--- title: What Kimi K3 Costs to Run | daily.dev description: Kimi K3, Moonshot AI's 2.8 trillion parameter open-weights MoE model, requires roughly 1.5 TB of RAM to run inference — about 1.4 TB for weights alone at... canonical: https://daily.dev/posts/what-kimi-k3-costs-to-run-g7siyv512 twitter:card: summary_large_image twitter:site: @dailydotdev og:type: website og:site_name: daily.dev og:title: What Kimi K3 Costs to Run | daily.dev og:description: Kimi K3, Moonshot AI's 2.8 trillion parameter open-weights MoE model, requires roughly 1.5 TB of RAM to run inference — about 1.4 TB for weights alone at... og:url: https://daily.dev/posts/what-kimi-k3-costs-to-run-g7siyv512 og:image: https://api.daily.dev/og/posts/g7siyv512.png og:image:alt: What Kimi K3 Costs to Run og:image:width: 1200 og:image:height: 630 og:locale: en --- > ## Documentation Index > Fetch the complete documentation index at: https://daily.dev/llms.txt > Use this file to discover all available pages before exploring further. # What Kimi K3 Costs to Run **[DigitalOcean Community](https://daily.dev/sources/do_community)** · 9 min read · 0 upvotes · 0 comments ## Summary Kimi K3, Moonshot AI's 2.8 trillion parameter open-weights MoE model, requires roughly 1.5 TB of RAM to run inference — about 1.4 TB for weights alone at native MXFP4 4-bit precision. Running it demands at minimum 8x next-gen GPUs (NVIDIA B300 or AMD MI350X) capable of native FP4 execution, since older Hopper/MI300X hardware dequantizes at runtime and loses the speed benefits. The cost math shows self-hosting on rented GPUs runs ~$38/hr (~$27,800/month), making serverless inference far cheaper for most teams unless they sustain 40+ heavy concurrent users generating 50M+ tokens/month. Key architectural features like Kimi Delta Attention (KDA), Stable LatentMoE, and Attention Residuals improve scaling efficiency ~2.5x over K2. A custom vLLM build with K3-specific code is required for self-hosting. DigitalOcean offers both serverless inference at $3/$15 per 1M tokens and managed GPU options with MI350X and B300 hardware. ## Full article daily.dev links to this article rather than hosting it. Read it at the original source: ## Similar posts on daily.dev - [Why Long-Horizon Agents Break Your Pricing Model and How Kimi K2.6 on DigitalOcean Changes the Math](https://daily.dev/posts/why-long-horizon-agents-break-your-pricing-model-and-how-kimi-k2-6-on-digitalocean-changes-the-math-5w2epivod) · DigitalOcean Community · 0 upvotes · 0 comments - [Moonshot AI’s Kimi K2.7-Code Targets Token Efficiency in Agentic Coding](https://daily.dev/posts/moonshot-ai-s-kimi-k2-7-code-targets-token-efficiency-in-agentic-coding-rpll6qhkm) · DevOps.com · 0 upvotes · 0 comments - [Everyone Read Kimi K3 as a Price War. 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