Where is the Kimi K2.6 documentation?

The Kimi K2.6 documentation on OpenRouter includes the LLM Quantization: What fp8 and fp4 Do to Quality and Price blog post. The quickstart covers API keys and your first request, and the API reference lists every parameter.

How much does Kimi K2.6 cost?

Kimi K2.6 costs $0.3895/M input tokens and $1.64/M output tokens, with separate rates for Cache Read at $0.0656/M tokens.

What is the context length of Kimi K2.6?

Kimi K2.6 has a 262,144 token context window. It supports up to 262,144 completion tokens.

Does Kimi K2.6 support tool calling and structured outputs?

Yes. Kimi K2.6 accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.

What inputs and outputs does Kimi K2.6 support?

Kimi K2.6 accepts text and images as input and returns text.

Which providers serve Kimi K2.6?

Kimi K2.6 is served by 15 providers on OpenRouter: Baidu Qianfan, Chutes, DigitalOcean, StreamLake, CoreWeave, Crusoe, DeepInfra, Venice and 7 more. Requests are routed to the best available provider, with automatic failover to the others, and you can pin or exclude providers with provider routing.

When was Kimi K2.6 released?

Kimi K2.6 was released on April 20, 2026.

MoonshotAI: Kimi K2.6

moonshotai/kimi-k2.6

Model weights

Compare

Kimi K2.6 is Moonshot AI's next-generation multimodal model, designed for long-horizon coding, coding-driven UI/UX generation, and multi-agent orchestration. It handles complex end-to-end coding tasks across Python, Rust, and Go, and can convert prompts and visual inputs into production-ready interfaces. Its agent swarm architecture scales to hundreds of parallel sub-agents for autonomous task decomposition - delivering documents, websites, and spreadsheets in a single run without human oversight.

Modalities

In / out price

59% off

$0.3895 / $1.64per 1M

Context

262K

Released

Apr 20, 2026

Providers

Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick: Balanced (price + speed), Nitro (fastest), or Floor (cheapest).

Latency / throughput


	$0.65	$3.41	$0.15	0.62s	69 tok/s	99.87%
	$0.75	$3.50	$0.16	0.83s	77 tok/s	99.69%
	$0.39	$1.80	$0.039	1.79s	39 tok/s	99.61%
	$0.95	$4.00	$0.16	1.03s	59 tok/s	100.00%
	$0.70	$3.50	$0.35	0.39s	49 tok/s	99.72%
	$0.57	$2.40	$0.114	0.74s	42 tok/s	100.00%
37% off	$0.95$0.5985	$4.00$2.52	$0.16$0.1008	1.49s	48 tok/s	98.50%
	$0.75	$3.50	$0.16	0.93s	84 tok/s	98.00%
	$0.95	$4.00	$0.16	1.36s	56 tok/s	96.74%
	$0.77	$3.40	$0.14	0.86s	26 tok/s	100.00%
	$0.95	$4.00	$0.16	2.67s	29 tok/s	99.74%
	$0.75	$3.50	$0.15	0.87s	27 tok/s	99.00%
59% off	$0.95$0.3895	$4.00$1.64	$0.16$0.0656	0.66s	82 tok/s	99.85%
	$0.80	$3.40	$0.16	6.56s	17 tok/s	100.00%
	$0.7985	$3.75	$0.19	0.80s	68 tok/s	100.00%

Input $0.65Output $3.41
69 tok/s99.87% uptime
Input $0.75Output $3.50
77 tok/s99.69% uptime
Input $0.39Output $1.80
39 tok/s99.61% uptime
Input $0.95Output $4.00
59 tok/s100.00% uptime
Input $0.70Output $3.50
49 tok/s99.72% uptime
Input $0.57Output $2.40
42 tok/s100.00% uptime
Input $0.5985Output $2.52
37% off
48 tok/s98.50% uptime
Input $0.75Output $3.50
84 tok/s98.00% uptime
Input $0.95Output $4.00
56 tok/s96.74% uptime
Input $0.77Output $3.40
26 tok/s100.00% uptime
Input $0.95Output $4.00
29 tok/s99.74% uptime
Input $0.75Output $3.50
27 tok/s99.00% uptime
Input $0.3895Output $1.64
59% off
82 tok/s99.85% uptime
Input $0.80Output $3.40
17 tok/s100.00% uptime
Input $0.7985Output $3.75
68 tok/s100.00% uptime

Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Weighted average

Input

$0.3677/M tokens

Output

$3.205/M tokens

Kimi K2.6 — Price history

Price history

No effective price data for this selection

$0.181	$1.64	64.4%	17.6%
$0.277	$1.80	32.1%	2.9%
$0.279	$3.50	78.5%	9.7%
$0.301	$2.40	58.9%	1.8%
$0.369	$4.00	73.6%	5.4%
$0.391	$3.41	51.7%	27.5%
$0.401	$3.50	85.4%	13.1%
$0.413	$3.40	56.6%	0.4%
$0.468	$2.52	26.2%	0.5%
$0.504	$4.00	56.4%	4.8%
$0.526	$3.50	38.0%	5.4%
$0.537	$3.40	41.1%	0.8%
$0.567	$3.75	38.0%	6.1%
$0.576	$3.50	29.6%	3.9%
$0.792	$4.00	19.9%	0.2%

Effective in $0.181Effective out $1.64
Token share
17.6%
Effective in $0.277Effective out $1.80
Token share
2.9%
Effective in $0.279Effective out $3.50
Token share
9.7%
Effective in $0.301Effective out $2.40
Token share
1.8%
Effective in $0.369Effective out $4.00
Token share
5.4%
Effective in $0.391Effective out $3.41
Token share
27.5%
Effective in $0.401Effective out $3.50
Token share
13.1%
Effective in $0.413Effective out $3.40
Token share
0.4%
Effective in $0.468Effective out $2.52
Token share
0.5%
Effective in $0.504Effective out $4.00
Token share
4.8%
Effective in $0.526Effective out $3.50
Token share
5.4%
Effective in $0.537Effective out $3.40
Token share
0.8%
Effective in $0.567Effective out $3.75
Token share
6.1%
Effective in $0.576Effective out $3.50
Token share
3.9%
Effective in $0.792Effective out $4.00
Token share
0.2%

Performance

Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).

Throughput

84tok/s

P50, best across providers

Latency

0.39s

P50, best provider

Latency / throughput

AutoExacto benchmarks

GPQA DiamondTAU-BenchDigitalOcean90.0%75.8%Inceptron91.7%73.6%AtlasCloud87.2%77.3%Phala90.7%73.4%Cloudflare90.5%73.5%

+12 more providers

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Uptime (3d)

100.00%

Availability (3d)

99.76%

Availability over the last 3 days

Last 72 hours

Availability 99.76%

3 Days Ago2 Days AgoYesterdayNow

Availability over the last 24 hours

OpenRouter Availability

99.85%

Without Routing

94.61%

When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and provider routing options.

Benchmarks

Scores on standardized evaluations and this model’s own outputs on shared benchmark prompts. Higher percentages are better — and each rank shows where this model lands among the models evaluated on that source.

Benchmark score summary for MoonshotAI: Kimi K2.6 (Artificial Analysis, Design Arena and Vals AI)
Source	Benchmark	Score
Artificial Analysis	Kimi K2.6 (Reasoning) Coding Index	61.8
Artificial Analysis	Kimi K2.6 (Reasoning) Agentic Index	20.5
Artificial Analysis	Kimi K2.6 (Reasoning) GPQA Diamond	91.1%
Artificial Analysis	Kimi K2.6 (Reasoning) HLE	37.5%
Artificial Analysis	Kimi K2.6 (Reasoning) IFBench	76.0%
Artificial Analysis	Kimi K2.6 (Reasoning) τ²-Bench Telecom	95.9%
Artificial Analysis	Kimi K2.6 (Reasoning) AA-LCR	81.0%
Artificial Analysis	Kimi K2.6 (Reasoning) τ-Bench Banking	23.3%
Artificial Analysis	Kimi K2.6 (Reasoning) GDPval-AA	27.3%
Artificial Analysis	Kimi K2.6 (Reasoning) CritPt	8.0%
Artificial Analysis	Kimi K2.6 (Reasoning) SciCode	51.5%
Artificial Analysis	Kimi K2.6 (Reasoning) Terminal-Bench Hard	43.9%
Artificial Analysis	Kimi K2.6 (Reasoning) Terminal-Bench 4.0	0.5%
Artificial Analysis	Kimi K2.6 (Reasoning) Terminal-Bench 2.1	65.9%
Artificial Analysis	Kimi K2.6 (Non-reasoning) GPQA Diamond	78.8%
Artificial Analysis	Kimi K2.6 (Non-reasoning) HLE	19.6%
Artificial Analysis	Kimi K2.6 (Non-reasoning) IFBench	44.3%
Artificial Analysis	Kimi K2.6 (Non-reasoning) τ²-Bench Telecom	93.9%
Artificial Analysis	Kimi K2.6 (Non-reasoning) AA-LCR	69.7%
Artificial Analysis	Kimi K2.6 (Non-reasoning) CritPt	1.4%
Artificial Analysis	Kimi K2.6 (Non-reasoning) Terminal-Bench Hard	37.9%
Design Arena	Kimi K2.6 Agents Arena Agenticgamedev Elo	1084
Design Arena	Kimi K2.6 Agents Arena Agentichtmlslides Elo	1248
Design Arena	Kimi K2.6 Agents Arena Agenticslides Elo	1187
Design Arena	Kimi K2.6 Agents Arena Agenticslides(Html) Elo	1252
Design Arena	Kimi K2.6 Agents Arena Agenticslides(Python-Pptx) Elo	1186
Design Arena	Kimi K2.6 Agents Arena Androidnative Elo	1152
Design Arena	Kimi K2.6 Agents Arena Full Stack Elo	1128
Design Arena	Kimi K2.6 Agents Arena Godotgamedev Elo	1100
Design Arena	Kimi K2.6 Agents Arena Htmlslides Elo	1080
Design Arena	Kimi K2.6 Agents Arena Mobile Apps Elo	1147
Design Arena	Kimi K2.6 Agents Arena Pptxslides Elo	1181
Design Arena	Kimi K2.6 Agents Arena Python-Pptxslides Elo	1180
Design Arena	Kimi K2.6 Agents Arena Python-Pptxslides Elo	1095
Design Arena	Kimi K2.6 Agents Arena Spreadsheet Elo	1276
Design Arena	Kimi K2.6 Agents Arena Webapps Elo	1268
Design Arena	Kimi K2.6 Models Arena 3D Elo	1247
Design Arena	Kimi K2.6 Models Arena Asciiart Elo	1152
Design Arena	Kimi K2.6 Models Arena Code Categories Elo	1262
Design Arena	Kimi K2.6 Models Arena Data Visualization Elo	1246
Design Arena	Kimi K2.6 Models Arena Game Development Elo	1239
Design Arena	Kimi K2.6 Models Arena SVG Elo	1170
Design Arena	Kimi K2.6 Models Arena UI Component Elo	1257
Design Arena	Kimi K2.6 Models Arena Website Elo	1263
Vals AI	Kimi K2.6 CaseLaw v2	61.2%
Vals AI	Kimi K2.6 Code Migration	27.8%
Vals AI	Kimi K2.6 CorpFin v2	66.7%
Vals AI	Kimi K2.6 EMB	57.9%
Vals AI	Kimi K2.6 Finance Agent (v2)	44.9%
Vals AI	Kimi K2.6 GPQA Diamond	89.1%
Vals AI	Kimi K2.6 Harvey's Legal Agent Benchmark v1	1.7%
Vals AI	Kimi K2.6 LiveCodeBench	86.8%
Vals AI	Kimi K2.6 LegalBench	84.7%
Vals AI	Kimi K2.6 Legal Research Bench	15.9%
Vals AI	Kimi K2.6 MedCode	40.1%
Vals AI	Kimi K2.6 MedScribe	78.1%
Vals AI	Kimi K2.6 MMLU Pro	87.6%
Vals AI	Kimi K2.6 MMMU Pro	86.3%
Vals AI	Kimi K2.6 MortgageTax	65.8%
Vals AI	Kimi K2.6 ProgramBench	0.0%
Vals AI	Kimi K2.6 ProofBench v1	16.0%
Vals AI	Kimi K2.6 Public Benefits Bench v1.1	56.6%
Vals AI	Kimi K2.6 SAGE v1	50.2%
Vals AI	Kimi K2.6 SWE-bench	76.2%
Vals AI	Kimi K2.6 Tax Agent Bench	12.4%
Vals AI	Kimi K2.6 TaxEval v2	74.7%
Vals AI	Kimi K2.6 Terminal-Bench 2.1	53.6%
Vals AI	Kimi K2.6 Vals Index	43.5%
Vals AI	Kimi K2.6 Vals Multimodal Index	56.4%
Vals AI	Kimi K2.6 Vibe Code Bench v1.1	37.9%

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

OpenHands

AI coding agent that can run commands, browse the web, call APIs

58.5Btokens

There are many coding agents, but this one is yours.

52.1Btokens

Hermes Agent

Hermes Agent is an open-source, self-improving AI agent by Nous Research that runs persistently with memory across sessions, and builds reusable skills from experience. It comes with 40+ built-in tools, including web search, browser automation, and vision, plus scheduled automations and subagents.

17.8Btokens

OpenClaw

OpenClaw is an open-source AI agent that connects to your messaging apps and takes real actions on your behalf, from running commands and browsing the web to managing files and sending emails.

12.8Btokens

Namazu Data Factory

new

9.68Btokens

Rest of OpenRouter

6.62B

Top 5 Apps

4.16B

MoonshotAI: Kimi versions

Available through EU in-region routing

MoonshotAI: Kimi K2.6 is available through EU in-region routing. Requests sent to eu.openrouter.ai are decrypted in the EU and routed only to shared provider endpoints in Europe (the EU/EEA, the UK, and Switzerland).

Providers in Europe

Inceptron

Prices in Europe

Inceptron: $0.7985/M tokens input, $3.75/M tokens output

Base URL

https://eu.openrouter.ai/api/v1

Plan

Requires Business or Enterprise. Self-serve on Business: no contract, no monthly minimum. OpenRouter Business for EU in-region routing

Fails closed: if no shared provider endpoint in Europe is available, the request errors instead of leaving the region. Requests served by your own BYOK key go to your deployment’s region, which you control. In-region routing docs

More models from moonshotai

Kimi K3.1 Pro

Kimi K3.1 Pro is Moonshot AI's flagship open-weight multimodal reasoning model and a post-trained successor to Kimi K3, with a 1M-token context window. It is built for long-horizon coding, 3D creation, financial research, and end-to-end agentic knowledge work, with native image and video understanding.

Text1.0M context$0.2375 / $8.411

Kimi K3.1 Pro (batch)

Text1.0M context$0.70 / $6

Kimi K3

Kimi K3 is a 2.8T parameter open-weight multimodal reasoning model from Moonshot AI. It is suited for complex coding, knowledge work, and long-horizon agentic workflows, and is particularly strong at navigating large repositories, using tools, debugging, and iterating against images, logs, tests, and runtime feedback. Its architecture uses KDA and Attention Residuals for computational efficiency.

Text1.0M context$0.1824 / $11.01

Kimi K3 (batch)

Text1.0M context$2.28 / $11.40

Kimi K2.7 Code

MoonshotAI: Kimi K2.7 Code is a coding-focused model in Moonshot AI's Kimi K2 family, built to complete end-to-end programming tasks reliably over long contexts. It uses a native multimodal mixture-of-experts architecture that accepts text and image input, and it always operates in a thinking mode, preserving full reasoning content across multi-turn conversations. With a 256K-token context window, it targets long-horizon coding, agentic task decomposition, and multi-turn dialogue. The model activates 32B parameters out of roughly 1T total.

Text262K context$0.60 / $3

Kimi Latest

This model always redirects to the latest model in the Kimi family.

Text262K context

Kimi K2.6

Text262K context$0.3895 / $1.64

Kimi K2.5

Kimi K2.5 is Moonshot AI's native multimodal model, delivering state-of-the-art visual coding capability and a self-directed agent swarm paradigm. Built on Kimi K2 with continued pretraining over approximately 15T mixed visual and text tokens, it delivers strong performance in general reasoning, visual coding, and agentic tool-calling.

Text262K context$0.49 / $2.50

Kimi K2 Thinking

Kimi K2 Thinking is Moonshot AI’s most advanced open reasoning model to date, extending the K2 series into agentic, long-horizon reasoning. Built on the trillion-parameter Mixture-of-Experts (MoE) architecture introduced in Kimi K2, it activates 32 billion parameters per forward pass and supports 256 k-token context windows. The model is optimized for persistent step-by-step thought, dynamic tool invocation, and complex reasoning workflows that span hundreds of turns. It interleaves step-by-step reasoning with tool use, enabling autonomous research, coding, and writing that can persist for hundreds of sequential actions without drift.

It sets new open-source benchmarks on HLE, BrowseComp, SWE-Multilingual, and LiveCodeBench, while maintaining stable multi-agent behavior through 200–300 tool calls. Built on a large-scale MoE architecture with MuonClip optimization, it combines strong reasoning depth with high inference efficiency for demanding agentic and analytical tasks.

Text262K context$0.60 / $2.50

Kimi K2 0905

Kimi K2 0905 is the September update of Kimi K2 0711. It is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. It supports long-context inference up to 256k tokens, extended from the previous 128k.

This update improves agentic coding with higher accuracy and better generalization across scaffolds, and enhances frontend coding with more aesthetic and functional outputs for web, 3D, and related tasks. Kimi K2 is optimized for agentic capabilities, including advanced tool use, reasoning, and code synthesis. It excels across coding (LiveCodeBench, SWE-bench), reasoning (ZebraLogic, GPQA), and tool-use (Tau2, AceBench) benchmarks. The model is trained with a novel stack incorporating the MuonClip optimizer for stable large-scale MoE training.

Text262K context$0.60 / $2.50

Kimi K2 0711

Kimi K2 Instruct is a large-scale Mixture-of-Experts (MoE) language model developed by Moonshot AI, featuring 1 trillion total parameters with 32 billion active per forward pass. It is optimized for agentic capabilities, including advanced tool use, reasoning, and code synthesis. Kimi K2 excels across a broad range of benchmarks, particularly in coding (LiveCodeBench, SWE-bench), reasoning (ZebraLogic, GPQA), and tool-use (Tau2, AceBench) tasks. It supports long-context inference up to 128K tokens and is designed with a novel training stack that includes the MuonClip optimizer for stable large-scale MoE training.

Text131K context$0.57 / $2.30

Kimi Dev 72B

Kimi-Dev-72B is an open-source large language model fine-tuned for software engineering and issue resolution tasks. Based on Qwen2.5-72B, it is optimized using large-scale reinforcement learning that applies code patches in real repositories and validates them via full test suite execution—rewarding only correct, robust completions. The model achieves 60.4% on SWE-bench Verified, setting a new benchmark among open-source models for software bug fixing and code reasoning.

Text131K context

Kimi VL A3B Thinking

Kimi-VL is a lightweight Mixture-of-Experts vision-language model that activates only 2.8B parameters per step while delivering strong performance on multimodal reasoning and long-context tasks. The Kimi-VL-A3B-Thinking variant, fine-tuned with chain-of-thought and reinforcement learning, excels in math and visual reasoning benchmarks like MathVision, MMMU, and MathVista, rivaling much larger models such as Qwen2.5-VL-7B and Gemma-3-12B. It supports 128K context and high-resolution input via its MoonViT encoder.

Text131K context

Moonlight 16B A3B Instruct

Moonlight-16B-A3B-Instruct is a 16B-parameter Mixture-of-Experts (MoE) language model developed by Moonshot AI. It is optimized for instruction-following tasks with 3B activated parameters per inference. The model advances the Pareto frontier in performance per FLOP across English, coding, math, and Chinese benchmarks. It outperforms comparable models like Llama3-3B and Deepseek-v2-Lite while maintaining efficient deployment capabilities through Hugging Face integration and compatibility with popular inference engines like vLLM12.

Text8K context

MoonshotAI: Kimi K2.6

Providers