Claude Sonnet 5 vs GPT-5.5
GPT-5.5 leads Claude Sonnet 5 on coding, 71.3 to 57.7 on the Vibe Coding Index, and Claude Sonnet 5 costs 3.0x less per output token ($10.00 vs $30.00 per million). Updated October 22, 2026; 114 benchmarks have a result for both.
Claude Sonnet 5 or GPT-5.5: which to pick
Pick GPT-5.5 for coding: it scores 71.3 on the Vibe Coding Index against 57.7 for Claude Sonnet 5, though on 5 benchmarks against 6.
Pick Claude Sonnet 5 for output tokens 3.0x cheaper ($10.00 vs $30.00 per million) and work measured by LMArena WebDev or Vibe Code Bench (Vals AI), where it leads.
- Shared results
- 114
- Claude Sonnet 5 only
- 7
- GPT-5.5 only
- 20
- 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 57.7.
6 and 5 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-5.5
GPT-5.5 leads, 38.4 against 38.2.
Same board, both measured
Agentic work
AA Agentic Index
Claude Sonnet 5
Claude Sonnet 5 leads, 43.6 against 36.4.
Same board, both measured
Reasoning
GPQA Diamond
GPT-5.5
GPT-5.5 leads, 93.2% against 88.9%.
Same board, both measured
Knowledge
MMLU Pro
GPT-5.5
GPT-5.5 leads, 88.1% against 87.5%.
Same board, both measured
Web design
Design Arena: websites
Claude Sonnet 5
Claude Sonnet 5 leads, 1274 against 1256.
Same board, both measured
Long documents
Listed context window
GPT-5.5
GPT-5.5 takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Claude Sonnet 5
Claude Sonnet 5 $0.0070, GPT-5.5 $0.020 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GPT-5.5
Claude Sonnet 5 $1.87, GPT-5.5 $1.65.
Published attempt cost and pass rate
At a glance
- Coding index
- Claude Sonnet 5 57.7 from 6 benchmarks, GPT-5.5 71.3 from 5 benchmarks.
- Widest category
- Math, 17.7 points apart on average over 6 shared benchmarks.
- Widest single gap
- FrontierMath, tier 4: Claude Sonnet 5 29.3% against GPT-5.5 72.5%, 43.2 points apart on a 0 to 100 scale.
- Output price
- Claude Sonnet 5 $10.00 against GPT-5.5 $30.00 per million output tokens, 3.0x apart.
- Context window
- Claude Sonnet 5 takes 1M tokens, GPT-5.5 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 | Claude Sonnet 5 | Bars | GPT-5.5 | Ties |
|---|---|---|---|---|
| Coding | 4 | 16 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 15 | 4 | ||
| Reasoning | 0 | 14 | ||
| Math | 2 | 4 | ||
| Knowledge | 2 | 9 | ||
| Web design | 5 | 4 | ||
| General | 2 | 31 | ||
| All shared boards | 30 | 84 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index416
| Benchmark | Claude Sonnet 5 | GPT-5.5 | Leader |
|---|---|---|---|
| LiveBench coding | 74.7% | 85.1% | GPT-5.5 |
| LMArena WebDev | 1540 | 1513 | Claude Sonnet 5 |
| AA Coding Index | 71.5 | 74.9 | GPT-5.5 |
| LiveCodeBench (Vals AI) | 82.4% | 85.3% | GPT-5.5 |
| SWE-bench Verified (Vals AI) | 79.6% | 82.6% | GPT-5.5 |
| Terminal-Bench 4 (Vals AI) | 10.6% | Not measured | Only Claude Sonnet 5 measured |
| Vibe Code Bench (Vals AI) | 81.3% | 69.8% | Claude Sonnet 5 |
| Code migration (Vals AI) | 44.4% | 45.2% | GPT-5.5 |
| ProgramBench (Vals AI) | 0.0% | 0.5% | GPT-5.5 |
| IOI (Vals AI) | 45.0% | Not measured | Only Claude Sonnet 5 measured |
| Terminal-Bench 2.1 (Vals AI) | 74.5% | 76.4% | GPT-5.5 |
| Vibe Code Bench 1-100 (Vals AI) | 13.8% | Not measured | Only Claude Sonnet 5 measured |
| SkillsBench (Vals AI) | 46.5% | 62.5% | GPT-5.5 |
| CyberBench (Vals AI) | 70.3% | Not measured | Only Claude Sonnet 5 measured |
| SciCode | 54.3% | 56.1% | GPT-5.5 |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 60.6% | Only GPT-5.5 measured |
| Terminal-Bench | Not measured | 84.7% | Only GPT-5.5 measured |
| FrontierCode | 42.7% | 43.0% | GPT-5.5 |
| GSO-Bench | 37.3% | 40.2% | GPT-5.5 |
| WeirdML | 68.8% | 84.9% | GPT-5.5 |
| MirrorCode | Not measured | 10.0% | Only GPT-5.5 measured |
| ALE-Bench | 1463.1 | 1943.0 | GPT-5.5 |
| LMArena Text: coding | 1483 | 1494 | GPT-5.5 |
| LMArena Text: software and IT | 1474 | 1493 | GPT-5.5 |
| LMArena WebDev: React | 1541 | 1506 | Claude Sonnet 5 |
| LMArena WebDev: HTML | 1527 | 1543 | GPT-5.5 |
| LMArena WebDev: from an image | 1540 | 1532 | Claude Sonnet 5 |
| SciCode | 10.7% | Not measured | Only Claude Sonnet 5 measured |
| Neither model has a result on the other 11 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Claude Sonnet 5 | GPT-5.5 | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.2 | 38.4 | GPT-5.5 |
| Epoch Capabilities Index | 156.9 | 159.7 | GPT-5.5 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index154
| Benchmark | Claude Sonnet 5 | GPT-5.5 | Leader |
|---|---|---|---|
| AA Agentic Index | 43.6 | 36.4 | Claude Sonnet 5 |
| Design Arena: agents building web apps | 1245 | 1117 | Claude Sonnet 5 |
| Design Arena: agents building full-stack apps | 1249 | 1089 | Claude Sonnet 5 |
| Design Arena: agents building mobile apps | 1215 | 1142 | Claude Sonnet 5 |
| Design Arena: agents building Android apps | 1227 | 1164 | Claude Sonnet 5 |
| Design Arena: agents building Godot games | 1225 | 1173 | Claude Sonnet 5 |
| Design Arena: agents building games | 1227 | 1179 | Claude Sonnet 5 |
| Design Arena: HTML slides | 1168 | 1017 | Claude Sonnet 5 |
| Design Arena: PowerPoint slides | 1191 | 1084 | Claude Sonnet 5 |
| Design Arena: spreadsheets | 1035 | Not measured | Only Claude Sonnet 5 measured |
| LiveBench research | 82.8% | 61.6% | Claude Sonnet 5 |
| LiveBench browser | 72.0% | 48.0% | Claude Sonnet 5 |
| LiveBench long agentic | 39.0% | 44.6% | GPT-5.5 |
| SREBench (Vals AI) | 0.4% | 3.8% | GPT-5.5 |
| Finance Agent (Vals AI) | 53.9% | 51.8% | Claude Sonnet 5 |
| Tax Agent Bench (Vals AI) | 29.4% | 21.8% | Claude Sonnet 5 |
| Legal Research Bench (Vals AI) | 41.8% | 40.4% | Claude Sonnet 5 |
| Excel Modeling Benchmark (Vals AI) | 66.3% | 64.5% | Claude Sonnet 5 |
| Terminal-Bench-Science (Vals AI) | 5.7% | Not measured | Only Claude Sonnet 5 measured |
| Time Horizon Index (Vals AI) | Not measured | 8.3% | Only GPT-5.5 measured |
| τ²-Bench Telecom | Not measured | 93.9% | Only GPT-5.5 measured |
| APEX-Agents | 54.5% | 55.1% | GPT-5.5 |
| Remote Labor Index | Not measured | 6.3% | Only GPT-5.5 measured |
| OSWorld 2.0 | Not measured | 13.0% | Only GPT-5.5 measured |
| DeepResearch Bench | Not measured | 54.0% | Only GPT-5.5 measured |
| PostTrainBench | Not measured | 27.2% | Only GPT-5.5 measured |
| Vending-Bench 2 | $6,378 | $7,524 | GPT-5.5 |
| Neither model has a result on the other 14 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index014
| Benchmark | Claude Sonnet 5 | GPT-5.5 | Leader |
|---|---|---|---|
| GPQA Diamond | 88.9% | 93.2% | GPT-5.5 |
| LiveBench reasoning | 88.7% | 89.7% | GPT-5.5 |
| MMMU Pro (Vals AI) | 83.0% | 88.3% | GPT-5.5 |
| GPQA Diamond (Artificial Analysis run) | 91.1% | 93.5% | GPT-5.5 |
| Humanity's Last Exam (Artificial Analysis run) | 41.3% | 45.8% | GPT-5.5 |
| GPQA Diamond (Epoch AI run) | 90.5% | 90.7% | GPT-5.5 |
| ARC-AGI | Not measured | 95.0% | Only GPT-5.5 measured |
| ARC-AGI-2 | Not measured | 85.0% | Only GPT-5.5 measured |
| SimpleBench | 60.6% | 69.0% | GPT-5.5 |
| Chess puzzles | 45.0% | 63.0% | GPT-5.5 |
| Mystery game puzzles | 35.0% | 56.0% | GPT-5.5 |
| EBR-bench | Not measured | 34.3% | Only GPT-5.5 measured |
| LMArena Text: hard prompts | 1461 | 1489 | GPT-5.5 |
| LMArena Text: expert | 1489 | 1507 | GPT-5.5 |
| LMArena Text: hard prompts in English | 1464 | 1483 | GPT-5.5 |
| LMArena Vision: diagrams | 1293 | 1325 | GPT-5.5 |
| LMArena Vision: homework | 1311 | 1332 | GPT-5.5 |
| Kagi LLM Benchmark | Not measured | 88.8% | 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 | Claude Sonnet 5 | GPT-5.5 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 94.7% | 84.4% | Claude Sonnet 5 |
| FrontierMath, tiers 1 to 3 | 65.6% | 85.3% | GPT-5.5 |
| FrontierMath, tier 4 | 29.3% | 72.5% | GPT-5.5 |
| ProofBench | 77.0% | 50.0% | Claude Sonnet 5 |
| LMArena Text: math | 1467 | 1487 | GPT-5.5 |
| LMArena Text: mathematical work | 1481 | 1496 | GPT-5.5 |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index29
| Benchmark | Claude Sonnet 5 | GPT-5.5 | Leader |
|---|---|---|---|
| MMLU Pro | 87.5% | 88.1% | GPT-5.5 |
| LegalBench (Vals AI) | 83.9% | 86.5% | GPT-5.5 |
| CaseLaw (Vals AI) | Not measured | 66.2% | Only GPT-5.5 measured |
| CorpFin (Vals AI) | 67.0% | 68.4% | GPT-5.5 |
| TaxEval (Vals AI) | 75.6% | 75.0% | Claude Sonnet 5 |
| MortgageTax (Vals AI) | 70.0% | 68.8% | Claude Sonnet 5 |
| MedCode (Vals AI) | 47.5% | 49.1% | GPT-5.5 |
| SimpleQA Verified | 33.7% | 63.0% | GPT-5.5 |
| LMArena Text: science | 1460 | 1485 | GPT-5.5 |
| LMArena Text: medicine and healthcare | 1442 | 1465 | GPT-5.5 |
| LMArena Text: legal and government | 1454 | 1491 | GPT-5.5 |
| LMArena Text: business and finance | 1436 | 1478 | GPT-5.5 |
| FACTS Benchmark Suite | Not measured | 66.7% | 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 index54
| Benchmark | Claude Sonnet 5 | GPT-5.5 | Leader |
|---|---|---|---|
| Design Arena: websites | 1274 | 1256 | Claude Sonnet 5 |
| Design Arena: UI components | 1277 | 1257 | Claude Sonnet 5 |
| Design Arena: game dev | 1277 | 1293 | GPT-5.5 |
| Design Arena: data viz | 1251 | 1264 | GPT-5.5 |
| Design Arena: 3D | 1261 | 1197 | Claude Sonnet 5 |
| Design Arena: all code categories | 1275 | 1260 | Claude Sonnet 5 |
| Design Arena: SVG | 1192 | 1234 | GPT-5.5 |
| Design Arena: ASCII art | 1207 | 1255 | GPT-5.5 |
| LiveBench design | 82.0% | 70.3% | Claude Sonnet 5 |
GeneralLike-for-likePublic boards, shown as published, kept out of the index231
| Benchmark | Claude Sonnet 5 | GPT-5.5 | Leader |
|---|---|---|---|
| LiveBench data analysis | 71.7% | 81.6% | GPT-5.5 |
| Public Benefits Bench (Vals AI) | 66.0% | 60.9% | Claude Sonnet 5 |
| SAGE (Vals AI) | 48.9% | 51.5% | GPT-5.5 |
| MedScribe (Vals AI) | 76.0% | 86.9% | GPT-5.5 |
| Vals Multimodal Index | 68.8% | 68.1% | Claude Sonnet 5 |
| IFBench | Not measured | 75.9% | Only GPT-5.5 measured |
| Long context reasoning (AA-LCR) | 82.0% | 84.3% | GPT-5.5 |
| DTBench | 92.5% | 96.0% | GPT-5.5 |
| LMCA | 50.0% | 54.3% | GPT-5.5 |
| Surface Evolver Bench | 60.0% | 88.1% | GPT-5.5 |
| Furniture assembly | Not measured | 44.2% | Only GPT-5.5 measured |
| ExploitBench | Not measured | 47.4% | Only GPT-5.5 measured |
| CL-bench Life | Not measured | 22.2% | Only GPT-5.5 measured |
| LMArena Text | 1442 | 1471 | GPT-5.5 |
| LMArena Text: instruction following | 1452 | 1478 | GPT-5.5 |
| LMArena Text: creative writing | 1416 | 1455 | GPT-5.5 |
| LMArena Vision | 1273 | 1297 | GPT-5.5 |
| LMArena Text: English | 1450 | 1470 | GPT-5.5 |
| LMArena Text: non-English | 1431 | 1467 | GPT-5.5 |
| LMArena Text: Chinese | 1478 | 1534 | GPT-5.5 |
| LMArena Text: German | 1442 | 1480 | GPT-5.5 |
| LMArena Text: Japanese | 1422 | 1499 | GPT-5.5 |
| LMArena Text: Korean | 1412 | 1460 | GPT-5.5 |
| LMArena Text: French | 1463 | 1485 | GPT-5.5 |
| LMArena Text: Spanish | 1438 | 1468 | GPT-5.5 |
| LMArena Text: Russian | 1450 | 1473 | GPT-5.5 |
| LMArena Text: Polish | 1425 | 1465 | GPT-5.5 |
| LMArena Text: multi-turn | 1453 | 1476 | GPT-5.5 |
| LMArena Text: longer queries | 1462 | 1484 | GPT-5.5 |
| LMArena Text: writing and language | 1436 | 1466 | GPT-5.5 |
| LMArena Text: entertainment and media | 1411 | 1449 | GPT-5.5 |
| LMArena Vision: English | 1275 | 1292 | GPT-5.5 |
| LMArena Vision: Chinese | 1331 | 1360 | GPT-5.5 |
| LMArena Vision: reading text | 1288 | 1306 | GPT-5.5 |
| LMArena Vision: humor | 1261 | 1293 | GPT-5.5 |
| LMArena Vision: recognizing things | Not measured | 1231 | Only GPT-5.5 measured |
| LMArena Vision: creative writing | 1246 | 1301 | GPT-5.5 |
| LMArena Document | 1466 | 1486 | GPT-5.5 |
| Neither model has a result on the other 8 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Claude Sonnet 5 | GPT-5.5 | 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
Claude Sonnet 5 costs less
Repository review
50K input + 3K output tokens
Claude Sonnet 5 costs less
Agent loop
200K input + 10K output tokens
Claude Sonnet 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 | Anthropic Claude Sonnet 5 | OpenAI GPT-5.5 |
|---|---|---|
| Maker | Anthropic | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | June 30, 2026 | April 24, 2026 |
| Context window | 1M | 1.05M |
| Input $/Mtok | $2.00 | $5.00 |
| Output $/Mtok | $10.00 | $30.00 |
| Coding index | 57.7 | 71.3 |
| Independent measurements behind it | 6 | 5 |
| Cost per solved task | $1.87 | $1.65 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Claude Sonnet 5 better than GPT-5.5 for coding?
Pick GPT-5.5 for coding: it scores 71.3 on the Vibe Coding Index against 57.7 for Claude Sonnet 5, though on 5 benchmarks against 6. Pick Claude Sonnet 5 for output tokens 3.0x cheaper ($10.00 vs $30.00 per million) and work measured by LMArena WebDev or Vibe Code Bench (Vals AI), where it leads.
Which is cheaper, Claude Sonnet 5 or GPT-5.5?
Claude Sonnet 5 costs $2.00 per million input tokens and $10.00 per million output tokens; GPT-5.5 costs $5.00 and $30.00. Per solved SWE-bench Verified task, Claude Sonnet 5 costs $1.87 and GPT-5.5 $1.65.
Which has the bigger context window, Claude Sonnet 5 or GPT-5.5?
GPT-5.5, with 1.05M tokens against 1M.
How many benchmarks is the Claude Sonnet 5 vs GPT-5.5 comparison based on?
114 benchmarks have a result for both models as of October 22, 2026. Claude Sonnet 5's coding index rests on 6 independent benchmarks and GPT-5.5's on 5. Where only one model has a result, the page says so instead of naming a winner.