Claude Opus 5.5 vs GPT-6.1 Sol
Updated October 20, 2026. 70 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Claude Opus 5.5 for coding: it scores 92.2 on the Vibe Coding Index against 88.7 for GPT-6.1 Sol.
Pick GPT-6.1 Sol when output tokens cost 2.0x less, or when the context window is larger, 1.05M against 1M tokens.
- Shared results
- 70
- Claude Opus 5.5 only
- 35
- GPT-6.1 Sol only
- 0
- 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
Claude Opus 5.5
Claude Opus 5.5 scores 92.2 against 88.7.
2 benchmarks behind each score
Intelligence
AA Intelligence Index
Claude Opus 5.5
Claude Opus 5.5 leads, 57.6 against 51.8.
Same board, both measured
Web design
Design Arena: websites
Claude Opus 5.5
Claude Opus 5.5 leads, 1336 against 1320.
Same board, both measured
General
Vals Index
Claude Opus 5.5
Claude Opus 5.5 leads, 70.2% against 63.9%.
Same board, both measured
Long documents
Listed context window
GPT-6.1 Sol
GPT-6.1 Sol takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-6.1 Sol
Claude Opus 5.5 $0.014, GPT-6.1 Sol $0.0070 per turn.
List prices
At a glance
- Coding index
- Claude Opus 5.5 92.2 from 2 benchmarks, GPT-6.1 Sol 88.7 from 2 benchmarks.
- Widest category
- Agentic work, 10.0 points apart on average over 16 shared benchmarks.
- Widest single gap
- CyberBench (Vals AI): Claude Opus 5.5 74.6% against GPT-6.1 Sol 39.3%, 35.3 points apart on a 0 to 100 scale.
- Output price
- Claude Opus 5.5 $20.00 against GPT-6.1 Sol $10.00 per million output tokens, 2.0x apart.
- Context window
- Claude Opus 5.5 takes 1M tokens, GPT-6.1 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 Opus 5.5 | Bars | GPT-6.1 Sol | Ties |
|---|---|---|---|---|
| Coding | 12 | 3 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 9 | 7 | ||
| Reasoning | 5 | 5 | 1 tie | |
| Math | 1 | 2 | 1 tie | |
| Knowledge | 1 | 1 | ||
| Web design | 7 | 0 | ||
| General | 11 | 2 | ||
| All shared boards | 48 | 20 | 2 ties |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index123
| Benchmark | Claude Opus 5.5 | GPT-6.1 Sol | Leader |
|---|---|---|---|
| LiveBench coding | 96.3% | 96.0% | Claude Opus 5.5 |
| LMArena WebDev | 1807 | 1753 | Claude Opus 5.5 |
| Terminal-Bench 4 (Vals AI) | 65.2% | 55.0% | Claude Opus 5.5 |
| Vibe Code Bench (Vals AI) | 90.3% | 88.9% | Claude Opus 5.5 |
| Code migration (Vals AI) | 66.7% | 65.1% | Claude Opus 5.5 |
| ProgramBench (Vals AI) | 18.5% | 3.0% | Claude Opus 5.5 |
| IOI (Vals AI) | 95.1% | 96.9% | GPT-6.1 Sol |
| Terminal-Bench 2.1 (Vals AI) | 87.6% | Not measured | Only Claude Opus 5.5 measured |
| SWE-bench Multimodal (Vals AI) | 70.2% | 43.5% | Claude Opus 5.5 |
| Vibe Code Bench 1-100 (Vals AI) | 30.4% | Not measured | Only Claude Opus 5.5 measured |
| CyberBench (Vals AI) | 74.6% | 39.3% | Claude Opus 5.5 |
| SciCode | 66.9% | 55.8% | Claude Opus 5.5 |
| FrontierCode | 54.6% | 50.2% | Claude Opus 5.5 |
| FrontierSWE | 62.3% | Not measured | Only Claude Opus 5.5 measured |
| MirrorCode | 77.4% | Not measured | Only Claude Opus 5.5 measured |
| ALE-Bench | 2147.4 | 2743.8 | GPT-6.1 Sol |
| LMArena Text: coding | 1545 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: software and IT | 1538 | Not measured | Only Claude Opus 5.5 measured |
| LMArena WebDev: React | 1855 | 1754 | Claude Opus 5.5 |
| LMArena WebDev: HTML | 1753 | 1800 | GPT-6.1 Sol |
| LMArena WebDev: from an image | 1753 | 1702 | Claude Opus 5.5 |
| Neither model has a result on the other 17 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Claude Opus 5.5 | GPT-6.1 Sol | Leader |
|---|---|---|---|
| AA Intelligence Index | 57.6 | 51.8 | Claude Opus 5.5 |
| Epoch Capabilities Index | 166.8 | 166.3 | Claude Opus 5.5 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index97
| Benchmark | Claude Opus 5.5 | GPT-6.1 Sol | Leader |
|---|---|---|---|
| Design Arena: agents building web apps | 1318 | Not measured | Only Claude Opus 5.5 measured |
| Design Arena: agents building mobile apps | 1323 | 1198 | Claude Opus 5.5 |
| LiveBench research | 85.0% | 83.5% | Claude Opus 5.5 |
| LiveBench browser | 80.0% | 88.0% | GPT-6.1 Sol |
| LiveBench long agentic | 85.0% | 73.0% | Claude Opus 5.5 |
| SREBench (Vals AI) | 33.6% | 50.8% | GPT-6.1 Sol |
| Finance Agent (Vals AI) | 58.6% | 52.0% | Claude Opus 5.5 |
| Tax Agent Bench (Vals AI) | 45.6% | 21.8% | Claude Opus 5.5 |
| Legal Research Bench (Vals AI) | 50.5% | 38.5% | Claude Opus 5.5 |
| Harvey's Legal Agent Benchmark (Vals AI) | 9.2% | 6.3% | Claude Opus 5.5 |
| Excel Modeling Benchmark (Vals AI) | 75.9% | 70.8% | Claude Opus 5.5 |
| BioMysteryBench (Vals AI) | 79.3% | 79.6% | GPT-6.1 Sol |
| Terminal-Bench-Science (Vals AI) | 47.1% | 52.9% | GPT-6.1 Sol |
| Vals Science Index | 58.7% | 59.6% | GPT-6.1 Sol |
| Time Horizon Index (Vals AI) | 91.3% | Not measured | Only Claude Opus 5.5 measured |
| CUA-bench (Vals AI) | 14.0% | Not measured | Only Claude Opus 5.5 measured |
| Robo-bench (Vals AI) | 14.6% | 28.3% | GPT-6.1 Sol |
| APEX-Agents | 73.5% | 60.0% | Claude Opus 5.5 |
| Remote Labor Index | 21.3% | Not measured | Only Claude Opus 5.5 measured |
| SpireClimb | 3.3% | 24.7% | GPT-6.1 Sol |
| Vending-Bench 2 | $9,235 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Search | 1213 | Not measured | Only Claude Opus 5.5 measured |
| Neither model has a result on the other 17 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index55
| Benchmark | Claude Opus 5.5 | GPT-6.1 Sol | Leader |
|---|---|---|---|
| LiveBench reasoning | 92.2% | 92.6% | GPT-6.1 Sol |
| MysteryMechanism (Vals AI) | 49.5% | 46.4% | Claude Opus 5.5 |
| Humanity's Last Exam (Artificial Analysis run) | 61.4% | 52.9% | Claude Opus 5.5 |
| GPQA Diamond (Epoch AI run) | 90.6% | 95.4% | GPT-6.1 Sol |
| ARC-AGI | 98.5% | 98.5% | Tie |
| ARC-AGI-2 | 93.3% | 94.2% | GPT-6.1 Sol |
| Chess puzzles | 67.0% | 68.0% | GPT-6.1 Sol |
| Mystery game puzzles | 71.0% | 80.0% | GPT-6.1 Sol |
| EBR-bench | 71.4% | 54.3% | Claude Opus 5.5 |
| LMArena Text: hard prompts | 1535 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: expert | 1550 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: hard prompts in English | 1533 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Vision: diagrams | 1345 | 1306 | Claude Opus 5.5 |
| LMArena Vision: homework | 1362 | 1356 | Claude Opus 5.5 |
| Neither model has a result on the other 7 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index12
| Benchmark | Claude Opus 5.5 | GPT-6.1 Sol | Leader |
|---|---|---|---|
| OTIS Mock AIME | 100.0% | 100.0% | Tie |
| FrontierMath, tiers 1 to 3 | 91.2% | 93.7% | GPT-6.1 Sol |
| FrontierMath, tier 4 | 95.0% | 100.0% | GPT-6.1 Sol |
| ProofBench | 100.0% | 99.0% | Claude Opus 5.5 |
| LMArena Text: math | 1508 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: mathematical work | 1506 | Not measured | Only Claude Opus 5.5 measured |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index11
| Benchmark | Claude Opus 5.5 | GPT-6.1 Sol | Leader |
|---|---|---|---|
| MedCode (Vals AI) | 49.8% | 48.8% | Claude Opus 5.5 |
| SimpleQA Verified | 72.2% | 73.9% | GPT-6.1 Sol |
| LMArena Text: science | 1522 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: medicine and healthcare | 1513 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: legal and government | 1510 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: business and finance | 1492 | Not measured | Only Claude Opus 5.5 measured |
| Neither model has a result on the other 11 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index70
| Benchmark | Claude Opus 5.5 | GPT-6.1 Sol | Leader |
|---|---|---|---|
| Design Arena: websites | 1336 | 1320 | Claude Opus 5.5 |
| Design Arena: UI components | 1386 | 1317 | Claude Opus 5.5 |
| Design Arena: game dev | 1458 | 1390 | Claude Opus 5.5 |
| Design Arena: data viz | 1397 | 1321 | Claude Opus 5.5 |
| Design Arena: 3D | 1477 | 1461 | Claude Opus 5.5 |
| Design Arena: all code categories | 1390 | 1346 | Claude Opus 5.5 |
| Design Arena: SVG | 1332 | Not measured | Only Claude Opus 5.5 measured |
| LiveBench design | 86.9% | 82.1% | Claude Opus 5.5 |
| Neither model has a result on the other 1 board here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index112
| Benchmark | Claude Opus 5.5 | GPT-6.1 Sol | Leader |
|---|---|---|---|
| Vals Index | 70.2% | 63.9% | Claude Opus 5.5 |
| LiveBench data analysis | 80.3% | 82.7% | GPT-6.1 Sol |
| Public Benefits Bench (Vals AI) | 70.6% | 59.3% | Claude Opus 5.5 |
| SAGE (Vals AI) | 45.8% | 46.5% | GPT-6.1 Sol |
| MedScribe (Vals AI) | 91.4% | 86.5% | Claude Opus 5.5 |
| Long context reasoning (AA-LCR) | 84.7% | 84.0% | Claude Opus 5.5 |
| DTBench | 98.9% | 96.5% | Claude Opus 5.5 |
| LMCA | 68.2% | 62.8% | Claude Opus 5.5 |
| Furniture assembly | 83.3% | 80.0% | Claude Opus 5.5 |
| LMArena Text | 1516 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: instruction following | 1536 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: creative writing | 1534 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Vision | 1321 | 1288 | Claude Opus 5.5 |
| LMArena Text: English | 1517 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: non-English | 1507 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: Chinese | 1584 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: French | 1505 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: Spanish | 1519 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: Russian | 1519 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: multi-turn | 1502 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: longer queries | 1531 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: writing and language | 1534 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Text: entertainment and media | 1511 | Not measured | Only Claude Opus 5.5 measured |
| LMArena Vision: English | 1317 | 1274 | Claude Opus 5.5 |
| LMArena Vision: reading text | 1326 | 1289 | Claude Opus 5.5 |
| LMArena Vision: creative writing | 1320 | 1301 | Claude Opus 5.5 |
| Neither model has a result on the other 20 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Claude Opus 5.5 | GPT-6.1 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
GPT-6.1 Sol costs less
Repository review
50K input + 3K output tokens
GPT-6.1 Sol costs less
Agent loop
200K input + 10K output tokens
GPT-6.1 Sol 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 Opus 5.5 | OpenAI GPT-6.1 Sol |
|---|---|---|
| Maker | Anthropic | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | September 22, 2026 | September 29, 2026 |
| Context window | 1M | 1.05M |
| Input $/Mtok | $4.00 | $2.00 |
| Output $/Mtok | $20.00 | $10.00 |
| Coding index | 92.2 | 88.7 |
| Independent measurements behind it | 2 | 2 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Claude Opus 5.5 better than GPT-6.1 Sol for coding?
Pick Claude Opus 5.5 for coding: it scores 92.2 on the Vibe Coding Index against 88.7 for GPT-6.1 Sol. Pick GPT-6.1 Sol when output tokens cost 2.0x less, or when the context window is larger, 1.05M against 1M tokens.
Which is cheaper, Claude Opus 5.5 or GPT-6.1 Sol?
Claude Opus 5.5 costs $4.00 per million input tokens and $20.00 per million output tokens; GPT-6.1 Sol costs $2.00 and $10.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Claude Opus 5.5 or GPT-6.1 Sol?
GPT-6.1 Sol, with 1.05M tokens against 1M.
How many benchmarks is the Claude Opus 5.5 vs GPT-6.1 Sol comparison based on?
70 benchmarks have a result for both models as of October 20, 2026. Claude Opus 5.5's coding index rests on 2 independent benchmarks and GPT-6.1 Sol's on 2. Where only one model has a result, the page says so instead of naming a winner.