Claude Sonnet 5 vs GPT-5.6 Sol
GPT-5.6 Sol leads Claude Sonnet 5 on coding, 73.5 to 57.7 on the Vibe Coding Index, and Claude Sonnet 5 costs 2.0x less per output token ($10.00 vs $20.00 per million). Updated October 21, 2026; 119 benchmarks have a result for both.
Claude Sonnet 5 or GPT-5.6 Sol: which to pick
Pick GPT-5.6 Sol for coding: it scores 73.5 on the Vibe Coding Index against 57.7 for Claude Sonnet 5.
Pick Claude Sonnet 5 for output tokens 2.0x cheaper ($10.00 vs $20.00 per million) and work measured by Vibe Code Bench (Vals AI) or LiveBench research, where it leads.
- Shared results
- 119
- Claude Sonnet 5 only
- 2
- GPT-5.6 Sol 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-5.6 Sol
GPT-5.6 Sol scores 73.5 against 57.7.
6 benchmarks behind each score
Intelligence
AA Intelligence Index
GPT-5.6 Sol
GPT-5.6 Sol leads, 47.0 against 38.2.
Same board, both measured
Agentic work
AA Agentic Index
GPT-5.6 Sol
GPT-5.6 Sol leads, 50.2 against 43.6.
Same board, both measured
Reasoning
GPQA Diamond
GPT-5.6 Sol
GPT-5.6 Sol leads, 95.2% against 88.9%.
Same board, both measured
Knowledge
MMLU Pro
GPT-5.6 Sol
GPT-5.6 Sol leads, 89.1% against 87.5%.
Same board, both measured
Web design
Design Arena: websites
GPT-5.6 Sol
GPT-5.6 Sol leads, 1321 against 1274.
Same board, both measured
Long documents
Listed context window
GPT-5.6 Sol
GPT-5.6 Sol 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-5.6 Sol $0.014 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GPT-5.6 Sol
Claude Sonnet 5 $1.87, GPT-5.6 Sol $1.20.
Published attempt cost and pass rate
At a glance
- Coding index
- Claude Sonnet 5 57.7 from 6 benchmarks, GPT-5.6 Sol 73.5 from 6 benchmarks.
- Widest category
- Math, 15.3 points apart on average over 6 shared benchmarks.
- Widest single gap
- FrontierMath, tier 4: Claude Sonnet 5 29.3% against GPT-5.6 Sol 82.9%, 53.7 points apart on a 0 to 100 scale.
- Output price
- Claude Sonnet 5 $10.00 against GPT-5.6 Sol $20.00 per million output tokens, 2.0x apart.
- Context window
- Claude Sonnet 5 takes 1M tokens, GPT-5.6 Sol 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-5.6 Sol | Ties |
|---|---|---|---|---|
| Coding | 1 | 24 | ||
| Intelligence | 0 | 2 | ||
| Agentic work | 2 | 16 | 1 tie | |
| Reasoning | 1 | 13 | ||
| Math | 0 | 6 | ||
| Knowledge | 6 | 5 | ||
| Web design | 1 | 8 | ||
| General | 2 | 31 | ||
| All shared boards | 13 | 105 | 1 tie |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index124
| Benchmark | Claude Sonnet 5 | GPT-5.6 Sol | Leader |
|---|---|---|---|
| LiveBench coding | 74.7% | 89.7% | GPT-5.6 Sol |
| LMArena WebDev | 1540 | 1616 | GPT-5.6 Sol |
| AA Coding Index | 71.5 | 77.4 | GPT-5.6 Sol |
| LiveCodeBench (Vals AI) | 82.4% | 82.6% | GPT-5.6 Sol |
| SWE-bench Verified (Vals AI) | 79.6% | 96.2% | GPT-5.6 Sol |
| Terminal-Bench 4 (Vals AI) | 10.6% | 37.9% | GPT-5.6 Sol |
| Vibe Code Bench (Vals AI) | 81.3% | 80.5% | Claude Sonnet 5 |
| Code migration (Vals AI) | 44.4% | 52.9% | GPT-5.6 Sol |
| ProgramBench (Vals AI) | 0.0% | 1.5% | GPT-5.6 Sol |
| IOI (Vals AI) | 45.0% | 91.2% | GPT-5.6 Sol |
| Terminal-Bench 2.1 (Vals AI) | 74.5% | 85.8% | GPT-5.6 Sol |
| Vibe Code Bench 1-100 (Vals AI) | 13.8% | 20.0% | GPT-5.6 Sol |
| SkillsBench (Vals AI) | 46.5% | 54.1% | GPT-5.6 Sol |
| CyberBench (Vals AI) | 70.3% | 76.3% | GPT-5.6 Sol |
| SciCode | 54.3% | 57.8% | GPT-5.6 Sol |
| Terminal-Bench Hard (Artificial Analysis run) | Not measured | 65.9% | Only GPT-5.6 Sol measured |
| FrontierCode | 42.7% | 47.5% | GPT-5.6 Sol |
| FrontierSWE | Not measured | 32.2% | Only GPT-5.6 Sol measured |
| GSO-Bench | 37.3% | 76.5% | GPT-5.6 Sol |
| WeirdML | 68.8% | 88.8% | GPT-5.6 Sol |
| MirrorCode | Not measured | 20.0% | Only GPT-5.6 Sol measured |
| ALE-Bench | 1463.1 | 2176.9 | GPT-5.6 Sol |
| LMArena Text: coding | 1483 | 1496 | GPT-5.6 Sol |
| LMArena Text: software and IT | 1474 | 1489 | GPT-5.6 Sol |
| LMArena WebDev: React | 1541 | 1620 | GPT-5.6 Sol |
| LMArena WebDev: HTML | 1527 | 1618 | GPT-5.6 Sol |
| LMArena WebDev: from an image | 1540 | 1609 | GPT-5.6 Sol |
| SciCode | 10.7% | 10.8% | GPT-5.6 Sol |
| 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-5.6 Sol | Leader |
|---|---|---|---|
| AA Intelligence Index | 38.2 | 47.0 | GPT-5.6 Sol |
| Epoch Capabilities Index | 156.9 | 162.8 | GPT-5.6 Sol |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index216
| Benchmark | Claude Sonnet 5 | GPT-5.6 Sol | Leader |
|---|---|---|---|
| AA Agentic Index | 43.6 | 50.2 | GPT-5.6 Sol |
| Design Arena: agents building web apps | 1245 | 1245 | Tie |
| Design Arena: agents building full-stack apps | 1249 | 1261 | GPT-5.6 Sol |
| Design Arena: agents building mobile apps | 1215 | 1248 | GPT-5.6 Sol |
| Design Arena: agents building Android apps | 1225 | 1239 | GPT-5.6 Sol |
| Design Arena: agents building Godot games | 1225 | 1260 | GPT-5.6 Sol |
| Design Arena: agents building games | 1227 | 1267 | GPT-5.6 Sol |
| Design Arena: HTML slides | 1218 | 1286 | GPT-5.6 Sol |
| Design Arena: PowerPoint slides | 1216 | 1241 | GPT-5.6 Sol |
| Design Arena: spreadsheets | 1021 | Not measured | Only Claude Sonnet 5 measured |
| LiveBench research | 82.8% | 54.5% | Claude Sonnet 5 |
| LiveBench browser | 72.0% | 88.0% | GPT-5.6 Sol |
| LiveBench long agentic | 39.0% | 48.5% | GPT-5.6 Sol |
| SREBench (Vals AI) | 0.4% | 30.5% | GPT-5.6 Sol |
| Finance Agent (Vals AI) | 53.9% | 53.8% | Claude Sonnet 5 |
| Tax Agent Bench (Vals AI) | 29.4% | 31.1% | GPT-5.6 Sol |
| Legal Research Bench (Vals AI) | 41.8% | 48.1% | GPT-5.6 Sol |
| Excel Modeling Benchmark (Vals AI) | 66.3% | 72.3% | GPT-5.6 Sol |
| BioMysteryBench (Vals AI) | Not measured | 71.1% | Only GPT-5.6 Sol measured |
| Terminal-Bench-Science (Vals AI) | 5.7% | 20.0% | GPT-5.6 Sol |
| Vals Science Index | Not measured | 41.5% | Only GPT-5.6 Sol measured |
| Time Horizon Index (Vals AI) | Not measured | 23.8% | Only GPT-5.6 Sol measured |
| CUA-bench (Vals AI) | Not measured | 8.3% | Only GPT-5.6 Sol measured |
| τ²-Bench Telecom | Not measured | 85.1% | Only GPT-5.6 Sol measured |
| APEX-Agents | 54.5% | Not measured | Only Claude Sonnet 5 measured |
| OSWorld 2.0 | Not measured | 27.3% | Only GPT-5.6 Sol measured |
| BALROG | Not measured | 60.0% | Only GPT-5.6 Sol measured |
| PostTrainBench | Not measured | 36.2% | Only GPT-5.6 Sol measured |
| Vending-Bench 2 | $6,378 | $9,619 | GPT-5.6 Sol |
| LMArena Search | Not measured | 1261 | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 11 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index113
| Benchmark | Claude Sonnet 5 | GPT-5.6 Sol | Leader |
|---|---|---|---|
| GPQA Diamond | 88.9% | 95.2% | GPT-5.6 Sol |
| LiveBench reasoning | 88.7% | 91.7% | GPT-5.6 Sol |
| MysteryMechanism (Vals AI) | Not measured | 33.3% | Only GPT-5.6 Sol measured |
| MMMU Pro (Vals AI) | 83.0% | 88.8% | GPT-5.6 Sol |
| GPQA Diamond (Artificial Analysis run) | 91.1% | 94.1% | GPT-5.6 Sol |
| Humanity's Last Exam (Artificial Analysis run) | 41.3% | 49.5% | GPT-5.6 Sol |
| GPQA Diamond (Epoch AI run) | 90.5% | 93.5% | GPT-5.6 Sol |
| ARC-AGI | Not measured | 97.5% | Only GPT-5.6 Sol measured |
| ARC-AGI-2 | Not measured | 92.5% | Only GPT-5.6 Sol measured |
| SimpleBench | 60.6% | 64.8% | GPT-5.6 Sol |
| Chess puzzles | 45.0% | 59.0% | GPT-5.6 Sol |
| Mystery game puzzles | 35.0% | 58.0% | GPT-5.6 Sol |
| EBR-bench | Not measured | 44.8% | Only GPT-5.6 Sol measured |
| LMArena Text: hard prompts | 1461 | 1483 | GPT-5.6 Sol |
| LMArena Text: expert | 1489 | 1517 | GPT-5.6 Sol |
| LMArena Text: hard prompts in English | 1464 | 1477 | GPT-5.6 Sol |
| LMArena Vision: diagrams | 1293 | 1305 | GPT-5.6 Sol |
| LMArena Vision: homework | 1311 | 1305 | Claude Sonnet 5 |
| Kagi LLM Benchmark | Not measured | 67.0% | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 3 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index06
| Benchmark | Claude Sonnet 5 | GPT-5.6 Sol | Leader |
|---|---|---|---|
| OTIS Mock AIME | 94.7% | 100.0% | GPT-5.6 Sol |
| FrontierMath, tiers 1 to 3 | 65.6% | 89.1% | GPT-5.6 Sol |
| FrontierMath, tier 4 | 29.3% | 82.9% | GPT-5.6 Sol |
| ProofBench | 77.0% | 83.0% | GPT-5.6 Sol |
| LMArena Text: math | 1467 | 1473 | GPT-5.6 Sol |
| LMArena Text: mathematical work | 1481 | 1496 | GPT-5.6 Sol |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index65
| Benchmark | Claude Sonnet 5 | GPT-5.6 Sol | Leader |
|---|---|---|---|
| MMLU Pro | 87.5% | 89.1% | GPT-5.6 Sol |
| LegalBench (Vals AI) | 83.9% | 87.0% | GPT-5.6 Sol |
| CorpFin (Vals AI) | 67.0% | 64.4% | Claude Sonnet 5 |
| TaxEval (Vals AI) | 75.6% | 74.8% | Claude Sonnet 5 |
| MortgageTax (Vals AI) | 70.0% | 67.3% | Claude Sonnet 5 |
| MedCode (Vals AI) | 47.5% | 44.0% | Claude Sonnet 5 |
| SimpleQA Verified | 33.7% | 69.7% | GPT-5.6 Sol |
| LMArena Text: science | 1460 | 1455 | Claude Sonnet 5 |
| LMArena Text: medicine and healthcare | 1442 | 1431 | Claude Sonnet 5 |
| LMArena Text: legal and government | 1454 | 1476 | GPT-5.6 Sol |
| LMArena Text: business and finance | 1436 | 1457 | GPT-5.6 Sol |
| FACTS Benchmark Suite | Not measured | 52.4% | Only GPT-5.6 Sol measured |
| Neither model has a result on the other 6 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index18
| Benchmark | Claude Sonnet 5 | GPT-5.6 Sol | Leader |
|---|---|---|---|
| Design Arena: websites | 1274 | 1321 | GPT-5.6 Sol |
| Design Arena: UI components | 1280 | 1336 | GPT-5.6 Sol |
| Design Arena: game dev | 1278 | 1368 | GPT-5.6 Sol |
| Design Arena: data viz | 1251 | 1322 | GPT-5.6 Sol |
| Design Arena: 3D | 1261 | 1386 | GPT-5.6 Sol |
| Design Arena: all code categories | 1276 | 1341 | GPT-5.6 Sol |
| Design Arena: SVG | 1193 | 1316 | GPT-5.6 Sol |
| Design Arena: ASCII art | 1207 | 1304 | GPT-5.6 Sol |
| LiveBench design | 82.0% | 81.6% | Claude Sonnet 5 |
GeneralLike-for-likePublic boards, shown as published, kept out of the index231
| Benchmark | Claude Sonnet 5 | GPT-5.6 Sol | Leader |
|---|---|---|---|
| LiveBench data analysis | 71.7% | 79.8% | GPT-5.6 Sol |
| Public Benefits Bench (Vals AI) | 66.0% | 66.5% | GPT-5.6 Sol |
| SAGE (Vals AI) | 48.9% | 52.6% | GPT-5.6 Sol |
| MedScribe (Vals AI) | 76.0% | 85.2% | GPT-5.6 Sol |
| Vals Multimodal Index | 68.8% | 72.6% | GPT-5.6 Sol |
| IFBench | Not measured | 72.7% | Only GPT-5.6 Sol measured |
| Long context reasoning (AA-LCR) | 82.0% | 84.0% | GPT-5.6 Sol |
| DTBench | 92.5% | 95.7% | GPT-5.6 Sol |
| LMCA | 50.0% | 58.5% | GPT-5.6 Sol |
| Surface Evolver Bench | 60.0% | 93.1% | GPT-5.6 Sol |
| Furniture assembly | Not measured | 56.7% | Only GPT-5.6 Sol measured |
| LMArena Text | 1442 | 1457 | GPT-5.6 Sol |
| LMArena Text: instruction following | 1452 | 1483 | GPT-5.6 Sol |
| LMArena Text: creative writing | 1416 | 1449 | GPT-5.6 Sol |
| LMArena Vision | 1273 | 1281 | GPT-5.6 Sol |
| LMArena Text: English | 1450 | 1457 | GPT-5.6 Sol |
| LMArena Text: non-English | 1431 | 1451 | GPT-5.6 Sol |
| LMArena Text: Chinese | 1478 | 1525 | GPT-5.6 Sol |
| LMArena Text: German | 1442 | 1476 | GPT-5.6 Sol |
| LMArena Text: Japanese | 1422 | 1472 | GPT-5.6 Sol |
| LMArena Text: Korean | 1412 | 1442 | GPT-5.6 Sol |
| LMArena Text: French | 1463 | 1472 | GPT-5.6 Sol |
| LMArena Text: Spanish | 1438 | 1443 | GPT-5.6 Sol |
| LMArena Text: Russian | 1450 | 1471 | GPT-5.6 Sol |
| LMArena Text: Polish | 1425 | 1459 | GPT-5.6 Sol |
| LMArena Text: multi-turn | 1453 | 1461 | GPT-5.6 Sol |
| LMArena Text: longer queries | 1462 | 1481 | GPT-5.6 Sol |
| LMArena Text: writing and language | 1436 | 1462 | GPT-5.6 Sol |
| LMArena Text: entertainment and media | 1411 | 1450 | GPT-5.6 Sol |
| LMArena Vision: English | 1275 | 1280 | GPT-5.6 Sol |
| LMArena Vision: Chinese | 1331 | 1313 | Claude Sonnet 5 |
| LMArena Vision: reading text | 1288 | 1290 | GPT-5.6 Sol |
| LMArena Vision: humor | 1261 | 1246 | Claude Sonnet 5 |
| LMArena Vision: creative writing | 1246 | 1283 | GPT-5.6 Sol |
| LMArena Document | 1466 | 1483 | GPT-5.6 Sol |
| Neither model has a result on the other 11 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Claude Sonnet 5 | GPT-5.6 Sol | 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-5.6 Sol |
|---|---|---|
| Maker | Anthropic | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | June 30, 2026 | July 9, 2026 |
| Context window | 1M | 1.05M |
| Input $/Mtok | $2.00 | $4.00 |
| Output $/Mtok | $10.00 | $20.00 |
| Coding index | 57.7 | 73.5 |
| Independent measurements behind it | 6 | 6 |
| Cost per solved task | $1.87 | $1.20 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Claude Sonnet 5 better than GPT-5.6 Sol for coding?
Pick GPT-5.6 Sol for coding: it scores 73.5 on the Vibe Coding Index against 57.7 for Claude Sonnet 5. Pick Claude Sonnet 5 for output tokens 2.0x cheaper ($10.00 vs $20.00 per million) and work measured by Vibe Code Bench (Vals AI) or LiveBench research, where it leads.
Which is cheaper, Claude Sonnet 5 or GPT-5.6 Sol?
Claude Sonnet 5 costs $2.00 per million input tokens and $10.00 per million output tokens; GPT-5.6 Sol costs $4.00 and $20.00. Per solved SWE-bench Verified task, Claude Sonnet 5 costs $1.87 and GPT-5.6 Sol $1.20.
Which has the bigger context window, Claude Sonnet 5 or GPT-5.6 Sol?
GPT-5.6 Sol, with 1.05M tokens against 1M.
How many benchmarks is the Claude Sonnet 5 vs GPT-5.6 Sol comparison based on?
119 benchmarks have a result for both models as of October 21, 2026. Claude Sonnet 5's coding index rests on 6 independent benchmarks and GPT-5.6 Sol's on 6. Where only one model has a result, the page says so instead of naming a winner.