Kimi's open model K3 nears GPT-5.6 Sol and Fable 5 while signaling the end of super cheap Chinese AI

What happened

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. 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.

K3 is built to analyze large codebases, coordinate terminal tools, and stay focused on a task across many work steps. The model pairs programming with visual feedback: it examines screen captures, modifies code, then checks the visible output. Kimi calls this closed-loop system "Vision in the Loop" and positions it as a foundation for game development, UI design, and CAD.

Why it matters

The model targets long-running programming tasks, knowledge work, and complex reasoning. 2. All results come from Kimi and were achieved at maximum or high thinking intensity, according to the company. 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. 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. Independent testing lab Artificial Analysis has published its first evaluation of Kimi K3. 6 Sol. That largely lines up with Kimi's own claims. 6's 1,190. 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. 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. 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. According to Kimi, the model's primary use case is long-running software development with minimal human oversight.

What to watch

js, WebGPU, and GPU Compute, along with an interactive black hole visualization. For the open-world demo, K3 procedurally generated the environment and used an external tool to create the 3D rider and horse models. Other demos include a simulation of the Long March 10 rocket launch and return, plus a Game Boy Advance emulator. K3 uses a mixture-of-experts architecture that activates only 16 of 896 experts at a time.

3x faster decoding for million-token contexts. "Attention residuals" reportedly boost training efficiency by about 25 percent while adding less than 2 percent in extra compute overhead. 00 with