Kimi K2.6

Released
2026-04-20
Last refreshed
2026-10-08
Status
Researched 110d ago
Open sourceCommercial use: permittedMultimodalCodingRAGAgentsLong contextVisionClassificationJSON / Tool use
Moonshot AI releases · 6 in the last 12 months · this family litChangelog →
Specifications
Family
Kimi K2
Released
2026-04-20
Context
256K
Max output
64K
Parameters
1T
Architecture
Mixture of Experts
Knowledge cutoff
2025-04
Specialization
code
Openness
Open source
License
MITOSI-approvedPermitted
Created by

Lossless long-context AI innovation

Beijing, China
Founded 2023
Website
Pricing
Output / 1M
$3.40
Input / 1M
$0.800

Cheapest of 9 routes · Novita AI

About

Kimi K2.6 is Moonshot AI's multimodal agentic coding model, released April 20 2026 under a Modified MIT license. Built on a 1-trillion-parameter MoE architecture (32B active, 384 experts with 8 selected per token plus 1 shared expert, 61 layers), it features a 262K context window and up to 65,536 output tokens. Supports native image and video inputs (screenshots, PDFs, spreadsheets). Designed for long-horizon coding with agent swarms of up to 300 sub-agents and 4,000 coordinated steps; Moonshot AI cites 200–300 sequential tool calls without task drift.

Top use-case fit: coding, agents, and build tasks

Coding

Q/$ D

Agents

Q/$ C

Providers(9)

Compare all 9

Compare API pricing across 9 tracked provider routes for input and output tokens, batch, and cached reads when available.

ProviderInput / 1MOutput / 1MCacheRoute
Novita AI$0.800$3.40-
Serverless
Moonshot AI Kimi$0.950$4.00read $0.160
Serverless
Cloudflare Workers AI$0.950$4.00read $0.160
Serverless
Fireworks AI$0.950$4.00-
Serverless
OpenRouter$0.950$4.00read $0.160
Serverless
Vercel AI Gateway$0.950$4.00read $0.160
Serverless
Together AI$1.20$4.50read $0.200
Serverless
Microsoft FoundryContact salesContact sales-
Serverless
NVIDIA NIM---
ServerlessPartial

Available via routers & gateways(7)

Capabilities

VisionMultimodalReasoningJSON / Tool useStructured OutputsPrompt Caching

Benchmark peer barsfor Coding

Benchmark scores(17)

Scores are benchmark-specific and are direction-aware: the same numeric gap can mean very different outcomes across suites. Use the leaderboard context and this model's provider route to decide whether the winning margin is meaningful for your workload.
BenchmarkScoreVersionEvaluationSource
80.2SWE-bench VerifiedObserved 2026-04-24—
1462.0—Observed 2026-05-17—
90.5GPQA Diamond (accuracy)Observed 2026-06-07—
84.6From Kimi K2 (accuracy)Observed 2026-06-07—
92.0—Observed 2026-04-29—
58.6SWE-bench Pro (resolved%)Observed 2026-06-07—
89.8—Observed 2026-04-29—
80.1LLM-Stats aggregatorObserved 2026-06-07—
89.6v6Observed 2026-04-20—
66.7Terminal-Bench 2.0 (accuracy%)Observed 2026-06-07—
76.7—Observed 2026-04-20—
96.4AIME 2026 (accuracy)Observed 2026-06-07—
83.2BrowseComp (accuracy%)Observed 2026-06-07—
34.7HLE-Full without tools (accuracy)Observed 2026-06-07—
55.9MCP-Atlas (accuracy%)Observed 2026-06-07—
47.6CursorBench 3.1Observed 2026-06-30
Configuration: Kimi 2.6 (single reported configuration)
Harness: CursorBench 3.1
Evaluator: Cursor
Confidence: confirmed
Notes: Cursor published one CursorBench 3.1 configuration for this model; no cross-effort selection was needed.
4.4xhighObserved 2026-06-30—
Catalog ID
moonshotai/kimi-k2.6

Migration checks

No linked migration route is available for this model yet.

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