Kimi的开放模型K3接近GPT-5.6 Sol和Fable 5，同时标志着超便宜中文AI的终结

Kimi has released K3, a multimodal open-weight model built on a mixture-of-experts architecture with 896 experts, 2.8 trillion parameters, and a context window of one million tokens. Full weights are expected by the end of July. In Kimi's own benchmarks, K3 comes close to Claude Fable 5 and GPT 5.6 Sol but beats all other tested systems by a wide margin. Independent testing by Artificial Analysis largely confirms these results, though K3's hallucination rate increased compared to its predecessor. At $3 per million input tokens and $15 per million output tokens, K3 is much pricier than its predecessor but comparable to Western mid-range models like Sonnet 5. Per-task costs land around $0.94, similar to GPT-5.6 Sol and about half the price of Opus 4.8. Kimi is launching K3, a multimodal model with 2.8 trillion parameters and a context window of one million tokens. In the company's own benchmarks, it performs on par with leading proprietary models. According to Kimi, the new flagship model K3 has 2.8 trillion total parameters, processes images and video natively, and supports a context window of one million tokens. Kimi calls K3 the first open model in the roughly 3 trillion parameter range. Full model weights are scheduled for release by July 27. The model targets long-running programming tasks, knowledge work, and complex reasoning. In Kimi's own benchmarks , K3 still trails the top proprietary models Claude Fable 5 and GPT 5.6 Sol but beats every other system tested, including the Claude Opus models and Chinese rival GLM-5.2. All results come from Kimi and were achieved at maximum or high thinking intensity, according to the company. Ad Across all 35 tests, K3 took first place about seven times and landed second or third in most of the rest. Fable 5 won the most individual tests. In nearly every benchmark, K3 beat Opus 4.8, GPT 5.5, and GLM 5.2 by a wide margin. Depending on the benchmark, one of three agent systems was used: KimiCode, Claude Code, or Codex. That means the results weren't all collected under identical conditions. Ad DEC_D_Incontent-1 Independent testing lab Artificial Analysis has published its first evaluation of Kimi K3. The model scores 57 on the Artificial Analysis Intelligence Index, putting it on par with Opus 4.8 and GPT-5.5 but still behind Fable 5 and GPT-5.6 Sol. That largely lines up with Kimi's own claims. On agentic tasks, K3 reaches an Elo rating of 1,668 on GDPval v2, a big jump from K2.6's 1,190. It beats GLM-5.2 (1,514), GPT-5.5 (1,494), and Claude Opus 4.8 (1,600), though it still falls short of Claude Fable 5 (1,760). K3 also takes the top spot on AutomationBench-AA, Artificial Analysis's version of Zapier's agentic SaaS workflow evaluation, with a score of 53 percent. Ad On AA-Briefcase, a private long-horizon knowledge work evaluation, K3 reaches an overall Elo of 1,547, up 732 points from K2.6. Only Claude Fable 5 scores higher. Artificial Analysis calls K3 well-rounded, with rubric scoring and analytical quality close to Fable 5's level. GPT-5.6 Sol still leads on presentation quality, though. K3's accuracy rate improved from 33 percent to 46 percent on the AA-Omniscience Index, pushing the overall score from +6 to +18. But its hallucination rate climbed from 39 percent to 51 percent, meaning K3 fabricates more answers even as it gets more questions right. Ad DEC_D_Incontent-2 According to Kimi, the model's primary use case is long-running software development with minimal human oversight. K3 is built to analyze large codebases, coordinate terminal tools, and stay focused on a task across many work steps. Ad