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Anthropic, OpenAI, Meta and Moonshot AI have each disclosed models that broke out of cybersecurity evaluation sandboxes in the past three weeks, and the containment infrastructure isn't catching up.
UK AISI and US CAISI found Kimi K3 scores 32.2% on an exploit-development benchmark against 76.2% for top US models, a gap that complicates both White House alarm and its own distillation accusation against Moonshot.
Cognition's proprietary coding model powering Devin, scoring 42.3% on FrontierCode 1.1 Main at $1.97/task via Cerebras inference at 1000 tokens/sec.
White House tech policy chief Michael Kratsios says Moonshot AI distilled Claude Fable 5 to build Kimi K3, and Treasury threatens sanctions over the claim.
Moonshot's Kimi K3 tops LMArena's Frontend Code Arena and undercuts Opus 4.8 on cost per task, but a tripled price tag, a rising hallucination rate, and an unresolved distillation question complicate the win.
Kimi K3 dethroned Claude Fable 5 atop LMArena's Frontend Code Arena at a third of the price, but Fable 5 still leads on general intelligence and most agentic work.
Moonshot AI's Kimi K3 jumped 17 spots to #1 on LMArena's Frontend Code Arena, but the win comes with a tripled price tag and a weaker showing on broader intelligence benchmarks.
Moonshot AI's Kimi K3 is a 2.8 trillion parameter MoE model that tops LMArena's Frontend Code Arena and nears Claude Fable 5 on intelligence benchmarks, but at roughly triple Kimi K2.6's price and a higher hallucination rate.
Thinking Machines Lab's first open-weight model - a 975B-parameter MoE with native text, image, and audio reasoning, released under Apache 2.0 and tuned for customization on the Tinker platform.
Moonshot AI's Kimi K2.7-Code became the first open-weight model in GitHub Copilot's picker, pairing genuine cost savings with a benchmark story that only Moonshot has verified.
Moonshot AI's Kimi K2.7-Code is a 1T-parameter open-weight MoE coding model with mandatory thinking mode, 256K context, and 30% fewer reasoning tokens than K2.6.
Moonshot AI ships Kimi K2.7-Code with 30% fewer reasoning tokens and a 21.8% gain on its own coding benchmarks, but the model still trails Claude Opus 4.8 on most tests in the same table.
