Moonshot AI’s New Release Sits Just Behind Top Anthropic Models

Moonshot AI has rolled out Kimi K3.1 Pro, a new post-trained reasoning model that immediately ranks fourth on the Artificial Analysis Intelligence Index with a score of 55. This result places the tool only three points behind Claude Opus 5.5. The only models scoring higher are Claude Opus 5.5 (58), Claude Sonnet 5.5 (56), and Muse Wonder Full (56). The release marks an 11-point jump over the previous K3 version.

The timeline for this development starts with the predecessor, Kimi K3. To reach the current iteration, Moonshot applied significantly more post-training compute to the base model. This process culminated in the release of K3.1 Pro on October 23, 2026, alongside a variant named K3.1 Pro Highspeed, which the company claims runs two to three times faster.

Both models are already accessible through Kimi.ai, Kimi Work, Kimi Code, and the Kimi API. Moonshot plans to release the model weights by November 4, 2026. Should that plan hold, K3.1 Pro would become the highest-scoring open-weights model available. At that point, the gap between open and proprietary models would shrink from 12 points to just 3, assuming other models do not improve first.

The strongest gains appear in agentic tasks. On the GDPval-AA benchmark, K3.1 Pro reaches 1,846 Elo according to Artificial Analysis, which is 312 points higher than K3. This score is just behind Claude Opus 5.5 at 1,866 and Muse Wonder Full at 1,857. On Terminal-Bench 4.0, Moonshot reports a 65.7 percent success rate, surpassing GPT-6 Astra at 58.2 percent and falling just short of Claude Opus 5.5 at 66.4 percent. The previous K3 model recorded only 13 percent on that test.

Hallucination rates have also fallen sharply. On Moonshot's internal Kimi Hallu Bench Hard stress test, claim-level hallucinations dropped from 23.4 percent with K3 to 8.3 percent with the new release. While GPT-6 Astra still holds an edge with a 5.5 percent rate on the same test, K3.1 Pro has improved significantly in other areas, including financial tasks. The model gained 7.2 points on Financial Modeling and 11.6 points on Financial Research. For general office tasks, Moonshot says the model tops all tested models on OfficeQA Pro v2.

In 3D modeling and coding, K3.1 Pro works directly with game engines such as Unity, Unreal Engine, and Godot, handling both quick fixes and full project builds. On the BenchCAD benchmark, it scores 92.7 percent with tools, close to Claude Opus 5.5 at 96.2 percent and GPT-6 Astra at 95.9 percent. Without tools, it reaches 72.8 percent, nearly matching Claude Opus 5.5 at 73.0 percent. The company states the model is strongest at parametric modeling of mechanical parts, architectural models, and configurable products. It can write and run scripts for Blender and CAD software without MCP connectors. The company also launched a feature called "3D Make" on Kimi.com that lets users preview, edit, and export 3D models.

Despite the performance gains, the model's dimensions remain the same as K3, with 2.8 trillion total parameters and 104 billion active ones. The context window spans one million tokens, and the model handles both text and images. According to Artificial Analysis, it sits at the top of the Pareto frontier, meaning no model with a comparable parameter count scores higher on the Intelligence Index.

Pricing has decreased alongside these updates. Token prices drop by 33 percent, with input costs falling to $2 per million tokens from $3, output costs to $10 from $15, and cache hits to $0.20 from $0.30. Each Intelligence Index task costs $1.98, almost identical to K3 at $2.00, since the model generates 14 percent more output tokens.

Moonshot has also addressed cybersecurity concerns. The company observed that vulnerability research capabilities grew as post-training scaled up, because cyber-related content was embedded in the general mid-training corpus. For the open-weights release, Moonshot stripped cyber-related data from both training phases. On its internal xdev-bench-hard, the uncleaned version solves 90.5 percent of tasks, while the data-cleaned K3.1 Pro solves 81.0 percent.

Looking ahead, Moonshot intends to release the model weights by November 4, 2026. The company states that no open-weights model should push the absolute frontier of offensive cyber capabilities. At the same time, the company wants to gradually raise what open models can do, since they also serve defensive purposes like auditing legacy systems.