AI Model Timeline

Tracking the accelerating release frequency of frontier AI models.

Kimi K2.6

Moonshot AI·

LLMsopen-weightFrontier

Overview

1T MoE (32B active) open-weight successor to K2.5 with native multimodal vision (MoonViT 400M), 256K context, and agent swarm support for up to 300 sub-agents across 4,000 coordinated steps.

Capabilities and innovations

1T total / 32B active MoE (384 experts, 8 routed + 1 shared)256K context windowNatively multimodal (MoonViT 400M — text, image, video)Agent swarms (300 sub-agents, 4,000 coordinated steps)Long-horizon coding (Rust, Go, Python)Modified MIT licenseMLA (Multi-head Latent Attention)300 Sub-Agent Swarm (up from 100 in K2.5)4,000 Coordinated Tool-Call StepsNative Video Input

Benchmarks

BenchmarkScoreSource
Humanity’s Last Exam (no tools)36.4%vendor
HLE 36.4 no-tools (text-only), recorded for cross-model comparability. Moonshot also reports 54.0 with tools (HLE-Full) and 55.5 with-tools text-only, which are not comparable to the no-tools HLE used here. Corrected from a previously stored with-tools value (54.0).
SWE-bench Verified80.2%unsourced
SWE-bench Pro58.6%unsourced
Terminal-Bench 2.x66.7%unsourced
MMMU-Pro79.4%unsourced

Architecture and hardware

Parameters
1000B total, 32B active per token (MoE)
Estimated VRAM at Q4
~575 GB, Frontier class
Quantization formats
INT4, BF16, GGUF
Recommended runtime
vLLM
License
Modified MIT

Links

More from Moonshot AI

Data curated by AI Model Timeline. See the methodology for admission criteria, benchmark eras and source priority.