o1-pro vs Claude Opus 4.1 vs Aya Vision 32B
Too close to call on our weighted score (o1-pro 55, Claude Opus 4.1 55, Aya Vision 32B 15). The right pick depends on what you value most.
OpenAIo1-pro
55/100- ECI—
- Price$150.00 / $600.00
- Context200K
AnthropicClaude Opus 4.1
55/100- ECI144.1
- Price$15.00 / $75.00
- Context200K
CohereAya Vision 32B
15/100- ECI—
- Price—
- Context16K
Too close to call
It is close. Our weighted score puts them within a point (o1-pro 55/100, Claude Opus 4.1 55/100, Aya Vision 32B 15/100), so choose by what matters most for your work: Claude Opus 4.1 on price. 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 priceClaude Opus 4.1Claude Opus 4.1 $30.00 · o1-pro $262.50 per 1M tokens (3:1 blend) · Aya Vision 32B unpriced
- Longest contexto1-pro and Claude Opus 4.1o1-pro 200,000 · Claude Opus 4.1 200,000 · Aya Vision 32B 16,000 tokens
- Widest inputsClaude Opus 4.1o1-pro: Text, Images · Claude Opus 4.1: Text, Images, PDFs · Aya Vision 32B: Text, Images
- Self-hostingAya Vision 32BPublishes downloadable weights (CC-BY-NC-4.0)
| Measure | Weight | o1-pro | Claude Opus 4.1 | Aya Vision 32B |
|---|---|---|---|---|
| Inputs & features | 60% | 70 | 70 | 25 |
| Context window | 40% | 32 | 32 | 0 |
| Overall | 100% | 55/100 | 55/100 | 15/100 |
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 | o1-proOpenAI | Claude Opus 4.1Anthropic | Aya Vision 32BCohere |
|---|---|---|---|
| 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 | $150.00 | $15.00 (best) | — |
| Output | $600.00 | $75.00 (best) | — |
| Cached input | — | — | — |
| Blended (3:1) | $262.50 | $30.00 (best) | — |
| Long-context rate | Same rate | Same rate | — |
| Price source | Official OpenAI API | Median of 14 providers | — |
| Limits | |||
| Context window | 200,000 tokens (best) | 200,000 tokens (best) | 16,000 tokens |
| Max output | 100,000 tokens (best) | 32,000 tokens | 4,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | Yes | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yeslow · medium · high | Yes | No |
| Tool calling | Yes | Yes | No |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | Proprietary | OpenCC-BY-NC-4.0 |
| API model ID | o1-pro | — | c4ai-aya-vision-32b |
| API providers | 5 | 14 (best) | 1 |
| Released | Mar 19, 2025 | Aug 5, 2025 | Mar 4, 2025 |
| Knowledge cutoff | Sep 2023 | 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.
- o1-pro$2,700
- Claude Opus 4.1$300.00
- Aya Vision 32B—
Which should you choose?
Which is better: o1-pro, Claude Opus 4.1 or Aya Vision 32B?
It is close. Our weighted score puts them within a point (o1-pro 55/100, Claude Opus 4.1 55/100, Aya Vision 32B 15/100), so choose by what matters most for your work: Claude Opus 4.1 on price. 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, o1-pro, Claude Opus 4.1 or Aya Vision 32B?
Claude Opus 4.1 is cheaper at $15.00 input / $75.00 output per million tokens (median across 14 API providers). o1-pro costs $150.00 input / $600.00 output per million tokens (official OpenAI API price). At a typical mix of three input tokens to one output token, that is $30.00 per million tokens for Claude Opus 4.1 versus $262.50 for o1-pro (8.8× 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. o1-pro has not been scored yet, Claude Opus 4.1 has an ECI of 144.1 and Aya Vision 32B has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for o1-pro and Aya Vision 32B 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?
o1-pro and Claude Opus 4.1 have the largest context windows (200,000 and 200,000 tokens), against 16,000 for Aya Vision 32B. Maximum output per response: o1-pro up to 100,000, Claude Opus 4.1 up to 32,000, Aya Vision 32B up to 4,000 tokens.
Which can read images, PDFs, audio or video?
o1-pro accepts text and images; Claude Opus 4.1 accepts text, images and PDFs; Aya Vision 32B accepts text and images. 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; o1-pro and Claude Opus 4.1 is proprietary.
Which is newer?
Claude Opus 4.1 is the newest, released Aug 5, 2025. o1-pro came out Mar 19, 2025; Aya Vision 32B came out Mar 4, 2025. Knowledge cutoff: o1-pro Sep 2023, 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.
