GPT-5.5 vs Kimi K3
GPT-5.5 leads Kimi K3 on coding, 71.3 to 62.3 on the Vibe Coding Index, and Kimi K3 costs 2.0x less per output token ($15.00 vs $30.00 per million). Updated October 21, 2026; 106 benchmarks have a result for both.
GPT-5.5 or Kimi K3: which to pick
Pick GPT-5.5 for coding: it scores 71.3 on the Vibe Coding Index against 62.3 for Kimi K3, though on 5 benchmarks against 6.
Pick Kimi K3 for output tokens 2.0x cheaper ($15.00 vs $30.00 per million) and a lower cost per solved task ($0.81 against $1.65).
- Shared results
- 106
- GPT-5.5 only
- 28
- Kimi K3 only
- 11
- Like-for-like categories
- 8 of 9
Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.
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, six public coding benchmarks
GPT-5.5
GPT-5.5 scores 71.3 against 62.3.
5 and 6 benchmarks behind the scores
Intelligence
AA Intelligence Index
Kimi K3
Kimi K3 leads, 43.6 against 38.4.
Same board, both measured
Agentic work
AA Agentic Index
Kimi K3
Kimi K3 leads, 50.0 against 36.4.
Same board, both measured
Reasoning
GPQA Diamond
GPT-5.5
GPT-5.5 leads, 93.2% against 92.9%.
Same board, both measured
Knowledge
MMLU Pro
GPT-5.5
GPT-5.5 leads, 88.1% against 88.0%.
Same board, both measured
Web design
Design Arena: websites
Kimi K3
Kimi K3 leads, 1335 against 1256.
Same board, both measured
General
Vals Index
No call
Only Kimi K3 has a Vals Index result, 53.0%.
Directional only
Long documents
Listed context window
GPT-5.5
GPT-5.5 takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Kimi K3
GPT-5.5 $0.020, Kimi K3 $0.011 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
Kimi K3
GPT-5.5 $1.65, Kimi K3 $0.81.
Published attempt cost and pass rate
At a glance
- Coding index
- GPT-5.5 71.3 from 5 benchmarks, Kimi K3 62.3 from 6 benchmarks.
- Widest category
- Math, 16.5 points apart on average over 6 shared benchmarks.
- Widest single gap
- ProofBench: GPT-5.5 50.0% against Kimi K3 87.0%, 37.0 points apart on a 0 to 100 scale.
- Output price
- GPT-5.5 $30.00 against Kimi K3 $15.00 per million output tokens, 2.0x apart.
- Context window
- GPT-5.5 takes 1.05M tokens, Kimi K3 1.05M.
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 K3 | Ties |
|---|---|---|---|---|
| Coding | 4 | 14 | ||
| Intelligence | 1 | 1 | ||
| Agentic work | 4 | 16 | ||
| Reasoning | 7 | 6 | 1 tie | |
| Math | 2 | 4 | ||
| Knowledge | 5 | 6 | ||
| Web design | 0 | 8 | ||
| General | 9 | 18 | ||
| All shared boards | 32 | 73 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index414
| Benchmark | GPT-5.5 | Kimi K3 | Leader |
|---|---|---|---|
| LiveBench coding | 85.1% | 59.3% | GPT-5.5 |
| LMArena WebDev | 1513 | 1655 | Kimi K3 |
| AA Coding Index | 74.9 | 76.2 | Kimi K3 |
| LiveCodeBench (Vals AI) | 85.3% | 87.2% | Kimi K3 |
| SWE-bench Verified (Vals AI) | 82.6% | 93.4% | Kimi K3 |
| Terminal-Bench 4 (Vals AI) | Not measured | 17.2% | Only Kimi K3 measured |
| Vibe Code Bench (Vals AI) | 69.8% | 85.0% | Kimi K3 |
| Code migration (Vals AI) | 45.2% | 16.1% | GPT-5.5 |
| ProgramBench (Vals AI) | 0.5% | 2.0% | Kimi K3 |
| IOI (Vals AI) | Not measured | 48.9% | Only Kimi K3 measured |
| Terminal-Bench 2.1 (Vals AI) | 76.4% | 80.9% | Kimi K3 |
| SWE-bench Multimodal (Vals AI) | Not measured | 44.2% | Only Kimi K3 measured |
| Vibe Code Bench 1-100 (Vals AI) | Not measured | 18.2% | Only Kimi K3 measured |
| SkillsBench (Vals AI) | 62.5% | Not measured | Only GPT-5.5 measured |
| CyberBench (Vals AI) | Not measured | 75.2% | Only Kimi K3 measured |
| SciCode | 56.1% | 59.5% | Kimi K3 |
| Terminal-Bench Hard (Artificial Analysis run) | 60.6% | Not measured | Only GPT-5.5 measured |
| Terminal-Bench | 84.7% | Not measured | Only GPT-5.5 measured |
| FrontierCode | 43.0% | 44.2% | Kimi K3 |
| FrontierSWE | Not measured | 25.9% | Only Kimi K3 measured |
| GSO-Bench | 40.2% | Not measured | Only GPT-5.5 measured |
| WeirdML | 84.9% | 82.6% | GPT-5.5 |
| MirrorCode | 10.0% | Not measured | Only GPT-5.5 measured |
| ALE-Bench | 1943.0 | 1524.5 | GPT-5.5 |
| LMArena Text: coding | 1494 | 1508 | Kimi K3 |
| LMArena Text: software and IT | 1493 | 1499 | Kimi K3 |
| LMArena WebDev: React | 1506 | 1670 | Kimi K3 |
| LMArena WebDev: HTML | 1543 | 1644 | Kimi K3 |
| LMArena WebDev: from an image | 1532 | 1579 | Kimi K3 |
| Neither model has a result on the other 10 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | GPT-5.5 | Kimi K3 | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.4 | 43.6 | Kimi K3 |
| Epoch Capabilities Index | 159.7 | 157.9 | GPT-5.5 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index416
| Benchmark | GPT-5.5 | Kimi K3 | Leader |
|---|---|---|---|
| AA Agentic Index | 36.4 | 50.0 | Kimi K3 |
| Design Arena: agents building web apps | 1117 | 1295 | Kimi K3 |
| Design Arena: agents building full-stack apps | 1089 | 1315 | Kimi K3 |
| Design Arena: agents building mobile apps | 1143 | 1269 | Kimi K3 |
| Design Arena: agents building Android apps | 1163 | 1250 | Kimi K3 |
| Design Arena: agents building Godot games | 1173 | 1223 | Kimi K3 |
| Design Arena: agents building games | 1179 | 1252 | Kimi K3 |
| Design Arena: HTML slides | 1067 | 1256 | Kimi K3 |
| Design Arena: PowerPoint slides | 1109 | 1273 | Kimi K3 |
| Design Arena: spreadsheets | Not measured | 1058 | Only Kimi K3 measured |
| LiveBench research | 61.6% | 79.0% | Kimi K3 |
| LiveBench browser | 48.0% | 16.0% | GPT-5.5 |
| LiveBench long agentic | 44.6% | 42.8% | GPT-5.5 |
| SREBench (Vals AI) | 3.8% | Not measured | Only GPT-5.5 measured |
| Finance Agent (Vals AI) | 51.8% | 53.1% | Kimi K3 |
| Tax Agent Bench (Vals AI) | 21.8% | 33.4% | Kimi K3 |
| Legal Research Bench (Vals AI) | 40.4% | 46.1% | Kimi K3 |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 12.9% | Only Kimi K3 measured |
| Excel Modeling Benchmark (Vals AI) | 64.5% | 66.7% | Kimi K3 |
| BioMysteryBench (Vals AI) | Not measured | 72.6% | Only Kimi K3 measured |
| Terminal-Bench-Science (Vals AI) | Not measured | 1.4% | Only Kimi K3 measured |
| Time Horizon Index (Vals AI) | 8.3% | 10.5% | Kimi K3 |
| τ²-Bench Telecom | 93.9% | Not measured | Only GPT-5.5 measured |
| APEX-Agents | 55.1% | 47.8% | GPT-5.5 |
| 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% | 32.0% | Kimi K3 |
| Vending-Bench 2 | $7,524 | $5,165 | GPT-5.5 |
| Neither model has a result on the other 12 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index76
| Benchmark | GPT-5.5 | Kimi K3 | Leader |
|---|---|---|---|
| GPQA Diamond | 93.2% | 92.9% | GPT-5.5 |
| LiveBench reasoning | 89.7% | 90.7% | Kimi K3 |
| MMMU Pro (Vals AI) | 88.3% | 88.2% | GPT-5.5 |
| GPQA Diamond (Artificial Analysis run) | 93.5% | 93.5% | Tie |
| Humanity's Last Exam (Artificial Analysis run) | 45.8% | 46.9% | Kimi K3 |
| GPQA Diamond (Epoch AI run) | 90.7% | 93.1% | Kimi K3 |
| ARC-AGI | 95.0% | 94.5% | GPT-5.5 |
| ARC-AGI-2 | 85.0% | 60.4% | GPT-5.5 |
| SimpleBench | 69.0% | 60.7% | GPT-5.5 |
| Chess puzzles | 63.0% | 37.0% | GPT-5.5 |
| Mystery game puzzles | 56.0% | 26.0% | GPT-5.5 |
| EBR-bench | 34.3% | Not measured | Only GPT-5.5 measured |
| LMArena Text: hard prompts | 1489 | 1495 | Kimi K3 |
| LMArena Text: expert | 1507 | 1520 | Kimi K3 |
| LMArena Text: hard prompts in English | 1483 | 1496 | Kimi K3 |
| LMArena Vision: diagrams | 1325 | Not measured | Only GPT-5.5 measured |
| LMArena Vision: homework | 1332 | Not measured | Only GPT-5.5 measured |
| Kagi LLM Benchmark | 88.8% | Not measured | Only GPT-5.5 measured |
| Neither model has a result on the other 4 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index24
| Benchmark | GPT-5.5 | Kimi K3 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 84.4% | 97.2% | Kimi K3 |
| FrontierMath, tiers 1 to 3 | 85.3% | 72.2% | GPT-5.5 |
| FrontierMath, tier 4 | 72.5% | 39.0% | GPT-5.5 |
| ProofBench | 50.0% | 87.0% | Kimi K3 |
| LMArena Text: math | 1487 | 1494 | Kimi K3 |
| LMArena Text: mathematical work | 1496 | 1505 | Kimi K3 |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index56
| Benchmark | GPT-5.5 | Kimi K3 | Leader |
|---|---|---|---|
| MMLU Pro | 88.1% | 88.0% | GPT-5.5 |
| LegalBench (Vals AI) | 86.5% | 86.2% | GPT-5.5 |
| CaseLaw (Vals AI) | 66.2% | Not measured | Only GPT-5.5 measured |
| CorpFin (Vals AI) | 68.4% | 71.6% | Kimi K3 |
| TaxEval (Vals AI) | 75.0% | 75.7% | Kimi K3 |
| MortgageTax (Vals AI) | 68.8% | 66.3% | GPT-5.5 |
| MedCode (Vals AI) | 49.1% | 49.4% | Kimi K3 |
| SimpleQA Verified | 63.0% | 50.6% | GPT-5.5 |
| LMArena Text: science | 1485 | 1508 | Kimi K3 |
| LMArena Text: medicine and healthcare | 1465 | 1489 | Kimi K3 |
| LMArena Text: legal and government | 1491 | 1503 | Kimi K3 |
| LMArena Text: business and finance | 1478 | 1470 | GPT-5.5 |
| FACTS Benchmark Suite | 66.7% | Not measured | Only GPT-5.5 measured |
| Neither model has a result on the other 5 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index08
| Benchmark | GPT-5.5 | Kimi K3 | Leader |
|---|---|---|---|
| Design Arena: websites | 1256 | 1335 | Kimi K3 |
| Design Arena: UI components | 1260 | 1344 | Kimi K3 |
| Design Arena: game dev | 1294 | 1359 | Kimi K3 |
| Design Arena: data viz | 1265 | 1351 | Kimi K3 |
| Design Arena: 3D | 1198 | 1388 | Kimi K3 |
| Design Arena: all code categories | 1260 | 1360 | Kimi K3 |
| Design Arena: SVG | 1234 | 1302 | Kimi K3 |
| Design Arena: ASCII art | 1255 | Not measured | Only GPT-5.5 measured |
| LiveBench design | 70.3% | 77.2% | Kimi K3 |
GeneralLike-for-likePublic boards, shown as published, kept out of the index918
| Benchmark | GPT-5.5 | Kimi K3 | Leader |
|---|---|---|---|
| Vals Index | Not measured | 53.0% | Only Kimi K3 measured |
| LiveBench data analysis | 81.6% | 78.7% | GPT-5.5 |
| Public Benefits Bench (Vals AI) | 60.9% | 68.2% | Kimi K3 |
| SAGE (Vals AI) | 51.5% | 52.8% | Kimi K3 |
| MedScribe (Vals AI) | 86.9% | 88.0% | Kimi K3 |
| Vals Multimodal Index | 68.1% | 73.4% | Kimi K3 |
| IFBench | 75.9% | Not measured | Only GPT-5.5 measured |
| Long context reasoning (AA-LCR) | 84.3% | 88.7% | Kimi K3 |
| DTBench | 96.0% | 91.2% | GPT-5.5 |
| LMCA | 54.3% | 52.7% | GPT-5.5 |
| Surface Evolver Bench | 88.1% | 95.0% | Kimi K3 |
| Furniture assembly | 44.2% | 34.2% | GPT-5.5 |
| ExploitBench | 47.4% | Not measured | Only GPT-5.5 measured |
| CL-bench Life | 22.2% | Not measured | Only GPT-5.5 measured |
| LMArena Text | 1471 | 1476 | Kimi K3 |
| LMArena Text: instruction following | 1478 | 1485 | Kimi K3 |
| LMArena Text: creative writing | 1455 | 1457 | Kimi K3 |
| LMArena Vision | 1297 | Not measured | Only GPT-5.5 measured |
| LMArena Text: English | 1470 | 1481 | Kimi K3 |
| LMArena Text: non-English | 1467 | 1466 | GPT-5.5 |
| LMArena Text: Chinese | 1534 | 1529 | GPT-5.5 |
| LMArena Text: German | 1480 | 1490 | Kimi K3 |
| LMArena Text: Japanese | 1499 | 1494 | GPT-5.5 |
| LMArena Text: Korean | 1460 | 1460 | GPT-5.5 |
| LMArena Text: French | 1485 | 1492 | Kimi K3 |
| LMArena Text: Spanish | 1468 | 1472 | Kimi K3 |
| LMArena Text: Russian | 1473 | 1485 | Kimi K3 |
| LMArena Text: Polish | 1465 | 1458 | GPT-5.5 |
| LMArena Text: multi-turn | 1476 | 1489 | Kimi K3 |
| LMArena Text: longer queries | 1484 | 1494 | Kimi K3 |
| LMArena Text: writing and language | 1466 | 1471 | Kimi K3 |
| LMArena Text: entertainment and media | 1449 | 1453 | Kimi K3 |
| LMArena Vision: English | 1292 | Not measured | Only GPT-5.5 measured |
| LMArena Vision: Chinese | 1360 | Not measured | Only GPT-5.5 measured |
| LMArena Vision: reading text | 1306 | Not measured | Only GPT-5.5 measured |
| LMArena Vision: humor | 1293 | Not measured | Only GPT-5.5 measured |
| LMArena Vision: recognizing things | 1231 | Not measured | Only GPT-5.5 measured |
| LMArena Vision: creative writing | 1301 | Not measured | Only GPT-5.5 measured |
| LMArena Document | 1486 | Not measured | Only GPT-5.5 measured |
| Neither model has a result on the other 7 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | GPT-5.5 | Kimi K3 | 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 K3 costs less
Repository review
50K input + 3K output tokens
Kimi K3 costs less
Agent loop
200K input + 10K output tokens
Kimi K3 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 K3 |
|---|---|---|
| Maker | OpenAI | Moonshot AI |
| Weights | No public weights listed | Open weights |
| Released | April 24, 2026 | July 16, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $5.00 | $3.00 |
| Output $/Mtok | $30.00 | $15.00 |
| Coding index | 71.3 | 62.3 |
| Independent measurements behind it | 5 | 6 |
| Cost per solved task | $1.65 | $0.81 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GPT-5.5 better than Kimi K3 for coding?
Pick GPT-5.5 for coding: it scores 71.3 on the Vibe Coding Index against 62.3 for Kimi K3, though on 5 benchmarks against 6. Pick Kimi K3 for output tokens 2.0x cheaper ($15.00 vs $30.00 per million) and a lower cost per solved task ($0.81 against $1.65).
Which is cheaper, GPT-5.5 or Kimi K3?
GPT-5.5 costs $5.00 per million input tokens and $30.00 per million output tokens; Kimi K3 costs $3.00 and $15.00. Per solved SWE-bench Verified task, GPT-5.5 costs $1.65 and Kimi K3 $0.81.
Which has the bigger context window, GPT-5.5 or Kimi K3?
GPT-5.5, with 1.05M tokens against 1.05M.
How many benchmarks is the GPT-5.5 vs Kimi K3 comparison based on?
106 benchmarks have a result for both models as of October 21, 2026. GPT-5.5's coding index rests on 5 independent benchmarks and Kimi K3's on 6. Where only one model has a result, the page says so instead of naming a winner.