Claude Opus 4.7 vs GPT-5.6 Sol Pro
GPT-5.6 Sol Pro costs 1.3x less per output token than Claude Opus 4.7 ($20.00 vs $25.00 per million). Updated October 22, 2026; 7 benchmarks have a result for both.
Claude Opus 4.7 or GPT-5.6 Sol Pro: which to pick
Only Claude Opus 4.7 has a coding score, 67.5 on the Vibe Coding Index; GPT-5.6 Sol Pro has none, so the two cannot be ranked on coding.
Pick GPT-5.6 Sol Pro for output tokens 1.3x cheaper ($20.00 vs $25.00 per million) and a larger context window (1.05M against 1M tokens).
- Shared results
- 7
- Claude Opus 4.7 only
- 96
- GPT-5.6 Sol Pro only
- 0
- Like-for-like categories
- 5 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
No call
Only Claude Opus 4.7 has a coding score, so no call is made.
One side not measured
Intelligence
AA Intelligence Index
No call
Only Claude Opus 4.7 has a AA Intelligence Index result, 40.7.
Directional only
Agentic work
AA Agentic Index
No call
Only Claude Opus 4.7 has a AA Agentic Index result, 38.6.
Directional only
Reasoning
GPQA Diamond
No call
Only Claude Opus 4.7 has a GPQA Diamond result, 90.2%.
Directional only
Math
AIME
No call
Only Claude Opus 4.7 has a AIME result, 96.3%.
Directional only
Knowledge
MMLU Pro
No call
Only Claude Opus 4.7 has a MMLU Pro result, 89.9%.
Directional only
Long documents
Listed context window
GPT-5.6 Sol Pro
GPT-5.6 Sol Pro takes 1.05M tokens against 1M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5.6 Sol Pro
Claude Opus 4.7 $0.018, GPT-5.6 Sol Pro $0.014 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only Claude Opus 4.7 has the number, $2.95.
Directional only
At a glance
- Coding index
- Claude Opus 4.7 67.5 from 4 benchmarks, GPT-5.6 Sol Pro not benchmarked.
- Widest category
- Math, 48.8 points apart on average over 1 shared benchmark.
- Widest single gap
- FrontierMath, tier 4: Claude Opus 4.7 31.7% against GPT-5.6 Sol Pro 80.5%, 48.8 points apart on a 0 to 100 scale.
- Output price
- Claude Opus 4.7 $25.00 against GPT-5.6 Sol Pro $20.00 per million output tokens, 1.3x apart.
- Context window
- Claude Opus 4.7 takes 1M tokens, GPT-5.6 Sol Pro 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 4.7 | Bars | GPT-5.6 Sol Pro | Ties |
|---|---|---|---|---|
| Coding | 0 | 1 | ||
| Agentic work | 0 | 1 | ||
| Reasoning | 0 | 2 | ||
| Math | 0 | 1 | ||
| General | 0 | 2 | ||
| All shared boards | 0 | 7 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index01
| Benchmark | Claude Opus 4.7 | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| LMArena WebDev | 1558 | Not measured | Only Claude Opus 4.7 measured |
| AA Coding Index | 73.6 | Not measured | Only Claude Opus 4.7 measured |
| LiveCodeBench (Vals AI) | 85.1% | Not measured | Only Claude Opus 4.7 measured |
| SWE-bench Verified (Vals AI) | 82.0% | Not measured | Only Claude Opus 4.7 measured |
| Vibe Code Bench (Vals AI) | 71.0% | Not measured | Only Claude Opus 4.7 measured |
| Code migration (Vals AI) | 43.9% | Not measured | Only Claude Opus 4.7 measured |
| ProgramBench (Vals AI) | 0.0% | Not measured | Only Claude Opus 4.7 measured |
| Terminal-Bench 2.1 (Vals AI) | 68.5% | Not measured | Only Claude Opus 4.7 measured |
| Terminal-Bench Hard (Artificial Analysis run) | 54.5% | Not measured | Only Claude Opus 4.7 measured |
| Terminal-Bench | 80.2% | Not measured | Only Claude Opus 4.7 measured |
| FrontierCode | 38.5% | Not measured | Only Claude Opus 4.7 measured |
| GSO-Bench | 44.1% | Not measured | Only Claude Opus 4.7 measured |
| WeirdML | 76.4% | 89.4% | GPT-5.6 Sol Pro |
| MirrorCode | 31.1% | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: coding | 1519 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: software and IT | 1516 | Not measured | Only Claude Opus 4.7 measured |
| LMArena WebDev: React | 1560 | Not measured | Only Claude Opus 4.7 measured |
| LMArena WebDev: HTML | 1554 | Not measured | Only Claude Opus 4.7 measured |
| LMArena WebDev: from an image | 1577 | Not measured | Only Claude Opus 4.7 measured |
| Neither model has a result on the other 20 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Claude Opus 4.7 | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| AA Intelligence Index | 40.7 | Not measured | Only Claude Opus 4.7 measured |
| Epoch Capabilities Index | 156.8 | Not measured | Only Claude Opus 4.7 measured |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Claude Opus 4.7 | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| AA Agentic Index | 38.6 | Not measured | Only Claude Opus 4.7 measured |
| Finance Agent (Vals AI) | 51.5% | Not measured | Only Claude Opus 4.7 measured |
| Tax Agent Bench (Vals AI) | 23.7% | Not measured | Only Claude Opus 4.7 measured |
| Legal Research Bench (Vals AI) | 38.5% | Not measured | Only Claude Opus 4.7 measured |
| Excel Modeling Benchmark (Vals AI) | 63.7% | Not measured | Only Claude Opus 4.7 measured |
| τ²-Bench Telecom | 88.6% | Not measured | Only Claude Opus 4.7 measured |
| APEX-Agents | 49.2% | 51.4% | GPT-5.6 Sol Pro |
| OSWorld 2.0 | 18.2% | Not measured | Only Claude Opus 4.7 measured |
| PostTrainBench | 28.6% | Not measured | Only Claude Opus 4.7 measured |
| Vending-Bench 2 | $10,937 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Search | 1230 | Not measured | Only Claude Opus 4.7 measured |
| Neither model has a result on the other 30 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Claude Opus 4.7 | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| GPQA Diamond | 90.2% | Not measured | Only Claude Opus 4.7 measured |
| MMMU Pro (Vals AI) | 85.5% | Not measured | Only Claude Opus 4.7 measured |
| GPQA Diamond (Artificial Analysis run) | 91.4% | Not measured | Only Claude Opus 4.7 measured |
| Humanity's Last Exam (Artificial Analysis run) | 42.3% | Not measured | Only Claude Opus 4.7 measured |
| GPQA Diamond (Epoch AI run) | 90.2% | Not measured | Only Claude Opus 4.7 measured |
| ARC-AGI | 93.5% | Not measured | Only Claude Opus 4.7 measured |
| ARC-AGI-2 | 75.8% | Not measured | Only Claude Opus 4.7 measured |
| SimpleBench | 61.7% | 71.7% | GPT-5.6 Sol Pro |
| Chess puzzles | 41.0% | 68.0% | GPT-5.6 Sol Pro |
| Mystery game puzzles | 28.0% | Not measured | Only Claude Opus 4.7 measured |
| EBR-bench | 19.0% | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: hard prompts | 1506 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: expert | 1521 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: hard prompts in English | 1508 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Vision: diagrams | 1336 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Vision: homework | 1337 | Not measured | Only Claude Opus 4.7 measured |
| Kagi LLM Benchmark | 80.7% | Not measured | Only Claude Opus 4.7 measured |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index01
| Benchmark | Claude Opus 4.7 | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| AIME | 96.3% | Not measured | Only Claude Opus 4.7 measured |
| OTIS Mock AIME | 97.8% | Not measured | Only Claude Opus 4.7 measured |
| FrontierMath, tiers 1 to 3 | 70.2% | Not measured | Only Claude Opus 4.7 measured |
| FrontierMath, tier 4 | 31.7% | 80.5% | GPT-5.6 Sol Pro |
| ProofBench | 54.0% | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: math | 1498 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: mathematical work | 1509 | Not measured | Only Claude Opus 4.7 measured |
| Neither model has a result on the other 6 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index13 boards, none shared
| Benchmark | Claude Opus 4.7 | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| MMLU Pro | 89.9% | Not measured | Only Claude Opus 4.7 measured |
| LegalBench (Vals AI) | 85.3% | Not measured | Only Claude Opus 4.7 measured |
| CaseLaw (Vals AI) | 68.4% | Not measured | Only Claude Opus 4.7 measured |
| CorpFin (Vals AI) | 66.1% | Not measured | Only Claude Opus 4.7 measured |
| TaxEval (Vals AI) | 75.3% | Not measured | Only Claude Opus 4.7 measured |
| MortgageTax (Vals AI) | 70.3% | Not measured | Only Claude Opus 4.7 measured |
| MedCode (Vals AI) | 54.9% | Not measured | Only Claude Opus 4.7 measured |
| SimpleQA Verified | 51.7% | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: science | 1508 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: medicine and healthcare | 1495 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: legal and government | 1504 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: business and finance | 1490 | Not measured | Only Claude Opus 4.7 measured |
| FACTS Benchmark Suite | 45.5% | Not measured | Only Claude Opus 4.7 measured |
| Neither model has a result on the other 5 boards here | |||
Web designNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Claude Opus 4.7 | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| Neither model has a result on 9 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index02
| Benchmark | Claude Opus 4.7 | GPT-5.6 Sol Pro | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 56.1% | Not measured | Only Claude Opus 4.7 measured |
| MedScribe (Vals AI) | 83.0% | Not measured | Only Claude Opus 4.7 measured |
| Vals Multimodal Index | 67.4% | Not measured | Only Claude Opus 4.7 measured |
| IFBench | 58.6% | Not measured | Only Claude Opus 4.7 measured |
| Long context reasoning (AA-LCR) | 78.7% | Not measured | Only Claude Opus 4.7 measured |
| DTBench | 94.7% | 96.0% | GPT-5.6 Sol Pro |
| LMCA | 52.2% | 59.2% | GPT-5.6 Sol Pro |
| Furniture assembly | 33.3% | Not measured | Only Claude Opus 4.7 measured |
| ExploitBench | 26.5% | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text | 1490 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: instruction following | 1498 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: creative writing | 1486 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Vision | 1317 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: English | 1496 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: non-English | 1480 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: Chinese | 1531 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: German | 1495 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: Japanese | 1474 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: Korean | 1464 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: French | 1503 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: Spanish | 1494 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: Russian | 1494 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: Polish | 1489 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: multi-turn | 1505 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: longer queries | 1505 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: writing and language | 1492 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: entertainment and media | 1474 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Vision: English | 1322 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Vision: Chinese | 1371 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Vision: reading text | 1327 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Vision: humor | 1309 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Vision: recognizing things | 1278 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Vision: creative writing | 1326 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Document | 1495 | Not measured | Only Claude Opus 4.7 measured |
| Neither model has a result on the other 12 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Claude Opus 4.7 | GPT-5.6 Sol Pro | 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-5.6 Sol Pro costs less
Repository review
50K input + 3K output tokens
GPT-5.6 Sol Pro costs less
Agent loop
200K input + 10K output tokens
GPT-5.6 Sol Pro 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 4.7 | OpenAI GPT-5.6 Sol Pro |
|---|---|---|
| Maker | Anthropic | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | April 16, 2026 | July 9, 2026 |
| Context window | 1M | 1.05M |
| Input $/Mtok | $5.00 | $4.00 |
| Output $/Mtok | $25.00 | $20.00 |
| Coding index | 67.5 | Not benchmarked |
| Independent measurements behind it | 4 | 0 |
| Cost per solved task | $2.95 | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Claude Opus 4.7 better than GPT-5.6 Sol Pro for coding?
Only Claude Opus 4.7 has a coding score, 67.5 on the Vibe Coding Index; GPT-5.6 Sol Pro has none, so the two cannot be ranked on coding. Pick GPT-5.6 Sol Pro for output tokens 1.3x cheaper ($20.00 vs $25.00 per million) and a larger context window (1.05M against 1M tokens).
Which is cheaper, Claude Opus 4.7 or GPT-5.6 Sol Pro?
Claude Opus 4.7 costs $5.00 per million input tokens and $25.00 per million output tokens; GPT-5.6 Sol Pro costs $4.00 and $20.00. Cost per solved task is known for Claude Opus 4.7 only.
Which has the bigger context window, Claude Opus 4.7 or GPT-5.6 Sol Pro?
GPT-5.6 Sol Pro, with 1.05M tokens against 1M.
How many benchmarks is the Claude Opus 4.7 vs GPT-5.6 Sol Pro comparison based on?
7 benchmarks have a result for both models as of October 22, 2026. Claude Opus 4.7's coding index rests on 4 independent benchmarks and GPT-5.6 Sol Pro's on 0. Where only one model has a result, the page says so instead of naming a winner.