o3-pro vs Gemini 2.5 Pro vs Claude Opus 4.1
Gemini 2.5 Pro comes out ahead, 63 to 51 and 49 on our weighted score, and it is the cheaper option too.
OpenAIo3-pro
51/100- ECI147.4
- Price$20.00 / $80.00
- Context200K
- Our pick
GoogleGemini 2.5 Pro
63/100- ECI145.3
- Price$1.25 / $10.00
- Context1.05M
AnthropicClaude Opus 4.1
49/100- ECI144.1
- Price$15.00 / $75.00
- Context200K
Gemini 2.5 Pro is our pick
Gemini 2.5 Pro is the better all-round choice, scoring 63/100 against o3-pro (51) and Claude Opus 4.1 (49). It leads on price, inputs & features and context window. o3-pro wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
- Capabilityo3-proCapabilities Index (ECI): o3-pro 147.4 · Gemini 2.5 Pro 145.3 · Claude Opus 4.1 144.1
- Lowest priceGemini 2.5 ProGemini 2.5 Pro $3.44 · Claude Opus 4.1 $30.00 · o3-pro $35.00 per 1M tokens (3:1 blend)
- Longest contextGemini 2.5 ProGemini 2.5 Pro 1,048,576 · o3-pro 200,000 · Claude Opus 4.1 200,000 tokens
- Widest inputsGemini 2.5 Proo3-pro: Text, Images · Gemini 2.5 Pro: Text, Images, PDFs, Audio, Video · Claude Opus 4.1: Text, Images, PDFs
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | o3-pro | Gemini 2.5 Pro | Claude Opus 4.1 |
|---|---|---|---|---|
| CapabilityCapabilities Index (ECI) | 50% | 75 | 72 | 71 |
| Price | 25% | 0 | 24 | 0 |
| Inputs & features | 15% | 70 | 100 | 70 |
| Context window | 10% | 32 | 61 | 32 |
| Overall | 100% | 51/100 | 63/100 | 49/100 |
Every spec in one table
Highlighted cells lead their row. Dashes mean the data is not published.
| Specification | o3-proOpenAI | Gemini 2.5 ProGoogle | Claude Opus 4.1Anthropic |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 147.4 (best) | 145.3 | 144.1 |
| ECI rank | #60 of 148 (best) | #78 of 148 | #81 of 148 |
| GPQA DiamondGraduate-level science questions | — | 85.3% (best) | 77.3% |
| FrontierMath Tiers 1–3Research-level mathematics | — | 24.6% (best) | 12.6% |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 84.7% (best) | 68.9% |
| SWE-bench VerifiedFixing real GitHub issues | — | 57.6% | 73.4% (best) |
| Price per million tokens | |||
| Input | $20.00 | $1.25 (best) | $15.00 |
| Output | $80.00 | $10.00 (best) | $75.00 |
| Cached input | — | $0.125 | — |
| Blended (3:1) | $35.00 | $3.44 (best) | $30.00 |
| Long-context rate | Same rate | Over 200K: $2.50 / $15.00 | Same rate |
| Price source | Official OpenAI API | Official Google API | Median of 14 providers |
| Limits | |||
| Context window | 200,000 tokens | 1,048,576 tokens (best) | 200,000 tokens |
| Max output | 100,000 tokens (best) | 65,536 tokens | 32,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | Yes | Yes |
| Audio | No | Yes | No |
| Video | No | Yes | No |
| Reasoning | Yeslow · medium · high | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | No |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | o3-pro | gemini-2.5-pro | — |
| API providers | 6 | 22 (best) | 14 |
| Released | Jun 10, 2025 | Jun 17, 2025 | Aug 5, 2025 |
| Knowledge cutoff | May 2024 | 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.
- o3-pro$360.00
- Gemini 2.5 Pro$32.50
- Claude Opus 4.1$300.00
Which should you choose?
Which is better: o3-pro, Gemini 2.5 Pro or Claude Opus 4.1?
Gemini 2.5 Pro is the better all-round choice, scoring 63/100 against o3-pro (51) and Claude Opus 4.1 (49). It leads on price, inputs & features and context window. o3-pro wins on capability. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.
Which is cheaper, o3-pro, Gemini 2.5 Pro or Claude Opus 4.1?
Gemini 2.5 Pro is cheaper at $1.25 input / $10.00 output per million tokens (official Google 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 $3.44 per million tokens for Gemini 2.5 Pro versus $30.00 for Claude Opus 4.1 (8.7× as much) and $35.00 for o3-pro (10× as much).
Which scores higher on benchmarks?
o3-pro scores higher on the Capabilities Index (ECI): o3-pro 147.4 (#60 of 148), Gemini 2.5 Pro 145.3 (#78 of 148) and Claude Opus 4.1 144.1 (#81 of 148). The confidence ranges of the top two overlap (145.8–149.7 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 o3-pro yet, so there is no like-for-like coding score. On overall capability, o3-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 200,000 for o3-pro and 200,000 for Claude Opus 4.1. Maximum output per response: o3-pro up to 100,000, Gemini 2.5 Pro up to 65,536, Claude Opus 4.1 up to 32,000 tokens.
Which can read images, PDFs, audio or video?
o3-pro accepts text and images; Gemini 2.5 Pro accepts text, images, PDFs, audio and video; Claude Opus 4.1 accepts text, images and PDFs. Gemini 2.5 Pro handles the widest range of inputs.
Are any of these open source?
No. o3-pro, Gemini 2.5 Pro and Claude Opus 4.1 are proprietary and only available through APIs and apps.
Which is newer?
Claude Opus 4.1 is the newest, released Aug 5, 2025. Gemini 2.5 Pro came out Jun 17, 2025; o3-pro came out Jun 10, 2025. Knowledge cutoff: o3-pro May 2024, Gemini 2.5 Pro Jan 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.
