Kimi K2 0711
moonshotai/kimi-k2Kimi K2 Instruct is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass.
Standard pricing
Run this model at its standard rate. Cheap mode currently has no separate discount.
API routing ceilings, including your 5% Free-plan fee. Included usage applies first, then prepaid credits. Cached tokens and tools can have separate charges.
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A current API route is listed for this exact model. Gateway configuration is required for live calls.
Provider price + a transparent platform fee
| Rate | Provider baseline | Free plan · 5% fee | Paid plan · 4% fee |
|---|---|---|---|
| Input / 1M tokens | $0.57 | $0.5985 | $0.5928 |
| Output / 1M tokens | $2.3 | $2.415 | $2.392 |
| API input / 1M tokens | $0.57 | $0.5985 | $0.5928 |
| API output / 1M tokens | $2.3 | $2.415 | $2.392 |
Legacy chat image rates use the catalog baseline. The dedicated image playground shows separate estimates and settles the provider’s metered usage. API rates are current routing ceilings; final API charges use provider-reported cost plus your fee. Cheapest routing compares eligible OpenRouter and Cheaper Inference rates for the same model; savings are not guaranteed. Cached input or other provider charges may differ. Compare all model rates and verified discounts →
How your plan pays for usage
API and playground share one included allowance. Usage including the fee draws from that allowance first, then your prepaid credits. Plans bill monthly; included usage resets weekly: Free $1, Starter $5, Growth $25, Scale $50.
A $1 provider charge becomes $1.05 on Free or $1.04 on a paid plan before included usage is applied. Plan eligibility still applies in the playground.
Free models and limits
Zero-cost models stay $0, including the fee, and do not consume your dollar allowance. Free accounts can make 1,000 free-model API requests per calendar month, resetting in UTC. Admitted requests count even if the provider fails.
Free includes 20 API requests/minute and 6 playground messages/minute. Paid plans raise these limits. See plan limits.
Before a text API request, Gizmo temporarily reserves included usage and, if necessary, prepaid credit for the model’s full context plus your maximum output. Image jobs reserve twice their displayed estimate. Unused funds return after metering. This hold can exceed the final charge; unconfirmed usage remains marked pending.
Overview
Kimi K2 Instruct is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. It is optimized for agentic capabilities, including advanced tool use, reasoning, and code synthesis. Kimi K2 excels across a broad range of benchmarks, particularly in coding (LiveCodeBench, SWE-bench), reasoning (ZebraLogic, GPQA), and tool-use (Tau2, AceBench) tasks. It supports long-context inference up to 128K tokens and is designed with a novel training stack that includes the MuonClip optimizer for stable large-scale MoE training.
Benchmarks
Design Arena head-to-head, human-voted
| Category | Elo | Win rate | Rank |
|---|---|---|---|
| UI components | 1049 | 55.1% | #93 |
| Code | 1050 | 51.7% | #101 |
| Data viz | 1033 | 49.4% | #101 |
| Websites | 1064 | 53.1% | #102 |
| Game dev | 998 | 46.4% | #108 |
Instruction model evaluation results from the model card
| Benchmark | Metric | ||||||
|---|---|---|---|---|---|---|---|
| Coding Tasks | |||||||
| LiveCodeBench v6 | Pass@1 | 53.7 | 46.9 | 37.0 | 48.5 | 47.4 | 44.7 |
| OJBench | Pass@1 | 27.1 | 24.0 | 11.3 | 15.3 | 19.6 | 19.5 |
| MultiPL-E | Pass@1 | 85.7 | 83.1 | 78.2 | 88.6 | 89.6 | 86.7 |
| SWE-bench Verified | Single Patch w/o Test (Acc) | 51.8 | 36.6 | 39.4 | 50.2 | 53.0 | 40.8 |
| SWE-bench Verified | Single Attempt (Acc) | 65.8 | 38.8 | 34.4 | 72.7 | 72.5 | 54.6 |
| (Agentic Coding) | Multiple Attempts (Acc) | 71.6 | — | — | 80.2 | 79.4 | — |
| SWE-bench Multilingual | Single Attempt (Acc) | 47.3 | 25.8 | 20.9 | 51.0 | — | 31.5 |
| TerminalBench | Inhouse Framework (Acc) | 30.0 | — | — | 35.5 | 43.2 | 8.3 |
| TerminalBench | Terminus (Acc) | 25.0 | 16.3 | 6.6 | — | — | 30.3 |
| Aider-Polyglot | Acc | 60.0 | 55.1 | 61.8 | 56.4 | 70.7 | 52.4 |
| Tool Use Tasks | |||||||
| Tau2 retail | Avg@4 | 70.6 | 69.1 | 57.0 | 75.0 | 81.8 | 74.8 |
| Tau2 airline | Avg@4 | 56.5 | 39.0 | 26.5 | 55.5 | 60.0 | 54.5 |
| Tau2 telecom | Avg@4 | 65.8 | 32.5 | 22.1 | 45.2 | 57.0 | 38.6 |
| AceBench | Acc | 76.5 | 72.7 | 70.5 | 76.2 | 75.6 | 80.1 |
| Math & STEM Tasks | |||||||
| AIME 2024 | Avg@64 | 69.6 | 59.4 | 40.1 | 43.4 | 48.2 | 46.5 |
| AIME 2025 | Avg@64 | 49.5 | 46.7 | 24.7 | 33.1 | 33.9 | 37.0 |
| MATH-500 | Acc | 97.4 | 94.0 | 91.2 | 94.0 | 94.4 | 92.4 |
| HMMT 2025 | Avg@32 | 38.8 | 27.5 | 11.9 | 15.9 | 15.9 | 19.4 |
| CNMO 2024 | Avg@16 | 74.3 | 74.7 | 48.6 | 60.4 | 57.6 | 56.6 |
| PolyMath-en | Avg@4 | 65.1 | 59.5 | 51.9 | 52.8 | 49.8 | 54.0 |
| ZebraLogic | Acc | 89.0 | 84.0 | 37.7 | 73.7 | 59.3 | 58.5 |
Base model evaluation results from the model card
| Benchmark | Metric | Shot | Kimi K2 Base | Deepseek-V3-Base | Qwen2.5-72B | Llama 4 Maverick |
|---|---|---|---|---|---|---|
| General Tasks | ||||||
| MMLU | EM | 5-shot | 87.8 | 87.1 | 86.1 | 84.9 |
| MMLU-pro | EM | 5-shot | 69.2 | 60.6 | 62.8 | 63.5 |
| MMLU-redux-2.0 | EM | 5-shot | 90.2 | 89.5 | 87.8 | 88.2 |
| SimpleQA | Correct | 5-shot | 35.3 | 26.5 | 10.3 | 23.7 |
| TriviaQA | EM | 5-shot | 85.1 | 84.1 | 76.0 | 79.3 |
| GPQA-Diamond | Avg@8 | 5-shot | 48.1 | 50.5 | 40.8 | 49.4 |
| SuperGPQA | EM | 5-shot | 44.7 | 39.2 | 34.2 | 38.8 |
| Coding Tasks | ||||||
| LiveCodeBench v6 | Pass@1 | 1-shot | 26.3 | 22.9 | 21.1 | 25.1 |
| EvalPlus | Pass@1 | - | 80.3 | 65.6 | 66.0 | 65.5 |
| Mathematics Tasks | ||||||
| MATH | EM | 4-shot | 70.2 | 60.1 | 61.0 | 63.0 |
| GSM8k | EM | 8-shot | 92.1 | 91.7 | 90.4 | 86.3 |
| Chinese Tasks | ||||||
| C-Eval | EM | 5-shot | 92.5 | 90.0 | 90.9 | 80.9 |
| CSimpleQA | Correct | 5-shot | 77.6 | 72.1 | 50.5 | 53.5 |
Capabilities
Sampling controls: temperature, top_p, top_k, max_tokens, frequency_penalty, presence_penalty, repetition_penalty.
Pricing on Gizmo
These are provider baseline rates before Gizmo’s 5% Free-plan or 4% paid-plan fee. Your included usage covers charges first; overage uses prepaid credits. See the fee-inclusive comparison above.
Provider baseline rates
- Input
- $0.57 / 1M
- Output
- $2.30 / 1M
Examples before the platform fee
- Typical chat turn
- $0.0023 2k in · 500 out
- $1 of input
- ≈ 1.75M tokens
- $1 of output
- ≈ 435k tokens
- Full context, once
- $0.0747
Providers and pricing
One way to run Kimi K2 0711 on Gizmo.
| Provider | Route | Input / 1M | Output / 1M | Context | Uptime 24h |
|---|---|---|---|---|---|
| Novita · fp8Lowest price | OpenRouter | $0.57 | $2.30 | 131k | 100% |
Rates are each provider’s, per million tokens, before Gizmo’s 5% (Free) or 4% (paid) fee. “Cheapest” routing starts at the top of this list; “Fastest” starts with the model’s maker.
More from Moonshot AI
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