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Model details

Kimi K3 (CanopyWave)

Kimi K3 is positioned as a flagship multimodal reasoning model aimed at long-horizon, agentic work rather than routine chat. The model follows Moonshot's K-series lineage and ships in two context variants through Kimi Code: a k3 1M option and a recommended k3-256k option, where the 256k variant delivers equivalent results within its window while consuming roughly half the quota. That tiering lets users pick between full-depth long-context sessions and cheaper everyday coding, code completion, and small-file edits. The launch paired the hosted API with a full open-weight release under a custom Kimi K3 License, so the weights, deployment recipes, and technical report are all available for inspection even though the model is too large for typical local hardware.

Under the hood, K3 is a sparse Mixture-of-Experts network sitting in the three-trillion-parameter class, activating only 16 of 896 routed experts per token, which gives it unusual reach without activating the full parameter budget on every request. Its standout capabilities are the one-million-token context window, native vision, and long-horizon tool use, which together support large-codebase navigation, terminal-driven workflows, screenshot interpretation, and document-heavy research. Reported strengths include a leading blind frontend coding ranking at launch and competitive results across Moonshot's coding and agentic suite, making it a good fit for complex engineering, repository-scale analysis, and visual production work, while cheaper models remain the better choice for high-volume routine traffic.

LLM Gatewaycanopywave/kimi-k3kimi-k3

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LLM Gateway
Model key
canopywave/kimi-k3
Release date
Jul 16, 2026
Last updated
Jul 16, 2026
Input modalities
Output modalities
Capabilities

Cost

Input token cost
$3.00
Output token cost
$15.00

Limits

Output tokens
1,048,576 tokens
Context window
1,048,576 tokens

Transparent token rates

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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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Latest news about Kimi K3 (CanopyWave)

LLM Gateway

CoverageBenchmark

A vLLM engineering blog post dated 2026-09-13 documents Kimi K3 day-0 serving support and a follow-up multi-PR optimization pass covering adaptive speculative-token budgets, internal KDA prefix checkpoints, zero-copy mixed KDA batches, deferred MXFP4 finalization, ReplaySSM, prefill/decode disaggregation, and decode co Measured on a B300 node (CUDA 13.3) at TP8 with an 8K/1K workload and 8-token DSpark speculation, vLLM v0.27.1 vs. commit 82a85dc1 yields 56%–60% lower average latency, 2.2–2.8× throughput, and 72%–85% lower TTFT across concurrency 1, 4, and 16 (e.g., concurrency 16 latency drops from 55.90s to 22.17s and throughput ri

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