AI Model Pricing: Moonshot Cuts Costs as Kimi K3.1 Pro Ranks Fourth

Chinese AI firms have increasingly competed on price and performance to challenge established Western providers. Moonshot AI released Kimi K3.1 Pro on October 23, 2026, a reasoning model that now ranks fourth on the Artificial Analysis Intelligence Index with a score of 55.

The new model represents an 11-point improvement over its predecessor, Kimi K3. It trails only Anthropic's Claude Opus 5.5, which scored 58, and two other systems that scored 56. Moonshot plans to publish the model weights by November 4, 2026. If released on schedule, K3.1 Pro would become the highest-scoring open-weights model available. That move would reduce the performance gap between open and proprietary models from 12 points to 3.

Agentic tasks show the largest gains in the new release. On the GDPval-AA benchmark, K3.1 Pro reached 1,846 Elo. This is 312 points higher than K3 and places the model just behind Claude Opus 5.5 at 1,866 and Muse Wonder Full at 1,857. Moonshot also reports a score of 65.7 percent on Terminal-Bench 4.0. This result exceeds GPT-6 Astra at 58.2 percent and slightly trails Claude Opus 5.5 at 66.4 percent. The previous K3 model managed only 13 percent on that specific test.

The company reports a sharp drop in hallucinations on its internal benchmarks. Claim-level hallucinations fell from 23.4 percent with K3 to 8.3 percent with K3.1 Pro on the Kimi Hallu Bench Hard. Moonshot describes this benchmark as a stress test rather than a measure of general error rates. GPT-6 Astra still leads on that metric at 5.5 percent. In internal finance benchmarks, the model gained 7.2 points on Financial Modeling and 11.6 points on Financial Research. Moonshot states that K3.1 Pro tops all tested models on OfficeQA Pro v2.

API prices for the new model fell by 33 percent. Input tokens cost $2 per million, output tokens cost $10 per million, and cache hits cost $0.20 per million. The model generates 14 percent more output tokens than its predecessor. Consequently, the cost to run each Intelligence Index task is $1.98, nearly identical to K3's cost of $2.00. The architecture remains unchanged from K3, featuring 2.8 trillion total parameters with 104 billion active. The model supports a one-million-token context window and processes both text and images.

Moonshot also included a Highspeed variant that the company says runs two to three times faster. Both versions are available through Kimi.ai, Kimi Work, Kimi Code, and the Kimi API. The new model supports 3D modeling and coding tasks. It works with game engines including Unity, Unreal Engine, and Godot. It can write and run scripts for Blender and CAD software without MCP connectors. On the BenchCAD benchmark, it scores 92.7 percent with tools, compared to 96.2 percent for Claude Opus 5.5 and 95.9 percent for GPT-6 Astra. Without tools, it reaches 72.8 percent, slightly below Claude Opus 5.5 at 73.0 percent.

The technical blog post addresses cybersecurity capabilities in detail. Moonshot states that vulnerability research capabilities grew as post-training compute increased. Cyber-related content was part of the general mid-training corpus and reinforcement learning mix. For the open-weights release, the company removed cyber-related data from both training phases. On the internal xdev-bench-hard, which reproduces recently disclosed vulnerabilities in software such as the Linux kernel, Node.js, and JavaScriptCore, the uncleaned model solved 90.5 percent of tasks. The cleaned model solved 81.0 percent. DeepSeek-V4.1-Flash scored 85.7 percent, while Kimi K3 scored 33.3 percent.

Moonshot argues that no open-weights model should push the absolute frontier of offensive cyber capabilities. The company aims to raise what open models can do gradually because they also support defensive work, such as auditing legacy systems. Anthropic previously demonstrated that even GLM-5.3, which scores 45 on the Artificial Analysis Index, can write exploits at levels close to Claude Mythos.