Kimi K2 Thinking Turbo vs Gemini 2.5 Computer Use Preview vs GPT-5.1 Chat
GPT-5.1 Chat comes out ahead, 52 to 46 and 36 on our weighted score.
Moonshot AI
Kimi K2 Thinking Turbo
36/100- ECI—
- Price—
- Context262K
Google
Gemini 2.5 Computer Use Preview
46/100- ECI—
- Price$1.25 / $10.00
- Context128K
- Our pick
OpenAI
GPT-5.1 Chat
52/100- ECI—
- Price$1.25 / $10.00
- Context128K
GPT-5.1 Chat is our pick
GPT-5.1 Chat is the better all-round choice, scoring 52/100 against Gemini 2.5 Computer Use Preview (46) and Kimi K2 Thinking Turbo (36). It leads on inputs & features. Kimi K2 Thinking Turbo wins on 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 priceGemini 2.5 Computer Use Preview and GPT-5.1 ChatGemini 2.5 Computer Use Preview $3.44 · GPT-5.1 Chat $3.44 per 1M tokens (3:1 blend) · Kimi K2 Thinking Turbo unpriced
- Longest contextKimi K2 Thinking TurboKimi K2 Thinking Turbo 262,144 · Gemini 2.5 Computer Use Preview 128,000 · GPT-5.1 Chat 128,000 tokens
- Widest inputsGemini 2.5 Computer Use Preview and GPT-5.1 ChatKimi K2 Thinking Turbo: Text · Gemini 2.5 Computer Use Preview: Text, Images · GPT-5.1 Chat: Text, Images
- Self-hostingKimi K2 Thinking TurboPublishes downloadable weights
| Measure | Weight | Kimi K2 Thinking Turbo | Gemini 2.5 Computer Use Preview | GPT-5.1 Chat |
|---|---|---|---|---|
| Inputs & features | 60% | 35 | 60 | 70 |
| Context window | 40% | 37 | 24 | 24 |
| Overall | 100% | 36/100 | 46/100 | 52/100 |
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 | |||
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | — | — |
| ECI rank | — | — | — |
| Price per million tokens | |||
| Input | — | $1.25 | $1.25 |
| Output | — | $10.00 | $10.00 |
| Cached input | — | — | — |
| Blended (3:1) | — | $3.44 | $3.44 |
| Long-context rate | — | Over 200K: $2.50 / $15.00 | Same rate |
| Price source | — | Official Google API | Median of 2 providers |
| Limits | |||
| Context window | 262,144 tokens (best) | 128,000 tokens | 128,000 tokens |
| Max output | 262,144 tokens (best) | 64,000 tokens | 16,384 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | No | 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 | No | Yes |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | — | gemini-2.5-computer-use-preview-10-2025 | — |
| API providers | — | 2 | 2 |
| Released | Nov 6, 2025 | Oct 7, 2025 | Nov 13, 2025 |
| Knowledge cutoff | Aug 2024 | Jan 2025 | 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.
Kimi K2 Thinking Turbo—
Gemini 2.5 Computer Use Preview$32.50
GPT-5.1 Chat$32.50
Which should you choose?
Which is better: Kimi K2 Thinking Turbo, Gemini 2.5 Computer Use Preview or GPT-5.1 Chat?
GPT-5.1 Chat is the better all-round choice, scoring 52/100 against Gemini 2.5 Computer Use Preview (46) and Kimi K2 Thinking Turbo (36). It leads on inputs & features. Kimi K2 Thinking Turbo wins on 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, Kimi K2 Thinking Turbo, Gemini 2.5 Computer Use Preview or GPT-5.1 Chat?
Gemini 2.5 Computer Use Preview is cheaper at $1.25 input / $10.00 output per million tokens (official Google API price). GPT-5.1 Chat costs $1.25 input / $10.00 output per million tokens (median across 2 API providers). At a typical mix of three input tokens to one output token, that is $3.44 per million tokens for Gemini 2.5 Computer Use Preview versus $3.44 for GPT-5.1 Chat (1× as much). Kimi K2 Thinking Turbo has no published per-token price.
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Kimi K2 Thinking Turbo has not been scored yet, Gemini 2.5 Computer Use Preview has not been scored yet and GPT-5.1 Chat has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for Kimi K2 Thinking Turbo, Gemini 2.5 Computer Use Preview and GPT-5.1 Chat 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?
Kimi K2 Thinking Turbo has the largest context window at 262,144 tokens, against 128,000 for Gemini 2.5 Computer Use Preview and 128,000 for GPT-5.1 Chat. Maximum output per response: Kimi K2 Thinking Turbo up to 262,144, Gemini 2.5 Computer Use Preview up to 64,000, GPT-5.1 Chat up to 16,384 tokens.
Which can read images, PDFs, audio or video?
Kimi K2 Thinking Turbo accepts text; Gemini 2.5 Computer Use Preview accepts text and images; GPT-5.1 Chat accepts text and images. Gemini 2.5 Computer Use Preview handles the widest range of inputs.
Are any of these open source?
Kimi K2 Thinking Turbo publishes its weights and can be self-hosted; Gemini 2.5 Computer Use Preview and GPT-5.1 Chat is proprietary.
Which is newer?
GPT-5.1 Chat is the newest, released Nov 13, 2025. Kimi K2 Thinking Turbo came out Nov 6, 2025; Gemini 2.5 Computer Use Preview came out Oct 7, 2025. Knowledge cutoff: Kimi K2 Thinking Turbo Aug 2024, Gemini 2.5 Computer Use Preview Jan 2025, GPT-5.1 Chat 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.