Kimi K3
Kimi K3 publishes its weights, but at 2800B parameters (104B active per token) no consumer machine holds the checkpoint. This page covers the access paths that work and the open models that actually run locally.
Why you can't run Kimi K3 locally
At 2800B parameters (104B active per token), a Q4-class build of Kimi K3 would need roughly 1,680 GB — beyond any consumer machine. That figure is arithmetic, not opinion: 0.6 GB per billion parameters is the standard Q4 rule we apply across the whole catalog. The weights themselves are public (official source linked below); capacity, not licensing, is the wall.
What works instead: the hosted API. For most workloads, the open models below deliver the same job on hardware that fits under a desk.
Jul 2026 open-weight multimodal agentic MoE from Moonshot (weights on HuggingFace). Official checkpoint is far beyond any consumer machine; ollama run kimi-k3:cloud streams it from Ollama Cloud rather than running locally.
What to run locally instead of Kimi K3
More Kimi models
Frequently asked questions
Can I run Kimi K3 locally?
Not on hardware you can buy. The weights are public, but Kimi K3 is a 2800B-parameter model (104B active), and a Q4-class build would need roughly 1,680 GB — beyond any consumer machine. Until the ecosystem ships a smaller official build, the API or a smaller open model is the practical path.
How do I access Kimi K3?
Through the vendor's hosted API. The official source is linked on this page.
What is the best local alternative to Kimi K3?
Qwen3 235B A22B is the strongest local model we track (235B, from 192 GB machines), with Qwen3.5 122B-A10B Instruct close behind. Both run on a single high-memory Mac or GPU — see their pages for exact hardware.
Cite this page
ModelFit: Kimi K3 — specs, memory math and hardware verdicts. https://modelfit.io/models/kimi-k3/ (dataset updated 2026-09-03, CC BY 4.0).