GPT-5.5 vs Kimi K3
Full profiles: GPT-5.5 (OpenAI) and Kimi K3 (Moonshot AI): every benchmark, price and rank.
Updated · Data from 11 sources
As of 25 Oct 2026, GPT-5.5 (xhigh) and Kimi K3 (max) are neck and neck on quality (66.1 vs 64.8 on the BenchLeader Index, inside the ±5.0 margin of error), and Kimi K3 (max) costs 1.9× less, which makes it the better buy for most workloads. Pick GPT-5.5 for reasoning (76 vs 66); pick Kimi K3 for coding (65 vs 61).
GPT-5.5 benchmarks 
Kimi K3 benchmarks Which 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 |
|---|---|---|---|
| Coding | Kimi K3 | 65 vs 61 category score; Arena WebDev 1655 vs 1513 | Medium |
| Agents & tool use | GPT-5.5 | 62 vs 59 category score; MCP Atlas 75.3% vs 82.3% | Medium |
| Maths | GPT-5.5 | 70 vs 63 category score; FrontierMath Tiers 1–3 85.3% vs 72.2% | Medium |
| Reasoning | GPT-5.5 | 76 vs 66 category score; ARC-AGI-2 85.0% vs 60.4% | High |
| Knowledge | GPT-5.5 | 65 vs 63 category score; SimpleQA Verified 63.0% vs 50.6% | Medium |
| Long documents | Kimi K3 | 70 vs 67 category score; AA-LCR 88.7% vs 84.3% | Medium |
| Images and other media | Either | 63 vs 64 category score; MMMU-Pro 79.9% vs 80.5% | Either |
| Chat quality (human preference) | – | Only Kimi K3 has an Arena rating (68 category score) | Not comparable |
| Lowest cost | Kimi K3 | $6.00 vs $11.25 per 1M blended; agentic coding session $0.240 vs $0.420 | – |
| Fastest first answer | GPT-5.5 | 39.1 s (GPT-5.5 (xhigh)) vs 52.6 s (Kimi K3 (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
- GPT-5.5 (xhigh) and Kimi K3 (max) are neck and neck on quality (66.1 vs 64.8, within the ±5.0 margin).
- GPT-5.5 (xhigh) is stronger in agents & tools, instruction following, knowledge, maths, reasoning.
- Kimi K3 (max) is stronger in coding, composite, long context, multimodal, human preference.
- Kimi K3 (max) is 1.9× cheaper ($6.00 vs $11.25 per 1M blended).
- GPT-5.5 (xhigh) streams 2.1× faster (86 vs 41 tokens per second).
At a glance
| Spec | GPT-5.5 | Kimi K3 |
|---|---|---|
| Developer | OpenAI | Moonshot AI |
| Released | 23 Apr 2026 | 16 Jul 2026 |
| Context window (tokens) | 1,050,000 | 1,048,576 |
| Compared at | GPT-5.5 (xhigh) | Kimi K3 (max) |
| Open weights | No | Yes |
| Price in / out / cached input per 1M | $5.00 / $30.00 / $0.500 | $3.00 / $15.00 / $0.300 |
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 | GPT-5.5 (xhigh) | Kimi K3 (max) | Leader |
|---|---|---|---|
| Reasoning | 75.5 | 66.4 | GPT-5.5 |
| Coding | 61.1 | 64.6 | Kimi K3 |
| Agents & tools | 62.3 | 59.4 | GPT-5.5 |
| Maths | 69.7 | 63.4 | GPT-5.5 |
| Knowledge | 65.3 | 62.8 | GPT-5.5 |
| Instruction following | 73.9 | – | not comparable |
| Human preference | – | 68.1 | not comparable |
| Multimodal | 62.9 | 63.6 | level |
| Long context | 67.3 | 69.6 | Kimi K3 |
| Composite | 72.4 | 78.3 | Kimi K3 |
Where sources disagree
Across the 53 benchmarks both have, GPT-5.5 leads 23, Kimi K3 leads 29 and 1 is a tie. Every overall index that rates both puts Kimi K3 ahead.
| Overall index | GPT-5.5 (xhigh) | Kimi K3 (max) | Leader |
|---|---|---|---|
| BenchLeader Index | 66.1 | 64.8 | neck and neck |
| AA Intelligence Index v4.3.2 | 38.4 | 43.6 | Kimi K3 |
| Arena Text | 1482† | 1487 | Kimi K3 |
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 | GPT-5.5 (xhigh) | Kimi K3 (max) |
|---|---|---|
| Blended price per 1M tokens | $11.25 | $6.00 |
| Input / output per 1M | $5.00 / $30.00 | $3.00 / $15.00 |
| Cached input per 1M | $0.500 | $0.300 |
| Price per task: chat reply | $0.011 | $0.0057 |
| Price per task: summarize a 30-page report | $0.078 | $0.045 |
| Price per task: code edit | $0.075 | $0.041 |
| Price per task: agentic coding session | $0.420 | $0.240 |
| Price per task: structured extraction | $0.016 | $0.0090 |
| Cost to run a full benchmark suite | $2.63 | $2.00 |
| Output speed | 86 tok/s | 41 tok/s |
| Time to first answer | 39.1 s | 52.6 s |
| Time to a complete answer | 45.0 s | 65.0 s |
Per token is not per task: on Artificial Analysis' full suite GPT-5.5 (xhigh) cost $2.63 and Kimi K3 (max) $2.00, because Kimi K3 (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. GPT-5.5 (xhigh) scores 66.1 and takes 39 s to its first answer token; GPT-5.5 (high) scores 65.3 in 14 s, GPT-5.5 (medium) scores 62.9 in 3 s. Kimi K3 (max) scores 64.8 and takes 53 s to its first answer token; Kimi K3 scores 58.8 in 1 s, Kimi K3 (low) scores 58.2 in 57 s. 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
157 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 | GPT-5.5 (xhigh) | Kimi K3 (max) |
|---|---|---|---|
| BenchLeader Index | BenchLeader | 66.1 | 64.8 |
| Agents & tools score | BenchLeader | 62.3 | 59.4 |
| Coding score | BenchLeader | 61.1 | 64.6 |
| Composite score | BenchLeader | 72.4 | 78.3 |
| Instruction following score | BenchLeader | 73.9 | – |
| Knowledge score | BenchLeader | 65.3 | 62.8 |
| Long context score | BenchLeader | 67.3 | 69.6 |
| Maths score | BenchLeader | 69.7 | 63.4 |
| Multimodal score | BenchLeader | 62.9 | 63.6 |
| Reasoning score | BenchLeader | 75.5 | 66.4 |
| Human preference score | BenchLeader | – | 68.1 |
| Blended price $/M | BenchLeader | $11.25 | $6.00 |
| Output speed | BenchLeader | 86 tok/s | 41 tok/s |
| Time to first answer | BenchLeader | 39.1 s | 52.6 s |
| Context window | BenchLeader | 1,050,000 tokens | 1,048,576 tokens |
| Reasoning | |||
| GPQA Diamond | Epoch AI Benchmarking Hub | 90.7%† | 93.1% |
| SimpleBench | SimpleBench | 69.0%† | 60.7% |
| Arena Hard Prompts | Arena (LMArena) | 1499† | 1516 |
| LiveBench 2.0 Reasoning | LiveBench | 89.7%† | 90.7%† |
| LiveBench 1.0 Reasoning | LiveBench | 89.7% | 90.7%† |
| GPQA Diamond (AA) | Artificial Analysis | 93.5% | 93.5% |
| Humanity's Last Exam (AA) | Artificial Analysis | 45.8% | 46.9% |
| GPQA Diamond (Vals) | Vals AI | 93.2% | 92.9%† |
| Kagi LLM Benchmark | Kagi LLM Benchmark | 88.8%† | – |
| ARC-AGI-1 | ARC Prize | 95.0% | 94.5% |
| ARC-AGI-2 | ARC Prize | 85.0% | 60.4% |
| ARC-AGI-3 | ARC Prize | 0.4%† | – |
| CritPt | Artificial Analysis | 27.1% | 23.4% |
| Chess Puzzles | Epoch AI Benchmarking Hub | 63.0% | 36.0% |
| Mystery Game Puzzles | Epoch AI Benchmarking Hub | 56.0% | 26.0% |
| CL-bench Life | Epoch AI Benchmarking Hub | 22.2%† | – |
| LMCA | Epoch AI Benchmarking Hub | 54.3% | 52.7% |
| DTBench | Epoch AI Benchmarking Hub | 96.0% | 91.2% |
| ForecastBench | ForecastBench | 64.4%† | 64.6% |
| BTF-3 | Epoch AI Benchmarking Hub | 14.3%† | – |
| Coding | |||
| SciCode | SciCode | 55.8% | 59.5% |
| WeirdML | WeirdML | 84.9% | 82.6% |
| FrontierCode | Cognition | 43.0%† | 44.2%† |
| GSO-Bench | GSO-Bench | 40.2% | – |
| Arena Coding | Arena (LMArena) | 1511† | 1539 |
Show all 157 benchmarks
| Metric | Publisher | GPT-5.5 (xhigh) | Kimi K3 (max) |
|---|---|---|---|
| Coding | |||
| Arena WebDev | Arena (LMArena) | 1513 | 1655 |
| LiveBench 2.0 Coding | LiveBench | 85.1%† | 59.3%† |
| LiveBench 1.0 Coding | LiveBench | 82.2% | 81.5%† |
| LiveCodeBench | Vals AI | 85.3% | 87.2% |
| IOI | Vals AI | – | 48.9% |
| SWE-bench (Vals) | Vals AI | 82.6% | 93.4%† |
| Code Migration | Vals AI | 45.2% | 16.1% |
| Code Migration v1.1 | Vals AI | – | 28.6% |
| ProgramBench | Vals AI | 0.5% | 2.0%† |
| SWE-bench Multimodal | Vals AI | – | 44.2% |
| Vibe Code Bench 1-100 | Vals AI | – | 18.2% |
| Vibe Code Bench v1.1 | Vals AI | 69.8% | 85.0% |
| SWE Atlas: Codebase QnA | Scale AI SEAL | 45.4% | – |
| SWE Atlas: Refactoring | Scale AI SEAL | 44.8% | – |
| SWE Atlas: Test Writing | Scale AI SEAL | 42.6% | – |
| MirrorCode | Epoch AI Benchmarking Hub | 10.0%† | – |
| Surface Evolver Bench | Epoch AI Benchmarking Hub | 88.1%† | 93.0% |
| DeepSWE v1.1 | Epoch AI Benchmarking Hub | 67.0% | 68.5% |
| ALE-Bench | Epoch AI Benchmarking Hub | 1943.0 | 1524.5 |
| FrontierSWE | Epoch AI Benchmarking Hub | – | 25.9% |
| Terminal-Bench 4.0 (AA) | Artificial Analysis | 14.7% | 12.6% |
| Terminal-Bench 2.1 (AA) | Artificial Analysis | 84.3% | 85.0% |
| Startrise Frontend | Startrise | – | 79.8%† |
| FrontierCode 1.1 (AA) | Artificial Analysis | – | 43.6% |
| Agents & tools | |||
| Terminal-Bench | Terminal-Bench | 84.7%† | – |
| OSWorld-Verified 2.0 | OSWorld | 13.0% | – |
| Remote Labor Index | Scale AI / CAIS | 6.3%† | – |
| APEX-Agents | Mercor | 55.1%† | 47.8%† |
| Arena Agent | Arena (LMArena) | – | 1.6 |
| LiveBench Long Agentic | LiveBench | 44.6%† | 42.8%† |
| LiveBench Browser | LiveBench | 48.0%† | 16.0%† |
| LiveBench Agentic Coding | LiveBench | 54.0% | 62.2%† |
| Terminal-Bench Hard | Artificial Analysis | 60.6% | – |
| τ²-Bench Telecom (AA) | Artificial Analysis | 93.9% | – |
| Terminal-Bench 2.1 (Vals) | Vals AI | 76.4%† | 80.9%† |
| MCP Atlas | Scale AI SEAL | 75.3% | 82.3% |
| HiL-Bench | Scale AI SEAL | 39.7%† | 42.7%† |
| τ³-bench Banking | τ²-bench | 44.6% | 37.1% |
| τ³-Banking (AA) | Artificial Analysis | 39.0% | 46.0% |
| ITBench SRE (AA) | Artificial Analysis | 45.8% | 47.7% |
| Analyst Agent (AA) | Artificial Analysis | 50.0% | 38.8% |
| APEX-Agents (AA) | Artificial Analysis | 37.7% | 41.3% |
| CyberBench | Vals AI | – | 75.2% |
| Finance Agent v2 | Vals AI | 51.8% | 53.1% |
| Finance Agent v2.1 | Vals AI | – | 60.0% |
| Harvey's Legal Agent Benchmark v1.1 | Vals AI | – | 12.9% |
| Harvey's Legal Agent Benchmark v1 | Vals AI | 3.8% | 12.9% |
| Legal Research Bench | Vals AI | 40.4% | 46.1% |
| SkillsBench | Vals AI | 62.2% | – |
| SREBench | Vals AI | 3.8% | – |
| Tax Agent Bench | Vals AI | 21.8% | 33.4% |
| Terminal-Bench 2.0 (Vals) | Vals AI | 73.2%† | – |
| Terminal-Bench 4.0 (Vals) | Vals AI | – | 17.2% |
| Terminal-Bench Science | Vals AI | – | 1.4% |
| Time Horizon Index: KSP | Vals AI | 8.3% | 10.5% |
| DeepResearch Bench | DeepResearch Bench | 54.0%† | – |
| PostTrainBench | Epoch AI Benchmarking Hub | 27.2% | 32.0%† |
| ExploitBench | Epoch AI Benchmarking Hub | 47.4%† | – |
| GBAEval | Epoch AI Benchmarking Hub | 53.2%† | 48.4%† |
| Vending-Bench 2 | Andon Labs | 7523.8† | 5165.0† |
| AutomationBench | Artificial Analysis | 47.3% | 58.3% |
| GDP.pdf (AA) | Artificial Analysis | 21.2% | 22.0% |
| Harvey LAB-AA v1.1 | Harvey | – | 5.3% |
| EnterpriseOps-Gym | Artificial Analysis | 46.6% | 45.3% |
| AA-Briefcase v1.1 | Artificial Analysis | 1136 | 1499 |
| Terminal-Bench-Science 0.1 (AA) | Artificial Analysis | – | 8.1% |
| CWE-Bench (AA) | Artificial Analysis | – | 53.3% |
| DeepSec-Bench (AA) | Artificial Analysis | – | 12.4% |
| CyberGym end-to-end (AA) | Artificial Analysis | – | 58.0% |
| Maths | |||
| FrontierMath Tiers 1–3 | Epoch AI Benchmarking Hub | 85.3% | 72.2% |
| FrontierMath Tier 4 | Epoch AI Benchmarking Hub | 72.5% | 39.0% |
| OTIS Mock AIME | Epoch AI Benchmarking Hub | 84.4%† | 97.2% |
| ProofBench | Vals AI | 50.0% | 87.0%† |
| LiveBench Mathematics | LiveBench | 95.9% | 84.4%† |
| AIME 2026 | MathArena | 100.0% | 96.7%† |
| HMMT February 2026 | MathArena | 98.5% | 97.0%† |
| USAMO 2026 | MathArena | 98.2% | – |
| MathArena Apex | MathArena | 80.2% | 65.6%† |
| Arena Maths | Arena (LMArena) | 1501† | 1499 |
| Knowledge | |||
| SimpleQA Verified | Epoch AI Benchmarking Hub | 63.0% | 50.6% |
| LiveBench 2.0 Data Analysis | LiveBench | 81.6%† | 78.7%† |
| LiveBench Research | LiveBench | 61.6%† | 79.0%† |
| LiveBench 1.0 Data Analysis | LiveBench | 81.6% | 78.7%† |
| AA-Omniscience | Artificial Analysis | 20.5 | 19.7 |
| MMLU-Pro | Vals AI | 88.1% | 88.0% |
| LegalBench | Vals AI | 86.5% | 86.2% |
| CorpFin | Vals AI | 68.4% | 71.6%† |
| TaxEval | Vals AI | 75.0% | 75.7%† |
| BioMysteryBench | Vals AI | – | 72.6% |
| CaseLaw v2 | Vals AI | 66.2% | – |
| Excel Modeling Benchmark | Vals AI | 64.5% | 66.7% |
| Excel Modeling Benchmark v1.1 | Vals AI | – | 71.3% |
| MedCode | Vals AI | 49.1% | 49.4% |
| MedScribe | Vals AI | 86.9% | 88.0% |
| Public Benefits Bench v1.1 | Vals AI | 60.9% | 68.2% |
| DrugDiscoveryBench | Scale AI SEAL | 51.6% | – |
| EBR-bench | Epoch AI Benchmarking Hub | 34.3% | – |
| GDP.pdf | Epoch AI Benchmarking Hub | 26.0% | 19.0% |
| AA-Omniscience: accuracy | Artificial Analysis | 58.0% | 47.6% |
| AA-Omniscience: non-hallucination | Artificial Analysis | 11.0% | 46.8% |
| Instruction following | |||
| LiveBench Language | LiveBench | 87.4% | 85.5%† |
| LiveBench Instruction Following | LiveBench | 70.7% | 71.4%† |
| IFBench | Artificial Analysis | 75.8% | – |
| Arena Instruction Following | Arena (LMArena) | 1475† | 1489 |
| Human preference | |||
| Arena Text | Arena (LMArena) | 1477† | 1487 |
| EQ-Bench 4 | EQ-Bench | 1294† | 1318† |
| Arena Creative Writing | Arena (LMArena) | 1448† | 1462 |
| Arena Multi-turn | Arena (LMArena) | 1484† | 1502 |
| Arena Longer Queries | Arena (LMArena) | 1487† | 1503 |
| Multimodal | |||
| Arena Vision | Arena (LMArena) | 1297† | – |
| LiveBench Design | LiveBench | 70.3%† | 77.2%† |
| MMMU-Pro | Artificial Analysis | 79.9% | 80.5% |
| MMMU-Pro (Vals) | Vals AI | 88.3% | 88.2%† |
| MortgageTax | Vals AI | 68.8% | 66.3%† |
| SAGE | Vals AI | 51.5% | 52.8% |
| Blueprint-Bench 2 | Epoch AI Benchmarking Hub | 36.2%† | 29.5%† |
| AA-3D | Artificial Analysis | – | 982 |
| Long context | |||
| AA-LCR | Artificial Analysis | 84.3% | 88.7% |
| Arena Document | Arena (LMArena) | 1483† | – |
| MLCR | Artificial Analysis | 28.9% | 21.7% |
| Composite | |||
| Epoch Capabilities Index | Epoch AI Benchmarking Hub | 159.7† | 157.9† |
| LiveBench 2.0 | LiveBench | 68.7%† | 63.4%† |
| LiveBench 1.0 | LiveBench | 80.2% | 79.2%† |
| AA Intelligence Index v4.3.2 | Artificial Analysis | 38.4 | 43.6 |
| Vals Index | Vals AI | – | 53.0 |
| Vals Finance Index | Vals AI | – | 58.0% |
| Vals RSI Index | Vals AI | 16.5% | 20.9% |
| Vals Multimodal Index | Vals AI | 68.1% | 73.4%† |
| Vals Router Index | Vals AI | – | 53.0%† |
| AA Cyber Index | Artificial Analysis | – | 41.3 |
| Safety & honesty | |||
| FORTRESS | Scale AI SEAL | 16.3% | 26.6% |
| Metadata | |||
| AA Openness Index | Artificial Analysis | – | 38.9 |
Data as of 2026-10-25. Best configuration of each model; every score links to its source on the model pages.
What changed
- GPT-5.5 (xhigh): 1 new result (AA-Briefcase v1.1).
- GPT-5.5 (xhigh): 2 new results (Harvey's Legal Agent Benchmark v1, Vals RSI Index).
- Kimi K3 (max): 7 new results (Code Migration v1.1, Excel Modeling Benchmark v1.1, Finance Agent v2.1…).
- GPT-5.5 (xhigh): 1 score revision.
- Kimi K3 (max): 1 new result (Terminal-Bench-Science 0.1 (AA)); 1 score revision.
- Kimi K3 (max): 3 score revisions.
- Kimi K3 (max): 1 score revision.
- GPT-5.5 (xhigh): 6 new results (USAMO 2026, AutomationBench, GDP.pdf (AA)…).
- Kimi K3 (max): 1 new result (τ³-bench Banking).
- GPT-5.5 (xhigh): BenchLeader Index 66.2 → 65.7.
Related comparisons
- GPT-5.5 vs Claude Opus 5.5
- GPT-5.5 vs Gemini 4 Argon
- GPT-5.5 vs Muse Wonder Full
- Kimi K3 vs Claude Opus 5.5
- Kimi K3 vs Gemini 4 Argon
- Kimi K3 vs Muse Wonder Full
- Kimi K3 vs Claude Fable 5.1
- GPT-5.4 vs Kimi K3
Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs
GPT-5.5 vs Kimi K3: questions
- Is GPT-5.5 better than Kimi K3?
- GPT-5.5 (xhigh) and Kimi K3 (max) are neck and neck on quality (66.1 vs 64.8, within the ±5.0 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, GPT-5.5 or Kimi K3, and will that change?
- Kimi K3 is cheaper today: $6.00 against $11.25 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
- Is GPT-5.5 better than Kimi K3 for coding?
- Kimi K3 scores higher in coding (65 vs 61 on the category index, where 50 is average). On Arena WebDev, the top shared coding benchmark, it is 1513 for GPT-5.5 against 1655 for Kimi K3.
- Is GPT-5.5 better than Kimi K3 for agents and tool use?
- GPT-5.5 scores higher in agentic tasks (62 vs 59 on the category index, where 50 is average). On MCP Atlas, the top shared agents & tools benchmark, it is 75.3% for GPT-5.5 against 82.3% for Kimi K3.
- Which is better for long documents?
- Kimi K3 scores higher on long-context benchmarks (70 vs 67). Both take about 1.1M tokens: GPT-5.5 1,050,000, Kimi K3 1,048,576.
- Which has lower latency?
- GPT-5.5 (xhigh) answers first: 39.1 s against 52.6 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, GPT-5.5 or Kimi K3?
- GPT-5.5 streams faster: 86 against 41 output tokens per second.
- Do independent benchmarks agree on GPT-5.5 vs Kimi K3?
- Across the 53 benchmarks both have, GPT-5.5 leads 23, Kimi K3 leads 29 and 1 is a tie. Every overall index that rates both puts Kimi K3 ahead.
- When was Kimi K3 released?
- Kimi K3 was released on 16 Jul 2026.