Aya Vision 32B vs Magistral Medium vs Claude Opus 4.1
Claude Opus 4.1 comes out ahead, 55 to 31 and 15 on our weighted score, though Magistral Medium is 11× cheaper per token.
CohereAya Vision 32B
15/100- ECI—
- Price—
- Context16K
Mistral AIMagistral Medium
31/100- ECI—
- Price$2.00 / $5.00
- Context128K
- Our pick
AnthropicClaude Opus 4.1
55/100- ECI144.1
- Price$15.00 / $75.00
- Context200K
Claude Opus 4.1 is our pick
Claude Opus 4.1 is the better all-round choice, scoring 55/100 against Magistral Medium (31) and Aya Vision 32B (15). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. 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 per 1M tokens (3:1 blend) · Aya Vision 32B unpriced
- Longest contextClaude Opus 4.1Claude Opus 4.1 200,000 · Magistral Medium 128,000 · Aya Vision 32B 16,000 tokens
- Widest inputsClaude Opus 4.1Aya Vision 32B: Text, Images · Magistral Medium: Text · Claude Opus 4.1: Text, Images, PDFs
- Self-hostingAya Vision 32BPublishes downloadable weights (CC-BY-NC-4.0)
| Measure | Weight | Aya Vision 32B | Magistral Medium | Claude Opus 4.1 |
|---|---|---|---|---|
| Inputs & features | 60% | 25 | 35 | 70 |
| Context window | 40% | 0 | 24 | 32 |
| Overall | 100% | 15/100 | 31/100 | 55/100 |
Left out because at least one model lacks the data: capability and price. The remaining weights were rescaled.
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | Aya Vision 32BCohere | Magistral MediumMistral AI | Claude Opus 4.1Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | 144.1 |
| ECI rank | — | — | #81 of 148 |
| 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 | — | $2.00 (best) | $15.00 |
| Output | — | $5.00 (best) | $75.00 |
| Cached input | — | — | — |
| Blended (3:1) | — | $2.75 (best) | $30.00 |
| Long-context rate | — | Same rate | Same rate |
| Price source | — | Official Mistral API | Median of 14 providers |
| Limits | |||
| Context window | 16,000 tokens | 128,000 tokens | 200,000 tokens (best) |
| Max output | 4,000 tokens | 16,384 tokens | 32,000 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | No | Yes | Yes |
| Tool calling | No | Yes | Yes |
| Structured output | No | No | No |
| Availability | |||
| Weights | OpenCC-BY-NC-4.0 | Proprietary | Proprietary |
| API model ID | c4ai-aya-vision-32b | magistral-medium-latest | — |
| API providers | 1 | 4 | 14 (best) |
| Released | Mar 4, 2025 | Mar 17, 2025 | Aug 5, 2025 |
| Knowledge cutoff | — | Jun 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.
- Aya Vision 32B—
- Magistral Medium$30.00
- Claude Opus 4.1$300.00
Which should you choose?
Which is better: Aya Vision 32B, Magistral Medium or Claude Opus 4.1?
Claude Opus 4.1 is the better all-round choice, scoring 55/100 against Magistral Medium (31) and Aya Vision 32B (15). It leads on inputs & features and context window. The score weighs inputs & features 60%, context window 40%. None of the shared benchmarks cover every model here yet, so capability is left out of this verdict.
Which is cheaper, Aya Vision 32B, Magistral Medium or Claude Opus 4.1?
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). 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). Aya Vision 32B has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Aya Vision 32B has not been scored yet, Magistral Medium has not been scored yet and Claude Opus 4.1 has an ECI of 144.1.
Which is better for coding?
There are no published SWE-bench Verified results for Aya Vision 32B and Magistral Medium yet, so there is no like-for-like coding score. Test both on a sample of your own tasks. Note that Aya Vision 32B does not support tool calling, which most coding agents need.
Which has the bigger context window?
Claude Opus 4.1 has the largest context window at 200,000 tokens, against 128,000 for Magistral Medium and 16,000 for Aya Vision 32B. Maximum output per response: Aya Vision 32B up to 4,000, Magistral Medium up to 16,384, Claude Opus 4.1 up to 32,000 tokens.
Which can read images, PDFs, audio or video?
Aya Vision 32B accepts text and images; Magistral Medium accepts text; Claude Opus 4.1 accepts text, images and PDFs. Claude Opus 4.1 handles the widest range of inputs.
Are any of these open source?
Aya Vision 32B publishes its weights (CC-BY-NC-4.0) and can be self-hosted; Magistral Medium and Claude Opus 4.1 is proprietary.
Which is newer?
Claude Opus 4.1 is the newest, released Aug 5, 2025. Magistral Medium came out Mar 17, 2025; Aya Vision 32B came out Mar 4, 2025. Knowledge cutoff: Magistral Medium Jun 2025, Claude Opus 4.1 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.
