Kimi K3.1 Pro Is Here: The 2.8 Trillion-Parameter Open Model That Nearly Matches Claude Opus 5.5

On Thursday, October 23, 2026, China's Moonshot AI launched Kimi K3.1 Pro — and the AI world noticed immediately. This is not a small upgrade. It is a 2.8 trillion-parameter open-weight model that, on Moonshot's own benchmark figures, sits just 0.7 points behind Anthropic's Claude Opus 5.5 on one of the hardest coding-agent tests in the industry — and Moonshot has promised to release the full model weights for free by November 4.

If that promise holds, K3.1 Pro would become the strongest open-weight model anyone can download and run themselves. That is why this launch matters far beyond one company: it moves frontier-class coding and agent capability out of closed labs and into everyone's hands.

Key Takeaways

Moonshot AI launched Kimi K3.1 Pro on October 23, 2026, the first model in its new K3.1 series.

It is a mixture-of-experts model with 2.8 trillion total parameters (104 billion active) and a 1-million-token context window.

On Terminal-Bench 4.0, Moonshot reports 65.7% — ahead of OpenAI's GPT-6 Astra (58.2%) and just behind Claude Opus 5.5 (66.4%).

Independent testing by Artificial Analysis gives it an Intelligence Index score of 55, ranked 4th overall.

The API costs $2 per million input tokens and $10 per million output tokens — 33% cheaper than Kimi K3 — and a faster Highspeed variant runs 2–3x faster.

Full open weights are due by November 4, 2026, which would make it the top open-weight model on the index.

Image: Kimi K3.1 Pro launch artwork (via izz.co.in)

What is Kimi K3.1 Pro?

Kimi K3.1 Pro is not a brand-new base model built from zero. Moonshot describes it as a post-trained version of Kimi K3, pushed through far more reinforcement learning across what the company calls "hundreds of downstream domains." The optimizations touched its reinforcement learning system, long-context inference, and the sandboxes — the isolated environments where agents run code.

The scale is still enormous. A mixture-of-experts architecture means only a fraction of the model's parameters activate for any given token — here, 104 billion active out of 2.8 trillion total. It accepts text and image inputs, and it is live right now in the Kimi app, the Kimi Work desktop app, the Kimi Code coding tool, and the Kimi API, under the model IDs kimi-k3.1-pro and kimi-k3.1-pro-highspeed.

The companion Highspeed variant is worth noting: Moonshot says it delivers the same abilities at two to three times the speed, at $4/$20 per million input/output tokens. For developers running agents in production, speed at that level is often more valuable than a small benchmark edge.

The benchmarks: 0.7 points from the frontier

The headline claim comes from Terminal-Bench 4.0, which tests coding agents on realistic, resource-constrained terminal tasks. Moonshot's own figures put K3.1 Pro at 65.7%, against 66.4% for Claude Opus 5.5 and 58.2% for GPT-6 Astra. Moonshot ran its model in the Claude Code harness and pulled rivals' scores from their published reports or the official leaderboard — so treat these as vendor-reported comparisons, not a neutral head-to-head.

Elsewhere, the gains are real but uneven. On Kimi Code Bench 3.0 (long-horizon tasks), it scores 61.2%, up from K3's 55.95%. On BenchCAD (3D reconstruction via CAD code) with tools, it reaches 92.7%, behind Opus 5.5 (96.2%) and GPT-6 Astra (95.9%). On OfficeQA Pro v2 (office-document work), Moonshot claims a state-of-the-art 64.4. And on Moonshot's own hardest factual-accuracy test, claim-level hallucination errors fell from 23.4% (K3) to 8.3%.

Independent confirmation comes from Artificial Analysis, whose Intelligence Index gives K3.1 Pro a score of 55 — fourth overall, behind only three closed models (Claude Opus 5.5 at 58, Claude Sonnet 5.5 and Muse Wonder Full at 56), and a full 11 points above the old Kimi K3. Artificial Analysis measured Terminal-Bench 4.0 at 67% on its own harness, GDPval-AA at 1,846 Elo, and Humanity's Last Exam at 52%, up from 47% for K3. Its hallucination measurement (44%, down from 53%) is less dramatic than Moonshot's internal test — a useful reminder that different harnesses give different numbers.

The honest caveat: Moonshot's own chart shows K3.1 Pro well behind GPT-6 Astra on science reasoning (Terminal-Bench Science 0.1: 38.1 vs 68.1). This is a coding-and-agents monster, not an all-rounder.

Image: AI coding agent concept (via izz.co.in)

Pricing: 33% cheaper than K3

The API is available today at $2 per million input tokens and $10 per million output tokens (cached input at $0.20) — a third cheaper across the board than Kimi K3. Artificial Analysis estimates a cost of about $2.11 per Intelligence Index task, compared with $5.98 for Opus 5.5 at maximum effort. That is a benchmark-specific cost estimate, not a guarantee for every real-world workload, but the direction is clear: frontier-adjacent capability at a fraction of the closed-model price.

For developers, that combination — near-frontier coding scores plus a price cut — is the real story. Agent workloads burn a lot of tokens, so a 33% price drop on top of a capability jump changes what is economical to automate.

Open weights by November 4 — why that matters

This is the part that makes K3.1 Pro more than a routine upgrade. Moonshot has committed to publishing the full model weights by November 4. Once released, Artificial Analysis' data suggests it would be the highest-scoring open-weight model on the Intelligence Index — ahead of everything else you can download and run yourself.

That puts genuine frontier-class coding and agent capability into the hands of anyone with enough hardware, free of per-token pricing. For the open-source AI ecosystem, this is the same category of shock the DeepSeek release delivered in early 2025.

One safety note from Moonshot itself: the company says it deliberately stripped cyberattack-related data from mid-training and reinforcement learning for the open release, so the public weights "won't push the frontier of offensive hacking" — its words, not an independent audit. No license for the weights has been specified yet, which is worth watching when November 4 arrives.

Image: Kimi logo (via securityonline.info)

What this means for you

Developers: a cheaper, faster coding agent is available in the API and Kimi Code right now — and a self-hostable version is weeks away.
Open-source fans: November 4 could reset the open-weight leaderboard. Mark the date and watch for the license terms.
Everyone else: the gap between closed frontier models and open models just shrank to 0.7 benchmark points on coding. The AI race is no longer a closed-lab race.

The takeaway

Kimi K3.1 Pro is Moonshot's boldest move yet: near-frontier coding performance, a 1-million-token context, a 33% price cut, and a promise to give the whole model away in less than two weeks. Whether the open weights land on time — and under what license — will decide whether this is remembered as a great launch or a historic one.

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