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Open weightsMoonshot AI/10 trustVerified

Kimi-Dev-72B

Moonshot's open SWE agent — large-scale RL on real repos in Docker, 60.4% on SWE-bench Verified at launch.

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About

Kimi-Dev-72B is Moonshot's purpose-built software engineering model, and its training is unusually honest: the model patches real repositories inside Docker containers and only gets rewarded when the entire test suite passes. No partial credit for plausible-looking diffs. That regime, applied at scale on top of a Qwen2.5-72B base mid-trained on 150B tokens of GitHub issues and PR commits, produced the strongest open-source SWE result of its generation.

At release in June 2025 it hit 60.4% on SWE-bench Verified, the best open-source score at the time. It's MIT-licensed on Hugging Face with a 131K context window, which made it an instant default for local coding agents. Later Moonshot releases have pushed past it, but Kimi-Dev remains the clean permissive baseline for agentic software engineering.

Specs

Context window

131K tokens

Pricing

Free / open weights; third-party hosted APIs vary

Free quota

Fully open weights — no official hosted API

API access

No official hosted API — self-host from Hugging Face (moonshotai/Kimi-Dev-72B) or GitHub

Weights

Open weights

Released

Not disclosed

Benchmarks

  • Vendor-reported (HF model card): 60.4% on SWE-bench Verified — SOTA among open-source models at release (June 2025)
  • Based on Qwen2.5-72B, mid-trained on ~150B tokens of GitHub issues and PR commits

Provider-reported unless a source says otherwise. Benchmarks are marketing-adjacent by nature — treat them as directional.

Use cases

software-engineeringcode-reasoningbug-fixingcoding-agents

Trust score — 8/10

/10 trustVerified

Scored 8/10 (TIER verified, metrics-v1). Evidence: Moonshot AI release (June 16 2025) with SWE-bench Verified 60.4% on the HF model card; MIT license confirmed via HF API; open GitHub repo (MoonshotAI/Kimi-Dev); widely benchmarked by the community. Strengths: permissive license, honest RL training regime, strong adoption in local coding agents. Docked for: (1) headline numbers are vendor-reported; (2) superseded by later Moonshot releases. License: MIT.

How the trust score is built

Full methodology →
Adoption · stars/downloads, log-scaled vs peers
8.0/10
Maintenance · recency, releases, issue load
7.0/10
Openness · license + docs
9.0/10
Manual review · sanity read + red-flag check
8.0/10
  • · Moonshot AI; released 2025-06-16
  • · 60.4% SWE-bench Verified (SOTA open at release)
  • · Benchmarks are vendor-reported; superseded by later Moonshot releases

More in the kimi family

Sources