Moonshot
2 items across 1 edition. First seen Sat 24 Oct, last seen Sat 24 Oct.
- Moonshot launched Kimi K3.1 Pro on its API on 23 October and says "Full model weights will be released by Nov 4, 2026". Simon Willison reports pricing of $2.00 per million input tokens and $10 per million output tokens — half the price of Claude Opus 5.5 — with a "Highspeed" variant 2-3x faster at twice the price.
- On Artificial Analysis the model scores 55, ahead of Claude Fable 5.1, GPT-6 Astra and Gemini 4 Argon at 53 and behind Claude Opus 5.5 at 58, according to Willison. The Decoder lists Moonshot's own comparisons against Opus 5.5: Terminal-Bench 4.0 65.7% against 66.4%, GDPval-AA Elo 1,846 against 1,866, HLE-Full with tools 70.0% against 67.7%, GPQA-Diamond 94.2% against 93.9%, and ExploitBench 74.7% against 91.0%.
- The benchmark figures other than the Artificial Analysis score are Moonshot's own and have not been independently verified. The weights are not out yet, so the open-weights claim rests on the company's stated schedule.
- Moonshot says that for the open-weight release "we identified and removed cyber-related data from both training stages", and that "we aim not to release open weights that would extend the absolute frontier of cyber capability". On its internal xdev-bench-hard, a checkpoint without those measures "solves 90.5% of problems at pass@3; the final K3.1 Pro reaches 81.0%". The same chart lists DeepSeek-V4.1-Flash at 85.7, GLM-5.3 at 57.1 and Kimi K3 at 33.3.
- The Decoder quotes Moonshot saying "no open-weights model should push the absolute frontier of offensive cyber capabilities", and separately reports K3.1 Pro at 74.7% on ExploitBench against 91.0% for Claude Opus 5.5. It is the clearest case to date of a Chinese lab deliberately withholding cyber capability from a release it intends to publish as weights.
- Every figure here is Moonshot's own and unverified; xdev-bench-hard is an internal benchmark with no public definition. The weights are not released, so no one outside the company can yet check whether the removal holds once the model is in third-party hands, or whether fine-tuning restores what was stripped.