GPT-5.1 Chat vs Kimi K2 Thinking vs Kimi K2 Thinking Turbo
GPT-5.1 Chat comes out ahead, 52 to 36 and 36 on our weighted score, though Kimi K2 Thinking is 3.2× cheaper per token.
- Our pick
OpenAIGPT-5.1 Chat
52/100- ECI—
- Price$1.25 / $10.00
- Context128K
Moonshot AIKimi K2 Thinking
36/100- ECI146.0
- Price$0.60 / $2.50
- Context262K
- Moonshot AI
Kimi K2 Thinking Turbo
36/100- ECI—
- Price—
- Context262K
GPT-5.1 Chat is our pick
GPT-5.1 Chat is the better all-round choice, scoring 52/100 against Kimi K2 Thinking (36) and Kimi K2 Thinking Turbo (36). It leads on inputs & features. 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 priceKimi K2 ThinkingKimi K2 Thinking $1.07 · GPT-5.1 Chat $3.44 per 1M tokens (3:1 blend) · Kimi K2 Thinking Turbo unpriced
- Longest contextKimi K2 Thinking and Kimi K2 Thinking TurboKimi K2 Thinking 262,144 · Kimi K2 Thinking Turbo 262,144 · GPT-5.1 Chat 128,000 tokens
- Widest inputsGPT-5.1 ChatGPT-5.1 Chat: Text, Images · Kimi K2 Thinking: Text · Kimi K2 Thinking Turbo: Text
- Self-hostingKimi K2 Thinking and Kimi K2 Thinking TurboPublishes downloadable weights
| Measure | Weight | GPT-5.1 Chat | Kimi K2 Thinking | Kimi K2 Thinking Turbo |
|---|---|---|---|---|
| Inputs & features | 60% | 70 | 35 | 35 |
| Context window | 40% | 24 | 37 | 37 |
| Overall | 100% | 52/100 | 36/100 | 36/100 |
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 | GPT-5.1 ChatOpenAI | Kimi K2 ThinkingMoonshot AI | Kimi K2 Thinking TurboMoonshot AI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | — | 146.0 | — |
| ECI rank | — | #72 of 148 | — |
| GPQA DiamondGraduate-level science questions | — | 84.2% | — |
| OTIS Mock AIME 2024–2025Competition mathematics | — | 83.1% | — |
| Price per million tokens | |||
| Input | $1.25 | $0.60 (best) | — |
| Output | $10.00 | $2.50 (best) | — |
| Cached input | — | — | — |
| Blended (3:1) | $3.44 | $1.07 (best) | — |
| Long-context rate | Same rate | Same rate | — |
| Price source | Median of 2 providers | Median of 10 providers | — |
| Limits | |||
| Context window | 128,000 tokens | 262,144 tokens (best) | 262,144 tokens (best) |
| Max output | 16,384 tokens | 262,144 tokens (best) | 262,144 tokens (best) |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | No | No |
| PDFs | No | No | No |
| Audio | No | No | No |
| Video | No | No | No |
| Reasoning | Yes | Yes | Yes |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | No | No |
| Availability | |||
| Weights | Proprietary | Open | Open |
| API model ID | — | — | — |
| API providers | 2 | 10 (best) | — |
| Released | Nov 13, 2025 | Nov 6, 2025 | Nov 6, 2025 |
| Knowledge cutoff | Sep 30, 2024 | Aug 2024 | Aug 2024 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- GPT-5.1 Chat$32.50
- Kimi K2 Thinking$11.00
- Kimi K2 Thinking Turbo—
Which should you choose?
Which is better: GPT-5.1 Chat, Kimi K2 Thinking or Kimi K2 Thinking Turbo?
GPT-5.1 Chat is the better all-round choice, scoring 52/100 against Kimi K2 Thinking (36) and Kimi K2 Thinking Turbo (36). It leads on inputs & features. 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, GPT-5.1 Chat, Kimi K2 Thinking or Kimi K2 Thinking Turbo?
Kimi K2 Thinking is cheaper at $0.60 input / $2.50 output per million tokens (median across 10 API providers). 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 $1.07 per million tokens for Kimi K2 Thinking versus $3.44 for GPT-5.1 Chat (3.2× 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. GPT-5.1 Chat has not been scored yet, Kimi K2 Thinking has an ECI of 146.0 and Kimi K2 Thinking Turbo has not been scored yet.
Which is better for coding?
There are no published SWE-bench Verified results for GPT-5.1 Chat, Kimi K2 Thinking and Kimi K2 Thinking Turbo 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 and Kimi K2 Thinking Turbo have the largest context windows (262,144 and 262,144 tokens), against 128,000 for GPT-5.1 Chat. Maximum output per response: GPT-5.1 Chat up to 16,384, Kimi K2 Thinking up to 262,144, Kimi K2 Thinking Turbo up to 262,144 tokens.
Which can read images, PDFs, audio or video?
GPT-5.1 Chat accepts text and images; Kimi K2 Thinking accepts text; Kimi K2 Thinking Turbo accepts text. GPT-5.1 Chat handles the widest range of inputs.
Are any of these open source?
Kimi K2 Thinking and Kimi K2 Thinking Turbo publishes its weights and can be self-hosted; GPT-5.1 Chat is proprietary.
Which is newer?
GPT-5.1 Chat is the newest, released Nov 13, 2025. Kimi K2 Thinking came out Nov 6, 2025; Kimi K2 Thinking Turbo came out Nov 6, 2025. Knowledge cutoff: GPT-5.1 Chat Sep 30, 2024, Kimi K2 Thinking Aug 2024, Kimi K2 Thinking Turbo Aug 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.
