Gateway, weights, runtime, hardware
Do not buy hardware from a headline number. Start with the source ledger, separate client, gateway and inference layers, and wait for official weights before sizing a full local runtime.
Page video
The video is paired with page-specific captions so the moving layer explains the same source-backed path as the text.
Do not buy hardware from a headline number. Start with the source ledger, separate client, gateway and inference layers, and wait for official weights before sizing a full local runtime.
Practical entry
Choose the decision you need, then jump to the page that contains the right calculator, checklist or caveat.
Useful interpretation
Every text section is paired with a visual model so the page can be scanned as a decision guide, not just read as an essay.
A local web client, private API gateway, quantized lab runtime and full multi-accelerator inference cluster are different deployment shapes. Decide which data and artifact layers must stay inside your network.
Kimi Linear, Attention Residuals and FlashKDA explain why long-context inference may become practical, but they do not replace the final K3 model card, tokenizer, chat template, license and inference recipe.
When weights appear, check publisher identity, repository path, license, checksums, file list, tokenizer, runtime instructions and reproducible smoke prompts before changing production plans.
Source notes
External references are kept here as source notes. They support the page but do not replace the on-page decision tools.
Use this for model identity, 2.8T scale, KDA, Attention Residuals, native vision, 1M context, and the pending technical report boundary.
Use this to check official repositories and avoid treating third-party Kimi-K3 placeholders as official weights.
Use this to verify whether a Kimi-K3 weight repository appears under the official moonshotai account.
Use this for the high-performance Kimi Delta Attention kernel implementation trail.
Use this for Kimi Delta Attention background, KV-cache efficiency claims, and long-context decoding context.
Use this for Kimi Code model ID, 1M context configuration, and OpenAI/Anthropic compatible coding endpoints.
FAQ
Short answers keep limits, dates and source boundaries explicit.
The source ledger did not find an official Kimi-K3 weight repository in its July 23, 2026 scan, so full local inference should wait for verified artifacts.
A local UI or private gateway can be built first, keeping the backend swappable once official runtime artifacts are verified.
No. It is an architecture implementation trail; the final K3 release still needs model artifacts, license, tokenizer, runtime guidance and sizing evidence.
Next decisions
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