5 wins on price. o3 wins on capability. 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 o3?
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); o3 costs $2.00 input / $8.00 output per million tokens (official OpenAI API price). 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 $3.50 for o3 (1.2× as much).
Which scores higher on benchmarks?
o3 scores higher on the Capabilities Index (ECI): o3 146.9 (#63 of 148), Gemini 2.5 Pro 145.3 (#78 of 148) and Mistral Medium 3.5 141.4 (#95 of 148). The confidence ranges of the top two overlap (144.9–148.6 vs 143.6–146.9), so treat the gap as small.
Which is better for coding?
There are no published SWE-bench Verified results for Mistral Medium 3.5 yet, so there is no like-for-like coding score. On overall capability, o3 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 o3. Maximum output per response: Gemini 2.5 Pro up to 65,536, Mistral Medium 3.5 up to 262,144, o3 up to 100,000 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; o3 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 o3 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; o3 came out Apr 16, 2025. Knowledge cutoff: Gemini 2.5 Pro Jan 2025, o3 May 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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