Kimi K3.1 Pro

Moonshot AI has released the Kimi K3.1 series, with Kimi K3.1 Pro Highspeed now available on Amazon Bedrock. Built on the same 3T-class open-weight architecture and 1-million-token context window as Kimi K3, it was post-trained with substantially more compute to target long-horizon agentic work, reduce factual errors, and improve professional tasks such as financial modeling, office documents, and coding for game engines, 3D scenes, and CAD scripts. The Highspeed variant delivers 2-3x the output speed of K3.1 Pro and reuses the same endpoints and APIs, so developers can switch by changing the model ID.

Google has published the first Android Bench results for Kimi K3.1 Pro and DeepSeek V4.1 Flash, with Kimi reaching a 24.0% pass rate above Claude and Gemini entries while DeepSeek delivers strong cost efficiency at $9.9 per run. The benchmark targets real Android engineering tasks, giving developers a quantified reference for long-horizon agent capability.

Tsinghua University and Moonshot AI released TCSExam, a 100-task expert-reviewed benchmark spanning Lean theorem proving, solver engineering, record-setting constructions, and 30 open conjectures, with every submission verified by the Lean kernel or a task checker. GPT-6 Astra fully proved 70.0% of theorems without supplied lemmas, versus 38.3% for Kimi K3.1 Pro and at most 11.7% for six other agents, yet the same model solved none of the 30 open TCS conjectures; the few accepted conjecture submissions merely adapted counterexamples and proofs OpenAI had already published.