Kimi K3
Kimi K3 is Moonshot AI's July 2026 flagship multimodal model for long-horizon coding, knowledge work, and reasoning. It is available through Kimi products and the Kimi API under the kimi-k3 model ID, while the full model weights are scheduled for release by July 27, 2026.
Kimi K3 matters because it combines a very large sparse Mixture-of-Experts architecture, native vision, a 1-million-token context window, and a currently callable API. Its delayed weight release also makes availability easy to misread: API access is live, but local or third-party deployment claims should wait for the published weights and technical artifacts.
Moonshot AI's launch blog provides the model architecture, availability, context window, API model ID, pricing, benchmark methodology, and weight-release timeline. The Kimi API platform independently lists the live K3 service and Chinese-market pricing. Reddit discussions are useful for questions about local deployment scale, provider availability, cost, and comparisons, but they are not used as authority for model specifications or benchmark claims.
- Run long-horizon coding and software-engineering tasks through Kimi Code or the Kimi API.
- Analyze long documents, repositories, images, and mixed knowledge-work inputs within a 1M-token context.
- Build multimodal agents that combine visual understanding, reasoning, and tool-driven workflows.
- Compare frontier-model quality and task cost using the same harness, tests, and review criteria.
Moonshot AI describes Kimi K3 as a 2.8-trillion-parameter model with native vision and a 1-million-token context window. The architecture combines Kimi Delta Attention, Attention Residuals, and a Stable LatentMoE design that activates 16 of 896 experts. Moonshot positions it for long-horizon coding, knowledge work, and reasoning.
- Architecture: 2.8T total parameters with 16 of 896 experts activated in the sparse MoE design.
- Modalities and context: native vision with a 1-million-token context window.
- Reasoning at launch: max thinking effort is the default, with lower effort modes planned for later updates.
Kimi K3 is available now on Kimi.com, Kimi Work, Kimi Code, and the Kimi API. The official API uses the `kimi-k3` model ID and lists $0.30 per million cache-hit input tokens, $3 per million cache-miss input tokens, and $15 per million output tokens. Moonshot says the full model weights will be released by July 27, 2026, so API availability should not be confused with an already downloadable checkpoint.
The launch table compares Kimi K3 with Claude Fable 5, GPT-5.6 Sol, Claude Opus 4.8, GPT-5.5, and GLM-5.2 across coding, agentic, knowledge, and vision tasks. These are useful vendor-reported launch results, but several rows use different agent harnesses, model settings, internal evaluations, or cited third-party results. Compare Kimi K3 on your own tasks before choosing it as a default model.
Kimi K3 FAQ
Page-level questions for Kimi K3.
Is Kimi K3 available now?+
Yes. Moonshot AI says Kimi K3 is available on Kimi.com, Kimi Work, Kimi Code, and the Kimi API. The API model ID is `kimi-k3`, but availability through another provider should be verified on that provider's current model list.
Is Kimi K3 open weight?+
Moonshot AI presents Kimi K3 as an open 3T-class model, but the launch post says the full model weights will be released by July 27, 2026. Until the checkpoint and license are published, API access is the confirmed way to use the model and local-deployment requirements remain provisional.
How much does the Kimi K3 API cost?+
Moonshot AI lists Kimi K3 at $0.30 per million cache-hit input tokens, $3 per million cache-miss input tokens, and $15 per million output tokens on its international API. The Chinese platform lists separate yuan pricing, and third-party providers may charge different rates.
Can Kimi K3 run locally?+
Not from an official public checkpoint yet. Moonshot AI recommends supernode configurations with at least 64 accelerators for deployment and says the full weights are due by July 27, 2026, so practical local inference guidance should wait for the checkpoint, license, quantizations, and serving support.