Claude Opus 5.5 vs Kimi K3.1 Pro
Full profiles: Claude Opus 5.5 (Anthropic) and Kimi K3.1 Pro (Moonshot AI): every benchmark, price and rank.
Updated · Data from 10 sources
As of 25 Oct 2026, Claude Opus 5.5 (max) and Kimi K3.1 Pro are neck and neck on quality (72.6 vs 66.9 on the BenchLeader Index, inside the ±8.4 margin of error), and Kimi K3.1 Pro costs 2.0× less, which makes it the better buy for most workloads. Pick Claude Opus 5.5 for knowledge (79 vs 75); pick Kimi K3.1 Pro for reasoning (81 vs 76).
Claude Opus 5.5 benchmarks max Anthropic
Kimi K3.1 Pro benchmarks Moonshot AIOpen in the comparison toolWhich to pick for…
The pick's numbers come first. Category scores on the BenchLeader scale (50 is the average model, 15 points one standard deviation). High confidence means a lead of half a standard deviation or more; under one point is called either.
| Use case | Pick | Why | Confidence |
|---|---|---|---|
| Agents & tool use | Kimi K3.1 Pro | 68 vs 63 category score; CWE-Bench (AA) 60.8% vs 58.3% | Medium |
| Reasoning | Kimi K3.1 Pro | 81 vs 76 category score; CritPt 24.6% vs 31.7% | Medium |
| Knowledge | Claude Opus 5.5 | 79 vs 75 category score; AA-Omniscience 46.4 vs 29.5 | Medium |
| Long documents | Either | 68 vs 68 category score; AA-LCR 84.7% vs 86.3% | Either |
| Images and other media | Claude Opus 5.5 | 71 vs 67 category score; MMMU-Pro 87.7% vs 83.9% | Medium |
| Lowest cost | Kimi K3.1 Pro | $4.00 vs $8.00 per 1M blended; agentic coding session $0.160 vs $0.320 | – |
| Fastest first answer | Kimi K3.1 Pro | 30.2 s (Kimi K3.1 Pro) vs 562.5 s (Claude Opus 5.5 (max)) to the first answer token | – |
| High volume on a budget | Neither flagship | A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs | – |
Key differences
- Claude Opus 5.5 (max) and Kimi K3.1 Pro are neck and neck on quality (72.6 vs 66.9, within the ±8.4 margin).
- Claude Opus 5.5 (max) is stronger in coding, composite, knowledge, maths, multimodal.
- Kimi K3.1 Pro is stronger in agents & tools, long context, reasoning.
- Kimi K3.1 Pro is 2.0× cheaper ($4.00 vs $8.00 per 1M blended).
- Claude Opus 5.5 (max) streams 1.3× faster (96 vs 73 tokens per second).
At a glance
| Spec | Claude Opus 5.5 | Kimi K3.1 Pro |
|---|---|---|
| Developer | Anthropic | Moonshot AI |
| Released | 22 Sept 2026 | 23 Oct 2026 |
| Context window (tokens) | 1,000,000 | 1,048,576 |
| Max output (tokens) | 128,000 (up to 300K on the Message Batches API (beta)) | – |
| Input types | text, image | – |
| Reasoning effort settings | low, medium, high, xhigh, max | – |
| Compared at | Claude Opus 5.5 (max) | Kimi K3.1 Pro |
| Open weights | No | No |
| Price in / out / cached input per 1M | $4.00 / $20.00 / $0.200 | $2.00 / $10.00 / $0.200 |
| API model ID | claude-opus-5-5 | – |
| Where to use it | Claude API, Amazon Bedrock, Google Cloud, Microsoft Foundry | – |
Limits, availability and announced prices from the vendors' own pages: docs.anthropic.com (checked 20 Oct 2026). Everything else is from the day's data.
Category by category
Category scores on the BenchLeader scale: 50 is the average evaluated model, 15 points is one standard deviation. A gap under one point is called level.
| Category | Claude Opus 5.5 (max) | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| Reasoning | 75.7 | 81.3 | Kimi K3.1 Pro |
| Coding | 81.9 | – | not comparable |
| Agents & tools | 63.2 | 68.0 | Kimi K3.1 Pro |
| Maths | 74.3 | – | not comparable |
| Knowledge | 78.8 | 74.8 | Claude Opus 5.5 |
| Multimodal | 70.9 | 67.0 | Claude Opus 5.5 |
| Long context | 67.5 | 68.3 | level |
| Composite | 94.0 | 75.8 | Claude Opus 5.5 |
Where sources disagree
Across the 21 benchmarks both have, Claude Opus 5.5 leads 12, Kimi K3.1 Pro leads 9. Every overall index that rates both puts Claude Opus 5.5 ahead.
| Overall index | Claude Opus 5.5 (max) | Kimi K3.1 Pro | Leader |
|---|---|---|---|
| BenchLeader Index | 72.6 | 66.9 | neck and neck |
| AA Intelligence Index v4.3.2 | 57.6 | 55.1 | Claude Opus 5.5 |
| Vals Index | 70.2† | 62.5 | Claude Opus 5.5 |
Each publisher runs its own tasks, harnesses and effort settings, so their overall verdicts can differ; BenchLeader reconciles them on one scale. † measured at another effort setting of the same model (the publisher did not test the one compared here).
Price, speed and latency
List prices blended at three input tokens per output token. Per-task prices use the token counts on the methodology page; suite cost is what Artificial Analysis paid to run its whole Intelligence Index.
| Measure | Claude Opus 5.5 (max) | Kimi K3.1 Pro |
|---|---|---|
| Blended price per 1M tokens | $8.00 | $4.00 |
| Input / output per 1M | $4.00 / $20.00 | $2.00 / $10.00 |
| Cached input per 1M | $0.200 | $0.200 |
| Price per task: chat reply | $0.0076 | $0.0038 |
| Price per task: summarize a 30-page report | $0.060 | $0.030 |
| Price per task: code edit | $0.054 | $0.027 |
| Price per task: agentic coding session | $0.320 | $0.160 |
| Price per task: structured extraction | $0.012 | $0.0060 |
| Cost to run a full benchmark suite | $5.98 | $2.11 |
| Output speed | 96 tok/s | 73 tok/s |
| Time to first answer | 562.5 s | 30.2 s |
| Time to a complete answer | 567.7 s | 37.0 s |
Per token is not per task: on Artificial Analysis' full suite Claude Opus 5.5 (max) cost $5.98 and Kimi K3.1 Pro $2.11, because Claude Opus 5.5 (max) used about 1.4× as many tokens for the same work, which a per-token price hides.
Each model is compared at its best-ranked reasoning-effort setting. Claude Opus 5.5 (max) scores 72.6 and takes 562 s to its first answer token; Claude Opus 5.5 (xhigh) scores 70.0 in 98 s, Claude Opus 5.5 (high) scores 69.4 in 22 s. Kimi K3.1 Pro scores 66.9 and takes 30 s to its first answer token. Higher effort means more thinking before the answer: better scores, longer waits and more tokens billed. How reasoning effort changes scores and cost.
Every benchmark
120 benchmarks, grouped by category; each name links to the board and its leaders. † measured at another effort setting of the same model, shown for reference and not counted as a win.
| Metric | Publisher | Claude Opus 5.5 (max) | Kimi K3.1 Pro |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 72.6 | 66.9 |
| Agents & tools score | BenchLeader | 63.2 | 68.0 |
| Coding score | BenchLeader | 81.9 | – |
| Composite score | BenchLeader | 94.0 | 75.8 |
| Knowledge score | BenchLeader | 78.8 | 74.8 |
| Long context score | BenchLeader | 67.5 | 68.3 |
| Maths score | BenchLeader | 74.3 | – |
| Multimodal score | BenchLeader | 70.9 | 67.0 |
| Reasoning score | BenchLeader | 75.7 | 81.3 |
| Blended price $/M | BenchLeader | $8.00 | $4.00 |
| Output speed | BenchLeader | 96 tok/s | 73 tok/s |
| Time to first answer | BenchLeader | 562.5 s | 30.2 s |
| Context window | BenchLeader | 1,000,000 tokens | 1,048,576 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | 90.6% | – |
| Arena Hard Prompts | Arena (LMArena) | 1535† | – |
| LiveBench 2.0 Reasoning | LiveBench | 92.2%† | 91.1% |
| LiveBench 1.0 Reasoning | LiveBench | 92.2% | – |
| Humanity's Last Exam (AA) | Artificial Analysis | 61.4% | 52.5% |
| ARC-AGI-1 | ARC Prize | 97.5% | – |
| ARC-AGI-2 | ARC Prize | 91.7% | – |
| CritPt | Artificial Analysis | 31.7% | 24.6% |
| MysteryMechanism | Vals AI | 49.5%† | – |
| Chess Puzzles | Epoch AI Benchmarking Hub | 67.0% | – |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | 71.0% | – |
| LMCA | Epoch AI Benchmarking Hub | 68.2% | – |
| DTBench | Epoch AI Benchmarking Hub | 98.9% | – |
| Coding | |||
| SciCode | SciCode | 66.9% | – |
| FrontierCode | Cognition | 54.6%† | – |
| Arena Coding | Arena (LMArena) | 1548† | – |
| Arena WebDev | Arena (LMArena) | 1807 | 1692† |
| LiveBench 2.0 Coding | LiveBench | 96.3%† | 81.8% |
| LiveBench 1.0 Coding | LiveBench | 89.3% | – |
| SciCode (AA) | Artificial Analysis | 66.9% | 60.8% |
| IOI | Vals AI | 95.1%† | – |
| Code Migration | Vals AI | 66.7%† | – |
| Code Migration v1.1 | Vals AI | 81.0%† | – |
| ProgramBench | Vals AI | 18.5%† | – |
| SWE-bench Multimodal | Vals AI | 70.2%† | – |
Show all 120 benchmarks
| Metric | Publisher | Claude Opus 5.5 (max) | Kimi K3.1 Pro |
|---|---|---|---|
| Coding | |||
| Vibe Code Bench 1-100 | Vals AI | 30.4%† | – |
| Vibe Code Bench v1.1 | Vals AI | 90.3%† | 84.9%† |
| MirrorCode | Epoch AI Benchmarking Hub | 77.4% | – |
| CursorBench | Cursor | 57.8% | – |
| ALE-Bench | Epoch AI Benchmarking Hub | 2147.4† | – |
| FrontierSWE | Epoch AI Benchmarking Hub | 62.3% | – |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 59.6% | 67.2% |
| Startrise Frontend | Startrise | 71.1%† | – |
| FrontierCode 1.1 (AA) | Artificial Analysis | 52.2% | 47.1% |
| Agents & tools | |||
| Terminal-Bench | Terminal-Bench | 64.8% | – |
| Remote Labor Index | Scale AI / CAIS | 21.3%† | – |
| APEX-Agents | Mercor | 73.5% | – |
| Arena Agent | Arena (LMArena) | 20.8 | – |
| LiveBench Long Agentic | LiveBench | 85.0%† | 49.5% |
| LiveBench Browser | LiveBench | 80.0%† | 80.0% |
| LiveBench Agentic Coding | LiveBench | 71.7% | – |
| Terminal-Bench 2.1 (Vals) | Vals AI | 87.6%† | – |
| HiL-Bench | Scale AI SEAL | 59.0%† | – |
| GDPval-AA v2.1 | Artificial Analysis | 68.3% | 67.3% |
| ITBench SRE (AA) | Artificial Analysis | 38.2% | – |
| Analyst Agent (AA) | Artificial Analysis | 56.3% | 38.8% |
| CUA-bench | Vals AI | 14.0% | – |
| CyberBench | Vals AI | 55.4%† | – |
| Finance Agent v2 | Vals AI | 58.6%† | – |
| Finance Agent v2.1 | Vals AI | 67.8%† | 61.5%† |
| Harvey's Legal Agent Benchmark v1.1 | Vals AI | 9.2%† | 11.7%† |
| Harvey's Legal Agent Benchmark v1 | Vals AI | 3.8%† | – |
| Legal Research Bench | Vals AI | 50.5%† | 37.5%† |
| Robo-bench | Vals AI | 14.6% | – |
| SREBench | Vals AI | 33.6%† | – |
| Tax Agent Bench | Vals AI | 45.6%† | 24.9%† |
| Terminal-Bench 4.0 (Vals) | Vals AI | 65.2%† | 63.6%† |
| Terminal-Bench Science | Vals AI | 47.1%† | – |
| Time Horizon Index: KSP | Vals AI | 91.3%† | – |
| Arena Search | Arena (LMArena) | 1211† | – |
| Vending-Bench 2 | Andon Labs | 9235.3† | – |
| AutomationBench | Artificial Analysis | 69.5% | 73.3% |
| GDP.pdf (AA) | Artificial Analysis | 26.2% | 31.4% |
| Harvey LAB-AA v1.1 | Harvey | 4.2% | – |
| AA-Briefcase v1.1 | Artificial Analysis | 1801 | 1678 |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | 59.0% | 34.3% |
| CWE-Bench (AA) | Artificial Analysis | 58.3% | 60.8% |
| DeepSec-Bench (AA) | Artificial Analysis | 26.9% | 36.7% |
| CyberGym end-to-end (AA) | Artificial Analysis | 0.8% | 94.7% |
| FACTS Search | 86.5%† | – | |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | 91.2% | – |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | 95.0% | – |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | 100.0% | – |
| ProofBench | Vals AI | 100.0% | – |
| LiveBench Mathematics | LiveBench | 97.1% | – |
| Arena Maths | Arena (LMArena) | 1512† | – |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | 72.2% | – |
| LiveBench 2.0 Data Analysis | LiveBench | 80.3%† | 79.1% |
| LiveBench Research | LiveBench | 85.0%† | 77.9% |
| LiveBench 1.0 Data Analysis | LiveBench | 80.3% | – |
| AA-Omniscience | Artificial Analysis | 46.4 | 29.5 |
| PRBench Legal | Scale AI SEAL | 47.6%† | – |
| BioMysteryBench | Vals AI | 79.3%† | – |
| ClaimBench | Vals AI | 100.0%† | – |
| Excel Modeling Benchmark | Vals AI | 75.9%† | – |
| Excel Modeling Benchmark v1.1 | Vals AI | 75.8%† | 70.0%† |
| MedCode | Vals AI | 49.8%† | – |
| MedScribe | Vals AI | 91.4%† | – |
| Public Benefits Bench v1.1 | Vals AI | 70.6%† | – |
| EBR-bench | Epoch AI Benchmarking Hub | 71.4% | – |
| GDP.pdf | Epoch AI Benchmarking Hub | 30.6% | – |
| AA-Omniscience: accuracy | Artificial Analysis | 66.2% | 51.0% |
| AA-Omniscience: non-hallucination | Artificial Analysis | 41.4% | 56.1% |
| Instruction following | |||
| LiveBench Language | LiveBench | 86.3% | – |
| LiveBench Instruction Following | LiveBench | 65.7% | – |
| Arena Instruction Following | Arena (LMArena) | 1521† | – |
| Human preference | |||
| Arena Text | Arena (LMArena) | 1509† | – |
| EQ-Bench 4 | EQ-Bench | 1339† | – |
| Arena Creative Writing | Arena (LMArena) | 1520† | – |
| Arena Multi-turn | Arena (LMArena) | 1503† | – |
| Arena Longer Queries | Arena (LMArena) | 1524† | – |
| Multimodal | |||
| Arena Vision | Arena (LMArena) | 1321† | – |
| LiveBench Design | LiveBench | 86.9%† | 77.8% |
| MMMU-Pro | Artificial Analysis | 87.7% | 83.9% |
| SAGE | Vals AI | 45.8%† | – |
| Blueprint-Bench 2 | Epoch AI Benchmarking Hub | 51.2%† | – |
| AA-3D | Artificial Analysis | 1196 | 1110 |
| Long context | |||
| AA-LCR | Artificial Analysis | 84.7% | 86.3% |
| MLCR | Artificial Analysis | 27.8% | – |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | 168.8† | – |
| LiveBench 2.0 | LiveBench | 86.5%† | 76.7% |
| LiveBench 1.0 | LiveBench | 83.2% | – |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 57.6 | 55.1 |
| Vals Index | Vals AI | 70.2† | 62.5† |
| Vals Finance Index | Vals AI | 65.6%† | 56.0%† |
| Vals RSI Index | Vals AI | 37.3% | – |
| Vals Science Index | Vals AI | 58.6%† | – |
| Vals Router Index | Vals AI | 64.2%† | – |
| AA Cyber Index | Artificial Analysis | 28.7 | 64.1 |
| Safety & honesty | |||
| FORTRESS | Scale AI SEAL | 5.8% | – |
Data as of 2026-10-25. Best configuration of each model; every score links to its source on the model pages.
What changed
- Claude Opus 5.5 (max): 1 score revision.
- Kimi K3.1 Pro: 3 new results (Analyst Agent (AA), Terminal-Bench-Science 0.1 (AA), AA-3D).
- Kimi K3.1 Pro: BenchLeader Index 65.6 → 66.8.
- Kimi K3.1 Pro: 5 new results (FrontierCode 1.1 (AA), AA Cyber Index, CWE-Bench (AA)…).
- Claude Opus 5.5 (max): 2 new results (Robo-bench, Vals RSI Index).
- Kimi K3.1 Pro: first results.
- Claude Opus 5.5 (max): 2 score revisions.
- Claude Opus 5.5 (max): 2 score revisions.
- Claude Opus 5.5 (max): BenchLeader Index 71.9 → 72.6.
- Claude Opus 5.5 (max): 1 new result (FORTRESS).
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- Kimi K3.1 Pro vs Muse Wonder Full
- Kimi K3.1 Pro vs Claude Fable 5.1
- Claude Opus 5.5 vs Kimi K3
- Claude Opus 5.5 vs GPT-6.1 Sol
Rankings: Best LLM overall · Best LLM for coding · Best LLM for agents · Best cheap LLMs
Claude Opus 5.5 vs Kimi K3.1 Pro: questions
- Is Claude Opus 5.5 better than Kimi K3.1 Pro?
- Claude Opus 5.5 (max) and Kimi K3.1 Pro are neck and neck on quality (72.6 vs 66.9, within the ±8.4 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2026-10-25, so check the category scores for your use.
- Which is cheaper, Claude Opus 5.5 or Kimi K3.1 Pro, and will that change?
- Kimi K3.1 Pro is cheaper today: $4.00 against $8.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
- Is Claude Opus 5.5 better than Kimi K3.1 Pro for agents and tool use?
- Kimi K3.1 Pro scores higher in agentic tasks (68 vs 63 on the category index, where 50 is average). On CWE-Bench (AA), the top shared agents & tools benchmark, it is 58.3% for Claude Opus 5.5 against 60.8% for Kimi K3.1 Pro.
- Which is better for long documents?
- They are level on long-context benchmarks (68 vs 68). Both take about 1M tokens: Claude Opus 5.5 1,000,000, Kimi K3.1 Pro 1,048,576.
- Which has lower latency?
- Kimi K3.1 Pro answers first: 30.2 s against 562.5 s to the first answer token, as Artificial Analysis measures it. Reasoning effort drives most of this: a higher setting thinks longer before it answers.
- Which is faster, Claude Opus 5.5 or Kimi K3.1 Pro?
- Claude Opus 5.5 streams faster: 96 against 73 output tokens per second.
- Do independent benchmarks agree on Claude Opus 5.5 vs Kimi K3.1 Pro?
- Across the 21 benchmarks both have, Claude Opus 5.5 leads 12, Kimi K3.1 Pro leads 9. Every overall index that rates both puts Claude Opus 5.5 ahead.
- When was Kimi K3.1 Pro released?
- Kimi K3.1 Pro was released on 23 Oct 2026.