Kimi K3.1 Pro vs Claude Opus 5.5: Price vs Frontier

Introduction

Claude Opus 5.5 sits at the top of the current Artificial Analysis Intelligence Index, and it prices accordingly: $4 per million input tokens, $20 output. Kimi K3.1 Pro arrives three points behind on the same index at exactly half the token price, with open weights promised in ten days.

That is the whole decision in one sentence. The rest of this comparison works out where the three-point gap actually bites, where the price advantage evaporates, and which workloads should move today rather than after the weight release.

Overview

Kimi K3.1 Pro

Moonshot's post-trained successor to K3:

• Intelligence Index: 55 (Artificial Analysis) — fourth overall, and the highest score slated for open weights
• $2 / $10 per million input/output tokens; $0.20 cached input; Highspeed variant at $4 / $20
• 1M-token context with native image and video input
• Terminal-Bench 4.0: 65.7% on Moonshot's launch chart
• Full weights promised by November 4, 2026
• Adjustable reasoning effort (low, high, max; default max)

See our full Kimi K3.1 Pro review for the benchmark breakdown and the cost-per-task caveat.

Claude Opus 5.5

Anthropic's current flagship, released September 22, 2026:

• Intelligence Index: 58 — the highest measured on the current index
• $4 / $20 per million input/output tokens; $0.20 cached input; cache writes $5; Fast mode at $8 / $40
• 1M-token context, 128K maximum output
• Terminal-Bench 4.0: 66.4% on Anthropic's own benchmark
• Closed weights; API and Claude products only

See our full Claude Opus 5.5 review for the independent testing disagreements and the safety disclosure.

Head-to-Head Benchmarks

Read the table honestly. Only the Intelligence Index and GDPval-AA come from the same independent harness; the Terminal-Bench figures are vendor runs from two different labs, and a 0.7-point gap on vendor charts is not a meaningful difference. The three-point index gap is the only capability signal here that is measured identically for both models — and three points is exactly the distance between "frontier" and "near-frontier" in this generation.

Both models also share a cost trap at maximum effort: K3.1 Pro emits about 14% more output tokens than K3 (cost per Intelligence Index task $1.98 versus $2.00), and Opus 5.5 at max effort generates roughly 1.6× the output tokens of Opus 5, leaving its cost per task level with its predecessor in independent testing.

Pricing: Half the Rate Card

Two details matter more than the headline. First, cached input is priced identically at $0.20, so cache-heavy agent loops — the workloads where most of the bill lives — see a smaller relative saving than the 50% sticker suggests. Second, cache writes are 2.5× cheaper on K3.1 Pro ($2 versus $5), which favors workloads that rebuild context often.

At list price, a workload with 2M fresh input tokens, 8M cached reads, and 1M output tokens costs $15.60 on K3.1 Pro versus $29.60 on Opus 5.5 — a 47% saving. Check the arithmetic against your own token mix before assuming half.

Where Each Model Wins

The pattern: Opus 5.5 sells certainty — the top score, a long independent testing record, and the ecosystem that most agent frameworks integrate first. K3.1 Pro sells the same neighborhood at half price, with the option to own the weights later.

The Open-Weights Variable

The weight release is the wildcard in this comparison. Moonshot says the full K3.1 Pro checkpoint lands by November 4, 2026, which would make it the highest-scoring open-weight model ever published and shrink the proprietary-to-open gap from 12 points to 3.

Moonshot also says it stripped cyber-offense material during training: on its internal xdev-bench-hard test, the filtered model scores 81.0% versus 90.5% unfiltered. That is a meaningful caveat for security teams, and a reminder that "open weights" does not mean "unrestricted capability."

If self-hosting, data sovereignty, or fine-tuning is on your roadmap, that single fact outweighs three index points. If it is not, the weight release changes nothing about your API bill.

Which Should You Choose?

• Hardest agentic tasks, budget secondary: Claude Opus 5.5 — the only model here with a measurable capability lead and a deep independent test record
• High-volume agentic coding: Kimi K3.1 Pro — half the token price for a statistical tie on vendor terminal benchmarks
• Cache-heavy long-running agents: compare your token mix first — identical $0.20 cache reads, but K3.1 Pro's $2 cache writes and flat long-context pricing usually win
• Self-hosting or fine-tuning on the roadmap: Kimi K3.1 Pro — weights by November 4
• Regulated or Western-enterprise procurement: Claude Opus 5.5 — closed weights, established vendor posture
• Scientific computing in a terminal: neither — GPT-6 Astra leads Terminal-Bench Science in both labs' reporting

Final Ratings

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