GPT-5.5 vs Kimi K2.5
Updated October 21, 2026. 90 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick GPT-5.5 for coding: it scores 67.8 on the Vibe Coding Index against 58.5 for Kimi K2.5.
Pick Kimi K2.5 when output tokens cost 12.0x less, or when a solved task costs $0.24 against $1.65.
- Shared results
- 90
- GPT-5.5 only
- 42
- Kimi K2.5 only
- 8
- Like-for-like categories
- 8 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, four public coding benchmarks
GPT-5.5
GPT-5.5 scores 67.8 against 58.5.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
GPT-5.5
GPT-5.5 leads, 38.4 against 23.5.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GPT-5.5 has a AA Agentic Index result, 36.4.
Directional only
Reasoning
GPQA Diamond
GPT-5.5
GPT-5.5 leads, 93.2% against 84.1%.
Same board, both measured
Math
AIME
No call
Only Kimi K2.5 has a AIME result, 95.6%.
Directional only
Knowledge
MMLU Pro
GPT-5.5
GPT-5.5 leads, 88.1% against 85.9%.
Same board, both measured
Web design
Design Arena: websites
GPT-5.5
GPT-5.5 leads, 1256 against 1249.
Same board, both measured
Long documents
Listed context window
GPT-5.5
GPT-5.5 takes 1.05M tokens against 262K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Kimi K2.5
GPT-5.5 $0.020, Kimi K2.5 $0.0018 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Kimi K2.5
GPT-5.5 $1.65, Kimi K2.5 $0.24.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.5 67.8 from 2 benchmarks, Kimi K2.5 58.5 from 2 benchmarks.
- Widest category
- Coding, 23.4 points apart on average over 16 shared benchmarks.
- Widest single gap
- ARC-AGI-2: GPT-5.5 85.0% against Kimi K2.5 11.8%, 73.2 points apart on a 0 to 100 scale.
- Output price
- GPT-5.5 $30.00 against Kimi K2.5 $2.50 per million output tokens, 12.0x apart.
- Context window
- GPT-5.5 takes 1.05M tokens, Kimi K2.5 262K.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | GPT-5.5 | Bars | Kimi K2.5 | Ties |
|---|---|---|---|---|
| Coding | 16 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 5 | 5 | ||
| Reasoning | 12 | 0 | ||
| Math | 2 | 0 | ||
| Knowledge | 11 | 0 | ||
| Web design | 7 | 1 | ||
| General | 28 | 1 | ||
| All shared boards | 83 | 7 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index160
| Benchmark | GPT-5.5 | Kimi K2.5 | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 70.8% | Only Kimi K2.5 measured |
| SWE-bench Multilingual | Not measured | 67.3% | Only Kimi K2.5 measured |
| LiveBench coding | 85.1% | Not measured | Only GPT-5.5 measured |
| LMArena WebDev | 1513 | 1437 | GPT-5.5 |
| AA Coding Index | 74.9 | 46.8 | GPT-5.5 |
| LiveCodeBench (Vals AI) | 85.3% | 83.9% | GPT-5.5 |
| SWE-bench Verified (Vals AI) | 82.6% | 70.0% | GPT-5.5 |
| Vibe Code Bench (Vals AI) | 69.8% | 17.5% | GPT-5.5 |
| Code migration (Vals AI) | 45.2% | 7.0% | GPT-5.5 |
| ProgramBench (Vals AI) | 0.5% | Not measured | Only GPT-5.5 measured |
| Terminal-Bench 2.1 (Vals AI) | 76.4% | 42.0% | GPT-5.5 |
| SkillsBench (Vals AI) | 62.5% | Not measured | Only GPT-5.5 measured |
| SciCode | 56.1% | Not measured | Only GPT-5.5 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 60.6% | 34.8% | GPT-5.5 |
| Terminal-Bench | 84.7% | 43.2% | GPT-5.5 |
| FrontierCode | 43.0% | Not measured | Only GPT-5.5 measured |
| GSO-Bench | 40.2% | Not measured | Only GPT-5.5 measured |
| WeirdML | 84.9% | 45.6% | GPT-5.5 |
| MirrorCode | 10.0% | Not measured | Only GPT-5.5 measured |
| ALE-Bench | 1943.0 | 821.6 | GPT-5.5 |
| LMArena Text: coding | 1494 | 1483 | GPT-5.5 |
| LMArena Text: software and IT | 1493 | 1471 | GPT-5.5 |
| LMArena WebDev: React | 1506 | 1429 | GPT-5.5 |
| LMArena WebDev: HTML | 1543 | 1426 | GPT-5.5 |
| LMArena WebDev: from an image | 1532 | 1439 | GPT-5.5 |
| Neither model has a result on the other 13 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.5 | Kimi K2.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.4 | 23.5 | GPT-5.5 |
| Epoch Capabilities Index | 159.7 | 148.1 | GPT-5.5 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index55
| Benchmark | GPT-5.5 | Kimi K2.5 | Leader |
|---|---|---|---|
| AA Agentic Index | 36.4 | Not measured | Only GPT-5.5 measured |
| Design Arena: agents building web apps | 1117 | 1136 | Kimi K2.5 |
| Design Arena: agents building full-stack apps | 1089 | 1114 | Kimi K2.5 |
| Design Arena: agents building mobile apps | 1143 | 1147 | Kimi K2.5 |
| Design Arena: agents building Android apps | 1169 | 1124 | GPT-5.5 |
| Design Arena: agents building Godot games | 1173 | 1219 | Kimi K2.5 |
| Design Arena: agents building games | 1179 | Not measured | Only GPT-5.5 measured |
| Design Arena: HTML slides | 1067 | Not measured | Only GPT-5.5 measured |
| Design Arena: PowerPoint slides | 1108 | Not measured | Only GPT-5.5 measured |
| LiveBench research | 61.6% | Not measured | Only GPT-5.5 measured |
| LiveBench browser | 48.0% | Not measured | Only GPT-5.5 measured |
| LiveBench long agentic | 44.6% | Not measured | Only GPT-5.5 measured |
| SREBench (Vals AI) | 3.8% | Not measured | Only GPT-5.5 measured |
| Finance Agent (Vals AI) | 51.8% | 35.8% | GPT-5.5 |
| Tax Agent Bench (Vals AI) | 21.8% | Not measured | Only GPT-5.5 measured |
| Legal Research Bench (Vals AI) | 40.4% | 15.9% | GPT-5.5 |
| Excel Modeling Benchmark (Vals AI) | 64.5% | 28.5% | GPT-5.5 |
| Time Horizon Index (Vals AI) | 8.3% | Not measured | Only GPT-5.5 measured |
| τ²-Bench Telecom | 93.9% | 95.9% | Kimi K2.5 |
| APEX-Agents | 55.1% | Not measured | Only GPT-5.5 measured |
| Remote Labor Index | 6.3% | Not measured | Only GPT-5.5 measured |
| OSWorld 2.0 | 13.0% | Not measured | Only GPT-5.5 measured |
| DeepResearch Bench | 54.0% | Not measured | Only GPT-5.5 measured |
| PostTrainBench | 27.2% | Not measured | Only GPT-5.5 measured |
| OSWorld | Not measured | 63.3% | Only Kimi K2.5 measured |
| Vending-Bench 2 | $7,524 | $1,198 | GPT-5.5 |
| Neither model has a result on the other 13 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index120
| Benchmark | GPT-5.5 | Kimi K2.5 | Leader |
|---|---|---|---|
| GPQA Diamond | 93.2% | 84.1% | GPT-5.5 |
| LiveBench reasoning | 89.7% | Not measured | Only GPT-5.5 measured |
| MMMU Pro (Vals AI) | 88.3% | 84.3% | GPT-5.5 |
| GPQA Diamond (Artificial Analysis run) | 93.5% | 87.9% | GPT-5.5 |
| Humanity's Last Exam (Artificial Analysis run) | 45.8% | 30.7% | GPT-5.5 |
| GPQA Diamond (Epoch AI run) | 90.7% | Not measured | Only GPT-5.5 measured |
| ARC-AGI | 95.0% | 65.3% | GPT-5.5 |
| ARC-AGI-2 | 85.0% | 11.8% | GPT-5.5 |
| SimpleBench | 69.0% | 46.8% | GPT-5.5 |
| Chess puzzles | 63.0% | Not measured | Only GPT-5.5 measured |
| Mystery game puzzles | 56.0% | Not measured | Only GPT-5.5 measured |
| EBR-bench | 34.3% | Not measured | Only GPT-5.5 measured |
| LMArena Text: hard prompts | 1489 | 1453 | GPT-5.5 |
| LMArena Text: expert | 1507 | 1466 | GPT-5.5 |
| LMArena Text: hard prompts in English | 1483 | 1460 | GPT-5.5 |
| LMArena Vision: diagrams | 1325 | 1282 | GPT-5.5 |
| LMArena Vision: homework | 1332 | 1297 | GPT-5.5 |
| Neither model has a result on the other 4 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GPT-5.5 | Kimi K2.5 | Leader |
|---|---|---|---|
| AIME | Not measured | 95.6% | Only Kimi K2.5 measured |
| OTIS Mock AIME | 84.4% | Not measured | Only GPT-5.5 measured |
| FrontierMath, tiers 1 to 3 | 85.3% | Not measured | Only GPT-5.5 measured |
| FrontierMath, tier 4 | 72.5% | Not measured | Only GPT-5.5 measured |
| ProofBench | 50.0% | Not measured | Only GPT-5.5 measured |
| LMArena Text: math | 1487 | 1470 | GPT-5.5 |
| LMArena Text: mathematical work | 1496 | 1473 | GPT-5.5 |
| Neither model has a result on the other 6 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index110
| Benchmark | GPT-5.5 | Kimi K2.5 | Leader |
|---|---|---|---|
| MMLU Pro | 88.1% | 85.9% | GPT-5.5 |
| LegalBench (Vals AI) | 86.5% | Not measured | Only GPT-5.5 measured |
| CaseLaw (Vals AI) | 66.2% | 58.7% | GPT-5.5 |
| CorpFin (Vals AI) | 68.4% | 68.3% | GPT-5.5 |
| TaxEval (Vals AI) | 75.0% | 74.2% | GPT-5.5 |
| MortgageTax (Vals AI) | 68.8% | 66.5% | GPT-5.5 |
| MedQA (Vals AI) | Not measured | 94.4% | Only Kimi K2.5 measured |
| MedCode (Vals AI) | 49.1% | 39.3% | GPT-5.5 |
| SimpleQA Verified | 63.0% | 34.3% | GPT-5.5 |
| LMArena Text: science | 1485 | 1459 | GPT-5.5 |
| LMArena Text: medicine and healthcare | 1465 | 1448 | GPT-5.5 |
| LMArena Text: legal and government | 1491 | 1441 | GPT-5.5 |
| LMArena Text: business and finance | 1478 | 1427 | GPT-5.5 |
| Neither model has a result on the other 4 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index71
| Benchmark | GPT-5.5 | Kimi K2.5 | Leader |
|---|---|---|---|
| Design Arena: websites | 1256 | 1249 | GPT-5.5 |
| Design Arena: UI components | 1260 | 1236 | GPT-5.5 |
| Design Arena: game dev | 1294 | 1207 | GPT-5.5 |
| Design Arena: data viz | 1265 | 1219 | GPT-5.5 |
| Design Arena: 3D | 1198 | 1205 | Kimi K2.5 |
| Design Arena: all code categories | 1260 | 1236 | GPT-5.5 |
| Design Arena: SVG | 1234 | 1149 | GPT-5.5 |
| Design Arena: ASCII art | 1254 | 1165 | GPT-5.5 |
| LiveBench design | 70.3% | Not measured | Only GPT-5.5 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index281
| Benchmark | GPT-5.5 | Kimi K2.5 | Leader |
|---|---|---|---|
| LiveBench data analysis | 81.6% | Not measured | Only GPT-5.5 measured |
| Public Benefits Bench (Vals AI) | 60.9% | Not measured | Only GPT-5.5 measured |
| SAGE (Vals AI) | 51.5% | 49.9% | GPT-5.5 |
| MedScribe (Vals AI) | 86.9% | 76.4% | GPT-5.5 |
| Vals Multimodal Index | 68.1% | Not measured | Only GPT-5.5 measured |
| IFBench | 75.9% | 70.2% | GPT-5.5 |
| Long context reasoning (AA-LCR) | 84.3% | 78.0% | GPT-5.5 |
| DTBench | 96.0% | Not measured | Only GPT-5.5 measured |
| LMCA | 54.3% | Not measured | Only GPT-5.5 measured |
| Fiction.LiveBench | Not measured | 86.1% | Only Kimi K2.5 measured |
| CL-bench | Not measured | 19.3% | Only Kimi K2.5 measured |
| Surface Evolver Bench | 88.1% | Not measured | Only GPT-5.5 measured |
| Furniture assembly | 44.2% | Not measured | Only GPT-5.5 measured |
| ExploitBench | 47.4% | Not measured | Only GPT-5.5 measured |
| CL-bench Life | 22.2% | 13.2% | GPT-5.5 |
| LMArena Text | 1471 | 1445 | GPT-5.5 |
| LMArena Text: instruction following | 1478 | 1431 | GPT-5.5 |
| LMArena Text: creative writing | 1455 | 1422 | GPT-5.5 |
| LMArena Vision | 1297 | 1269 | GPT-5.5 |
| LMArena Text: English | 1470 | 1453 | GPT-5.5 |
| LMArena Text: non-English | 1467 | 1433 | GPT-5.5 |
| LMArena Text: Chinese | 1534 | 1494 | GPT-5.5 |
| LMArena Text: German | 1480 | 1441 | GPT-5.5 |
| LMArena Text: Japanese | 1499 | 1423 | GPT-5.5 |
| LMArena Text: Korean | 1460 | 1412 | GPT-5.5 |
| LMArena Text: French | 1485 | 1454 | GPT-5.5 |
| LMArena Text: Spanish | 1468 | 1450 | GPT-5.5 |
| LMArena Text: Russian | 1473 | 1435 | GPT-5.5 |
| LMArena Text: Polish | 1465 | 1445 | GPT-5.5 |
| LMArena Text: multi-turn | 1476 | 1444 | GPT-5.5 |
| LMArena Text: longer queries | 1484 | 1445 | GPT-5.5 |
| LMArena Text: writing and language | 1466 | 1425 | GPT-5.5 |
| LMArena Text: entertainment and media | 1449 | 1417 | GPT-5.5 |
| LMArena Vision: English | 1292 | 1274 | GPT-5.5 |
| LMArena Vision: Chinese | 1360 | 1328 | GPT-5.5 |
| LMArena Vision: reading text | 1306 | 1276 | GPT-5.5 |
| LMArena Vision: humor | 1293 | 1284 | GPT-5.5 |
| LMArena Vision: captioning | Not measured | 1257 | Only Kimi K2.5 measured |
| LMArena Vision: recognizing things | 1231 | 1285 | Kimi K2.5 |
| LMArena Vision: creative writing | 1301 | 1269 | GPT-5.5 |
| LMArena Document | 1486 | Not measured | Only GPT-5.5 measured |
| Neither model has a result on the other 5 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.5 | Kimi K2.5 | Leader |
|---|---|---|---|
| Neither model has a result on 5 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Kimi K2.5 costs less
Repository review
50K input + 3K output tokens
Kimi K2.5 costs less
Agent loop
200K input + 10K output tokens
Kimi K2.5 costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | OpenAI GPT-5.5 | MoonshotAI Kimi K2.5 |
|---|---|---|
| Maker | OpenAI | Moonshot AI |
| Weights | No public weights listed | Open weights |
| Released | April 24, 2026 | January 27, 2026 |
| Context window | 1.05M | 262K |
| Input $/Mtok | $5.00 | $0.50 |
| Output $/Mtok | $30.00 | $2.50 |
| Coding index | 67.8 | 58.5 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | $1.65 | $0.24 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.5 better than Kimi K2.5 for coding?
Pick GPT-5.5 for coding: it scores 67.8 on the Vibe Coding Index against 58.5 for Kimi K2.5. Pick Kimi K2.5 when output tokens cost 12.0x less, or when a solved task costs $0.24 against $1.65.
Which is cheaper, GPT-5.5 or Kimi K2.5?
GPT-5.5 costs $5.00 per million input tokens and $30.00 per million output tokens; Kimi K2.5 costs $0.50 and $2.50. Per solved SWE-bench Verified task, GPT-5.5 costs $1.65 and Kimi K2.5 $0.24.
Which has the bigger context window, GPT-5.5 or Kimi K2.5?
GPT-5.5, with 1.05M tokens against 262K.
How many benchmarks is the GPT-5.5 vs Kimi K2.5 comparison based on?
90 benchmarks have a result for both models as of October 21, 2026. GPT-5.5's coding index rests on 2 independent benchmarks and Kimi K2.5's on 2. Where only one model has a result, the page says so instead of naming a winner.