Claude Opus 4.1 vs Magistral Medium vs o3-pro
Too close to call on our weighted score (Magistral Medium 30, Claude Opus 4.1 27, o3-pro 27). The right pick depends on what you value most.
AnthropicClaude Opus 4.1
27/100- ECI144.1
- Price$15.00 / $75.00
- Context200K
Mistral AIMagistral Medium
30/100- ECI—
- Price$2.00 / $5.00
- Context128K
OpenAIo3-pro
27/100- ECI147.4
- Price$20.00 / $80.00
- Context200K
Too close to call
It is close. Our weighted score puts them within 2 points (Magistral Medium 30/100, Claude Opus 4.1 27/100, o3-pro 27/100), so choose by what matters most for your work: Magistral Medium on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
- CapabilityNot enough dataNo independent benchmark covers every model here yet
- Lowest priceMagistral MediumMagistral Medium $2.75 · Claude Opus 4.1 $30.00 · o3-pro $35.00 per 1M tokens (3:1 blend)
- Longest contextClaude Opus 4.1 and o3-proClaude Opus 4.1 200,000 · o3-pro 200,000 · Magistral Medium 128,000 tokens
- Widest inputsClaude Opus 4.1Claude Opus 4.1: Text, Images, PDFs · Magistral Medium: Text · o3-pro: Text, Images
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | Claude Opus 4.1 | Magistral Medium | o3-pro |
|---|---|---|---|---|
| Price | 50% | 0 | 29 | 0 |
| Inputs & features | 30% | 70 | 35 | 70 |
| Context window | 20% | 32 | 24 | 32 |
| Overall | 100% | 27/100 | 30/100 | 27/100 |
Left out because at least one model lacks the data: capability. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Claude Opus 4.1Anthropic | Magistral MediumMistral AI | o3-proOpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 144.1 | — | 147.4 (best) |
| ECI rank | #81 of 148 | — | #60 of 148 (best) |
| GPQA DiamondGraduate-level science questions | 77.3% | — | — |
| FrontierMath Tiers 1–3Research-level mathematics | 12.6% | — | — |
| OTIS Mock AIME 2024–2025Competition mathematics | 68.9% | — | — |
| SWE-bench VerifiedFixing real GitHub issues | 73.4% | — | — |
| Price per million tokens | |||
| Input | $15.00 | $2.00 (best) | $20.00 |
| Output | $75.00 | $5.00 (best) | $80.00 |
| Cached input | — | — | — |
| Blended (3:1) | $30.00 | $2.75 (best) | $35.00 |
| Long-context rate | Same rate | Same rate | Same rate |
| Price source | Median of 14 providers | Official Mistral API | Official OpenAI API |
| Limits | |||
| Context window | 200,000 tokens (best) | 128,000 tokens | 200,000 tokens (best) |
| Max output | 32,000 tokens | 16,384 tokens | 100,000 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | Yes | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yes | Yeslow · medium · high |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | No | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | — | magistral-medium-latest | o3-pro |
| API providers | 14 (best) | 4 | 6 |
| Released | Aug 5, 2025 | Mar 17, 2025 | Jun 10, 2025 |
| Knowledge cutoff | Mar 31, 2025 | Jun 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.
- Claude Opus 4.1$300.00
- Magistral Medium$30.00
- o3-pro$360.00
Which should you choose?
Which is better: Claude Opus 4.1, Magistral Medium or o3-pro?
It is close. Our weighted score puts them within 2 points (Magistral Medium 30/100, Claude Opus 4.1 27/100, o3-pro 27/100), so choose by what matters most for your work: Magistral Medium on price. The score weighs price 50%, inputs & features 30%, context window 20%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Claude Opus 4.1, Magistral Medium or o3-pro?
Magistral Medium is cheaper at $2.00 input / $5.00 output per million tokens (official Mistral API price). Claude Opus 4.1 costs $15.00 input / $75.00 output per million tokens (median across 14 API providers); o3-pro costs $20.00 input / $80.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $2.75 per million tokens for Magistral Medium versus $30.00 for Claude Opus 4.1 (11× as much) and $35.00 for o3-pro (13× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Claude Opus 4.1 has an ECI of 144.1, Magistral Medium has not been scored yet and o3-pro has an ECI of 147.4.
Which is better for coding?
There are no published SWE-bench Verified results for Magistral Medium and o3-pro yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. All three support tool calling for agent workflows.
Which has the bigger context window?
Claude Opus 4.1 and o3-pro have the largest context windows (200,000 and 200,000 tokens), against 128,000 for Magistral Medium. Maximum output per response: Claude Opus 4.1 up to 32,000, Magistral Medium up to 16,384, o3-pro up to 100,000 tokens.
Which can read images, PDFs, audio or video?
Claude Opus 4.1 accepts text, images and PDFs; Magistral Medium accepts text; o3-pro accepts text and images. Claude Opus 4.1 handles the widest range of inputs.
Are any of these open source?
No. Claude Opus 4.1, Magistral Medium and o3-pro are proprietary and only available through APIs and apps.
Which is newer?
Claude Opus 4.1 is the newest, released Aug 5, 2025. o3-pro came out Jun 10, 2025; Magistral Medium came out Mar 17, 2025. Knowledge cutoff: Claude Opus 4.1 Mar 31, 2025, Magistral Medium Jun 2025, o3-pro 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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