Kimi K3 vs Kimi K3.1 Pro vs GPT-5.6 Terra
Too close to call on our weighted score (Kimi K3.1 Pro 46, GPT-5.6 Terra 45, Kimi K3 42). The right pick depends on what you value most.
Moonshot AIKimi K3
42/100- ECI158.3
- Price$3.00 / $15.00
- Context1.05M
- Moonshot AI
Kimi K3.1 Pro
46/100- ECI—
- Price$2.00 / $10.00
- Context1.05M
OpenAIGPT-5.6 Terra
45/100- ECI160.1
- Price$2.00 / $12.00
- Context1.05M
Too close to call
It is close. Our weighted score puts them within 1 points (Kimi K3.1 Pro 46/100, GPT-5.6 Terra 45/100, Kimi K3 42/100), so choose by what matters most for your work: Kimi K3.1 Pro 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 priceKimi K3.1 ProKimi K3.1 Pro $4.00 · GPT-5.6 Terra $4.50 · Kimi K3 $6.00 per 1M tokens (3:1 blend)
- Longest contextAbout the sameGPT-5.6 Terra 1,050,000 · Kimi K3 1,048,576 · Kimi K3.1 Pro 1,048,576 tokens
- Widest inputsSame inputsKimi K3: Text, Images, Video · Kimi K3.1 Pro: Text, Images, Video · GPT-5.6 Terra: Text, Images, PDFs
- Self-hostingKimi K3Publishes downloadable weights
| Measure | Weight | Kimi K3 | Kimi K3.1 Pro | GPT-5.6 Terra |
|---|---|---|---|---|
| Price | 50% | 12 | 20 | 18 |
| Inputs & features | 30% | 80 | 80 | 80 |
| Context window | 20% | 61 | 61 | 61 |
| Overall | 100% | 42/100 | 46/100 | 45/100 |
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 | Kimi K3Moonshot AI | Kimi K3.1 ProMoonshot AI | GPT-5.6 TerraOpenAI |
|---|---|---|---|
| Capability | |||
| Capabilities Index (ECI) | 158.3 | — | 160.1 (best) |
| ECI rank | #20 of 165 | — | #15 of 165 (best) |
| GPQA DiamondGraduate-level science questions | 93.1% | — | 93.3% (best) |
| FrontierMath Tiers 1–3Research-level mathematics | 72.2% | — | 86.0% (best) |
| OTIS Mock AIME 2024–2025Competition mathematics | 97.2% | — | 99.7% (best) |
| SimpleQA VerifiedShort factual questions | 50.6% (best) | — | 43.2% |
| Price per million tokens | |||
| Input | $3.00 | $2.00 (best) | $2.00 (best) |
| Output | $15.00 | $10.00 (best) | $12.00 |
| Cached input | $0.30 | $0.20 (best) | $0.20 (best) |
| Blended (3:1) | $6.00 | $4.00 (best) | $4.50 |
| Long-context rate | Same rate | Same rate | Over 272K: $4.00 / $18.00 |
| Price source | Official Moonshot AI API | Official Moonshot AI API | Official OpenAI API |
| Limits | |||
| Context window | 1,048,576 tokens | 1,048,576 tokens | 1,050,000 tokens (best) |
| Max output | 131,072 tokens (best) | 131,072 tokens (best) | 128,000 tokens |
| Inputs and features | |||
| Text | Yes | Yes | Yes |
| Images | Yes | Yes | Yes |
| PDFs | No | No | Yes |
| Audio | No | No | No |
| Video | Yes | Yes | No |
| Reasoning | Yeslow · high · max | Yeslow · high · max | Yeslow · medium · high · xhigh · max |
| Tool calling | Yes | Yes | Yes |
| Structured output | Yes | Yes | Yes |
| Availability | |||
| Weights | Open | Proprietary | Proprietary |
| API model ID | kimi-k3 | kimi-k3.1-pro | gpt-5.6-terra |
| API providers | 76 (best) | 17 | 45 |
| Released | Jul 16, 2026 | Oct 23, 2026 | Jul 9, 2026 |
| Knowledge cutoff | — | — | Feb 16, 2026 |
What would a month cost?
Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.
- Kimi K3$60.00
- Kimi K3.1 Pro$40.00
- GPT-5.6 Terra$44.00
Which should you choose?
Which is better: Kimi K3, Kimi K3.1 Pro or GPT-5.6 Terra?
It is close. Our weighted score puts them within 1 points (Kimi K3.1 Pro 46/100, GPT-5.6 Terra 45/100, Kimi K3 42/100), so choose by what matters most for your work: Kimi K3.1 Pro 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, Kimi K3, Kimi K3.1 Pro or GPT-5.6 Terra?
Kimi K3.1 Pro is cheaper at $2.00 input / $10.00 output per million tokens (official Moonshot AI API price). GPT-5.6 Terra costs $2.00 input / $12.00 output per million tokens (official OpenAI API price); Kimi K3 costs $3.00 input / $15.00 output per million tokens (official Moonshot AI API price). At a typical mix of three input tokens to one output token, that is $4.00 per million tokens for Kimi K3.1 Pro versus $4.50 for GPT-5.6 Terra (1.1× as much) and $6.00 for Kimi K3 (1.5× as much).
Which scores higher on benchmarks?
There is no independent benchmark that covers all three models yet. Kimi K3 has an ECI of 158.3, Kimi K3.1 Pro has not been scored yet and GPT-5.6 Terra has an ECI of 160.1.
Which is better for coding?
There are no published SWE-bench Verified results for Kimi K3, Kimi K3.1 Pro and GPT-5.6 Terra 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?
Their context windows are effectively the same size: Kimi K3 1,048,576, Kimi K3.1 Pro 1,048,576 and GPT-5.6 Terra 1,050,000 tokens. Maximum output per response: Kimi K3 up to 131,072, Kimi K3.1 Pro up to 131,072, GPT-5.6 Terra up to 128,000 tokens.
Which can read images, PDFs, audio or video?
Kimi K3 accepts text, images and video; Kimi K3.1 Pro accepts text, images and video; GPT-5.6 Terra accepts text, images and PDFs. They handle the same number of input types.
Are any of these open source?
Kimi K3 publishes its weights and can be self-hosted; Kimi K3.1 Pro and GPT-5.6 Terra is proprietary.
Which is newer?
Kimi K3.1 Pro is the newest, released Oct 23, 2026. Kimi K3 came out Jul 16, 2026; GPT-5.6 Terra came out Jul 9, 2026. Knowledge cutoff: GPT-5.6 Terra Feb 16, 2026.
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 Nov 2, 2026.
