Technical Specifications of Kimi K3
| Specification | Kimi K3 |
|---|---|
| Developer | Moonshot AI |
| Model ID | kimi-k3 |
| Model type | Frontier Mixture-of-Experts LLM |
| Total parameters | 2.8 trillion |
| Experts | 896 experts, 16 activated per token |
| Context window | Up to 1,000,000 tokens |
| Native multimodality | Visual understanding; Kimi API docs include image and video input examples |
| Core architecture | Kimi Delta Attention, Attention Residuals, Stable LatentMoE |
| Main use cases | Coding, software engineering, long-context reasoning, agent tasks, knowledge work, visual reasoning |
| Hosted API access | Kimi API Platform, CometAPI |
| Open weights | Scheduled by July 27, 2026 |
What is Kimi K3?
Kimi K3 is Moonshot AI's flagship large language model and currently the company's most capable foundation model. It is designed for professional software engineering, long-context reasoning, autonomous agents, and complex knowledge-intensive tasks. Unlike previous Kimi models, K3 expands the context window to 1 million tokens, enabling repository-scale coding, long document analysis, and multi-step agent workflows.
The model is built on a large-scale Mixture-of-Experts architecture and represents Moonshot's latest frontier model competing with leading proprietary systems from OpenAI and Anthropic.
Main Features of Kimi K3
- 1M-token context window enables reasoning across massive codebases, books, research papers, and enterprise documentation without aggressive chunking.
- Optimized for software engineering with strong performance on repository-level coding, debugging, UI implementation, and agentic development workflows.
- Designed for AI agents capable of long-horizon planning and multi-step task execution instead of isolated prompt completion.
- Reasoning-aware inference supports configurable reasoning effort for complex problem solving.
- K3 introduces two major architectural innovations: Kimi Delta Attention (KDA) for efficient long-sequence processing; Attention Residuals (AttnRes) to improve information retrieval across model depth
- Kimi K3 approximately 2.5× higher scaling efficiency compared with Kimi K2.
- Open-weight release strategy, allowing broader research and deployment compared with closed proprietary frontier models.
Benchmark Performance of Kimi K3
Moonshot released one of the most comprehensive benchmark reports among recent frontier models. Public results indicate Kimi K3 is competitive with leading proprietary systems across software engineering, reasoning, and agent tasks.
| Benchmark | Kimi K3 | GPT-5.6 Sol | Claude Fable 5 | Claude Opus 4.8 |
|---|---|---|---|---|
| TerminalBench 2.1 | 88.3 | 88.8 | 84.6 | 84.6 |
| FrontierSWE | 81.2 | 71.3 | 86.6 | 66.7 |
| ProgramBench | 77.8 | 77.6 | 76.8 | 71.9 |
| SWE Marathon | 42.0 | 39.0 | 35.0 | 40.0 |
| BrowseComp | 91.2 | 90.4 | 88.0 | 84.3 |
| DeepSearchQA | 95.0 | — | 94.2 | 93.1 |
Key observations
- Kimi K3 exceeds GPT-5.6 Sol on FrontierSWE and BrowseComp.
- It ranks among the strongest publicly reported coding models.
- Long-context software engineering is one of its biggest strengths.
- Agent benchmarks place it close to leading proprietary frontier systems, though Moonshot notes the strongest closed models still maintain an overall experience advantage.
Limitations
- Low- and high-reasoning modes are planned but were not available at launch.
- Switching into K3 midway through an existing conversation may reduce answer quality because the model relies on complete reasoning history.
- The model can occasionally be overly proactive when user intent is ambiguous.
- Despite its strong benchmark results, Moonshot explicitly states that K3 does not surpass every proprietary frontier model across all tasks.
Why Use Kimi K3 on CometAPI?
For developers building with multiple foundation models, accessing Kimi K3 through CometAPI offers several operational advantages:
- Unified API endpoint for Moonshot, OpenAI, Anthropic, Google, DeepSeek, and other providers.
- Faster model switching without rewriting application logic.
- Consistent authentication and request formats across providers.
- Simplified billing and centralized usage management.
- Easier evaluation of Kimi K3 against other frontier models within the same infrastructure.
Kimi K3 is especially valuable for organizations that require long-context reasoning, enterprise document intelligence, and advanced coding agents while retaining the flexibility of an open-weight model.