55 Points: Kimi K3.1 Pro Narrows Gap With Top AI Models

Moonshot AI's new Kimi K3.1 Pro model has surged to fourth place on the Artificial Analysis Intelligence Index with a score of 55 points. This performance places it just three points behind the leading proprietary models, signaling a significant shift in the competitive landscape for artificial intelligence.

The release, which launched today, represents a post-trained evolution of the previous Kimi K3 architecture. It utilizes significantly more post-training compute to achieve an 11-point improvement over its predecessor. Only Claude Opus 5.5, Claude Sonnet 5.5, and Muse Wonder Full currently rank higher on the index.

Pricing adjustments accompany the performance gains. While the model maintains the same 2.8 trillion total parameter count as its predecessor, API prices have dropped by 33 percent. Input costs are now $2 per million tokens, down from $3, while output costs stand at $10 per million tokens, reduced from $15. Cache hit costs have also fallen to $0.20 from $0.30.

The model demonstrates substantial improvements in agentic tasks and coding. On the GDPval-AA benchmark, Kimi K3.1 Pro reaches 1,846 Elo, a 312-point increase over the previous version. It also achieves 65.7 percent on Terminal-Bench 4.0, surpassing GPT-6 Astra and coming within 0.7 percent of Claude Opus 5.5.

In the realm of 3D modeling, the system can interact directly with game engines such as Unity, Unreal Engine, and Godot. It scores 92.7 percent on the BenchCAD benchmark when using tools, and 72.8 percent without them. Moonshot has also introduced a feature called 3D Make on Kimi.com, allowing users to preview, edit, and export 3D models.

Moonshot plans to release the model weights by November 4, 2026. If this schedule holds, Kimi K3.1 Pro would become the highest-scoring open-weights model available. This move would narrow the gap between open and proprietary models from 12 points to just 3, assuming no other changes occur in the interim.

The company has also addressed cybersecurity capabilities in its technical documentation. For the open-weights release, Moonshot removed cyber-related data from both training phases to manage offensive potential. On internal tests reproducing disclosed vulnerabilities, the cleaned model solves 81.0 percent of tasks, compared to 90.5 percent for the uncleaned version. A high-speed variant, K3.1 Pro Highspeed, is also available and runs two to three times faster than the standard model.