Gemini 2.5 Computer Use Preview vs GPT-5.1 Codex vs GPT-5.1 Codex Max
Too close to call on our weighted score (GPT-5.1 Codex 42, GPT-5.1 Codex Max 42, Gemini 2.5 Computer Use Preview 35). The right pick depends on what you value most.
Google
Gemini 2.5 Computer Use Preview
35/100- ECI—
- Price$1.25 / $10.00
- Context128K
OpenAI
GPT-5.1 Codex
42/100- ECI—
- Price$1.25 / $10.00
- Context400K
OpenAI
GPT-5.1 Codex Max
42/100- ECI—
- Price$1.25 / $10.00
- Context400K
Too close to call
It is close. Our weighted score puts them within a point (GPT-5.1 Codex 42/100, GPT-5.1 Codex Max 42/100, Gemini 2.5 Computer Use Preview 35/100), so choose by what matters most for your work: Gemini 2.5 Computer Use Preview 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 priceSame priceGemini 2.5 Computer Use Preview $3.44 · GPT-5.1 Codex $3.44 · GPT-5.1 Codex Max $3.44 per 1M tokens (3:1 blend)
- Longest contextGPT-5.1 Codex and GPT-5.1 Codex MaxGPT-5.1 Codex 400,000 · GPT-5.1 Codex Max 400,000 · Gemini 2.5 Computer Use Preview 128,000 tokens
- Widest inputsSame inputsGemini 2.5 Computer Use Preview: Text, Images · GPT-5.1 Codex: Text, Images · GPT-5.1 Codex Max: Text, Images
- Self-hostingNo open weightsAll three are available only through APIs
| Measure | Weight | Gemini 2.5 Computer Use Preview | GPT-5.1 Codex | GPT-5.1 Codex Max |
|---|---|---|---|---|
| Price | 50% | 24 | 24 | 24 |
| Inputs & features | 30% | 60 | 70 | 70 |
| Context window | 20% | 24 | 44 | 44 |
| Overall | 100% | 35/100 | 42/100 | 42/100 |
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 | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | $1.25 | $1.25 | $1.25 |
| Output | $10.00 | $10.00 | $10.00 |
| Cached input | — | — | — |
| Blended (3:1) | $3.44 | $3.44 | $3.44 |
| Long-context rate | Over 200K: $2.50 / $15.00 | Same rate | Same rate |
| Price source | Official Google API | Median of 10 providers | Median of 8 providers |
| Limits | |||
| Context window | 128,000 tokens | 400,000 tokens (best) | 400,000 tokens (best) |
| Max output | 64,000 tokens | 128,000 tokens (best) | 128,000 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | No | Yes | Yes |
| Availability | |||
| Weights | Proprietary | Proprietary | Proprietary |
| API model ID | gemini-2.5-computer-use-preview-10-2025 | — | — |
| API providers | 2 | 10 (best) | 8 |
| Released | Oct 7, 2025 | Nov 13, 2025 | Nov 13, 2025 |
| Knowledge cutoff | Jan 2025 | Sep 30, 2024 | Sep 30, 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 Computer Use Preview$32.50
GPT-5.1 Codex$32.50
GPT-5.1 Codex Max$32.50
Which should you choose?
Which is better: Gemini 2.5 Computer Use Preview, GPT-5.1 Codex or GPT-5.1 Codex Max?
It is close. Our weighted score puts them within a point (GPT-5.1 Codex 42/100, GPT-5.1 Codex Max 42/100, Gemini 2.5 Computer Use Preview 35/100), so choose by what matters most for your work: Gemini 2.5 Computer Use Preview 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, Gemini 2.5 Computer Use Preview, GPT-5.1 Codex or GPT-5.1 Codex Max?
Gemini 2.5 Computer Use Preview, GPT-5.1 Codex and GPT-5.1 Codex Max cost the same: $1.25 input / $10.00 output per million tokens.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Gemini 2.5 Computer Use Preview has not been scored yet, GPT-5.1 Codex has not been scored yet and GPT-5.1 Codex Max has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Gemini 2.5 Computer Use Preview, GPT-5.1 Codex and GPT-5.1 Codex Max 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?
GPT-5.1 Codex and GPT-5.1 Codex Max have the largest context windows (400,000 and 400,000 tokens), against 128,000 for Gemini 2.5 Computer Use Preview. Maximum output per response: Gemini 2.5 Computer Use Preview up to 64,000, GPT-5.1 Codex up to 128,000, GPT-5.1 Codex Max up to 128,000 tokens.
Which can read images, PDFs, audio or video?
Gemini 2.5 Computer Use Preview accepts text and images; GPT-5.1 Codex accepts text and images; GPT-5.1 Codex Max accepts text and images. They handle the same number of input types.
Are any of these open source?
No. Gemini 2.5 Computer Use Preview, GPT-5.1 Codex and GPT-5.1 Codex Max are proprietary and only available through APIs and apps.
Which is newer?
GPT-5.1 Codex is the newest, released Nov 13, 2025. GPT-5.1 Codex Max came out Nov 13, 2025; Gemini 2.5 Computer Use Preview came out Oct 7, 2025. Knowledge cutoff: Gemini 2.5 Computer Use Preview Jan 2025, GPT-5.1 Codex Sep 30, 2024, GPT-5.1 Codex Max Sep 30, 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.