K3 weights went open in July and K3.1 is rumored to follow, so I wanted to know how it behaves as an agent before anyone tries to run it at home. I gave K3.1 (API for now) and GPT-6 Astra the same one-shot task and let each run alone until it decided it was done: a 28 s Avatar-style dragon flight in Three.js, six camera shots, one HTML file, every mesh and texture in code, deterministic setTime() for frame-by-frame recording. One run each, no human in the loop. Numbers Metric Kimi K3.1 GPT-6 Astra Wall time 12:28 9:17 Agent steps 20 35 Tool calls 23 35 Prompt tokens read 725K 1,209K Cache hits 94% 97% Output tokens 49.2K 22.2K Reasoning tokens 27.7K 1.7K Final file 746 lines 217 lines Cost (API) ~$1.1 to $1.4, est. ~$2.63 Why the shape matters for local K3.1 reasons a lot and calls tools rarely. 56% of its output was reasoning, ~37 s per step, and it wrote the scene in a few big writes. Astra barely reasoned and made many small moves. Fewer steps means less prompt to reread. Every agent step resends the growing context. K3.1 read 725K prompt tokens over the run, Astra 1.2M. On a local box that is prefill time: with a hit rate like these you still pay for the uncached tail and every cache miss, so a low-step model is friendlier to prefill-bound hardware. But it is decode-heavy. 49K generated tokens, more than twice Astra's. On a big MoE at home, decode speed is what will decide whether a run like this takes 15 minutes or an hour. What went wrong (agent side, not the models) K3.1 only accepts temperature: 1. The agent sent 0.2, so I forced 1 for the main calls, but the image-review tool kept the old value. Both of K3.1's attempts to look at its own screenshots failed and it shipped blind; one 2 s sunrise moment renders as a flat teal frame. Astra reviewed its screenshots four times and fixed things after each. Astra fills every optional tool argument with zeros ("wait":0,"kill":0). The shell tool read that as two modes at once and rejected 29 calls in a row, killing the first run in 2.5 minutes. Fixed and rerun; the table is from the rerun. If you plan to run K3.1 locally as an agent: pin temperature to 1 everywhere your stack makes its own requests (vision, summaries, sub-calls), not just the main chat call. Caveats: one run per model; K3.1 has no public price, cost estimated from K3 Moonshot rates; Astra at OpenRouter list price. Ran in Atomic Agent, an open source agent I work on. Happy to share traces.   submitted by   /u/GapNew4766 [link]   [comments]