DeepSeek

Kimi K2.6

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...

Apr 21, 2026 262.1K context 16,384 tokens output
Text Image Tools Structured Output Reasoning

Model Overview

High-signal model metadata in a structured two-column overview table.

Provider

The entity that provides this model.

DeepSeek

Model ID

The routed model identifier exposed by upstream providers.

moonshotai/kimi-k2.6

Input Context Window

The number of tokens supported by the input context window.

262.1K tokens

Maximum Output Tokens

The number of tokens that can be generated by the model in a single request.

16,384 tokens tokens

Open Source

Whether the model's code is available for public use.

Yes

Release Date

When the model was first released.

Apr 21, 2026 1 month ago

Knowledge Cut-off Date

When the model's knowledge was last updated.

Unknown

API Providers

The providers that offer this model. This is not an exhaustive list.

Io Net, Chutes, Cloudflare, Parasail, DeepInfra, Inceptron, Novita, Venice, SiliconFlow, Fireworks, Moonshot AI, WandB, AtlasCloud, AkashML, StreamLake, Nebius, Phala, Together

Modalities

Types of data this model can process.

Text Image Video

What is Kimi K2.6

A fuller summary of positioning, capabilities, and source-specific details for Kimi K2.6.

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...

Capabilities

What Kimi K2.6 supports

RN

Reasoning Controls

OpenRouter lists GPT-5.5 with reasoning support and explicit reasoning-related request parameters.

JSON

Structured Outputs

Structured output settings are exposed through OpenRouter for schema-driven or format-controlled responses.

TL

Tool Calling

Tool invocation and tool selection are supported in the routed OpenRouter interface for this model.

MM

Multimodal I/O

This model accepts text input, image input and returns text output.

CTX

Large Context Window

OpenRouter currently lists a context window of 262.1K with up to 16,384 tokens maximum output tokens.

Pricing for Kimi K2.6

Primary API pricing shown in the same “quick compare” spirit as the reference page.

Price Comparison

Additional usage-cost dimensions synced into the project for this model.

Cache read $0.25
maxTemperature 1
maxResponseSize 16,384 tokens

API Access & Providers

Places where this model is available, based on the synced detail-page metadata.

Io Net Chutes Cloudflare Parasail DeepInfra Inceptron Novita Venice SiliconFlow Fireworks Moonshot AI WandB AtlasCloud AkashML StreamLake Nebius Phala Together

Provider Endpoints

Endpoint-level provider data currently available for this model.

Io Net

Max output: 262,142 1d uptime: 98.5% Supported params: 13 Implicit caching: No

Chutes

Max output: 65,535 1d uptime: 98.6% Supported params: 14 Implicit caching: No

Cloudflare

Max output: 262,144 1d uptime: 93.2% Supported params: 17 Implicit caching: No

Parasail

Max output: 262,144 1d uptime: 95.4% Supported params: 16 Implicit caching: No

DeepInfra

Max output: 16,384 1d uptime: 99.8% Supported params: 17 Implicit caching: No

Inceptron

Max output: 262,144 1d uptime: 98.2% Supported params: 17 Implicit caching: No

Novita

Max output: 262,144 1d uptime: 99.9% Supported params: 15 Implicit caching: No

Venice

Max output: 65,536 1d uptime: 98.3% Supported params: 13 Implicit caching: No

SiliconFlow

Max output: 262,144 1d uptime: 99.8% Supported params: 11 Implicit caching: No

Fireworks

1d uptime: 90.4% Supported params: 17 Implicit caching: No

Moonshot AI

1d uptime: 99.9% Supported params: 10 Implicit caching: No

WandB

Max output: 262,144 1d uptime: 99.9% Supported params: 15 Implicit caching: No

AtlasCloud

Max output: 262,144 1d uptime: 93.3% Supported params: 16 Implicit caching: No

AkashML

Max output: 262,144 1d uptime: 99.2% Supported params: 15 Implicit caching: No

StreamLake

Max output: 256,000 1d uptime: 99.8% Supported params: 10 Implicit caching: No

Nebius

1d uptime: 98.3% Supported params: 12 Implicit caching: No

Phala

Max output: 262,144 1d uptime: 98.0% Supported params: 17 Implicit caching: No

Together

1d uptime: 99.6% Supported params: 16 Implicit caching: No

Resources & Documentation

Official model cards, release notes, docs, and other references synced from the source page.

Community discussion

What people think about Kimi K2.6

Kimi K2.6 discussions are most active in r/LocalLLaMA, r/kimi, r/opencodeCLI. Top Reddit threads cluster around benchmark and model-comparison threads, coding workflow discussions, mixed hands-on reactions.

The strongest match in this snapshot has 1502 upvotes and 429 comments.

r/windsurf 9 upvotes 12 comments May 9, 2026
Is Kimi K2.6 really that good?

I’d like to know what your experience has been with the Kimi K2.6 model. In my experience as a free user, K2.6 feels better and more accurate than GPT-5.2 Low Thinking and GLM-5.1.

Is that really the case? And, are Sonnet 4.6 and Opus 4.6/4.7 even better?

Open Reddit thread
r/ClaudeCode 5 upvotes 48 comments April 23, 2026
Kimi K2.6 is NOT an Opus replacement or alternative

I ran out of usage pretty fast this week due to some pretty dense design work, so I've been messing around with K2.6 after backing up my files. It's nowhere near as intelligent or capable as Opus 4.6, I even took the time to optimize for it and create specific rules and .mds so it can operate better at a core level. It's unable to operate in an already established system with clear rules and files to instruct it on how it works to read and that it reads every session start.

It CANNOT understand and work with the system and constantly forgets parts of it. It can't fix simple code and system problems without 10 different iterations.

It is pretty good at visual analysis, better than opus imo. It's analysis of youtube videos and animations and images is way better.

Kimi lacks design taste and that robust reasoning system and eloquent outputs, and anthro hidden files touch that make Opus feel amazing to use sometimes. I've been fighting with Kimi pretty much since I downloaded it.

I will only be using it for sub agents and specific research work.

I am using Ollama cloud btw

Open Reddit thread

I’ve been using Kimi K2.6 on opencode go and I’m really pleased with the results, but since they removed the generous 3x limits, I guess it’s time to look for an alternative provider.

I tried DeepSeek V4 Flash, but it can’t process images and honestly isn’t on Kimi K2.6’s level. What other options do I have now?

I checked Kimi’s $19 Moderato plan, but the limits seem pretty low, and people on the Kimi sub have been complaining about it.

I’ve also seen people recommending Ollama Cloud’s $20 plan. What do you guys think? Could I get away with it if I mainly use only Kimi K2.6 on Ollama Cloud?

Open Reddit thread
r/LocalLLaMA 1,247 upvotes 366 comments April 21, 2026
Kimi K2.6 is a legit Opus 4.7 replacement

After testing it and getting some customer feedback too, its the first model I'd confidently recommend to our customers as an Opus 4.7 replacement.

It's not really better than Opus 4.7 at anything, but, it can do about 85% of the tasks that Opus can at a reasonable quality, and, it has vision and very good browser use.

I've been slowly replacing some of my personal workflows with Kimi K2.6 and it works surprisingly well, especially for long time horizon tasks.

Sure the model is monstrously big, but I think it shows that frontier LLMs like Opus 4.7 are not necessarily bringing anything new to the table. People are complaining about usage limits as well, it looks like local is the way to go.

Open Reddit thread
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