Claude Opus 4.7 vs GPT-5 Nano
Claude Opus 4.7 leads GPT-5 Nano on the Artificial Analysis Intelligence Index, 40.7 to 13.0, and GPT-5 Nano costs 62.5x less per output token ($0.40 vs $25.00 per million). Updated October 22, 2026; 70 benchmarks have a result for both.
Claude Opus 4.7 or GPT-5 Nano: which to pick
Only Claude Opus 4.7 has a coding score, 67.5 on the Vibe Coding Index; GPT-5 Nano has none, so the two cannot be ranked on coding.
Pick GPT-5 Nano for output tokens 62.5x cheaper ($0.40 vs $25.00 per million) and a lower cost per solved task ($0.109 against $2.95).
- Shared results
- 70
- Claude Opus 4.7 only
- 39
- GPT-5 Nano only
- 18
- Like-for-like categories
- 7 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
Claude Opus 4.7
Claude Opus 4.7 leads, 40.7 against 13.0.
Same board, both measured
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
Claude Opus 4.7
Claude Opus 4.7 leads, 90.2% against 63.4%.
Same board, both measured
Math
AIME
Claude Opus 4.7
Claude Opus 4.7 leads, 96.3% against 81.2%.
Same board, both measured
Knowledge
MMLU Pro
Claude Opus 4.7
Claude Opus 4.7 leads, 89.9% against 76.1%.
Same board, both measured
Web design
Design Arena: websites
No call
Only GPT-5 Nano has a Design Arena: websites result, 1101.
Directional only
Long documents
Listed context window
Claude Opus 4.7
Claude Opus 4.7 takes 1M tokens against 400K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5 Nano
Claude Opus 4.7 $0.018, GPT-5 Nano $0.0003 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GPT-5 Nano
Claude Opus 4.7 $2.95, GPT-5 Nano $0.109.
Published attempt cost and pass rate
At a glance
- Coding index
- Claude Opus 4.7 67.5 from 4 benchmarks, GPT-5 Nano not benchmarked.
- Widest category
- Agentic work, 52.0 points apart on average over 1 shared benchmark.
- Widest single gap
- ARC-AGI-2: Claude Opus 4.7 75.8% against GPT-5 Nano 2.6%, 73.2 points apart on a 0 to 100 scale.
- Output price
- Claude Opus 4.7 $25.00 against GPT-5 Nano $0.40 per million output tokens, 62.5x apart.
- Context window
- Claude Opus 4.7 takes 1M tokens, GPT-5 Nano 400K.
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 Nano | Ties |
|---|---|---|---|---|
| Coding | 6 | 0 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 1 | 0 | ||
| Reasoning | 15 | 0 | ||
| Math | 8 | 0 | ||
| Knowledge | 11 | 0 | ||
| General | 26 | 1 | ||
| All shared boards | 69 | 1 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index60
| Benchmark | Claude Opus 4.7 | GPT-5 Nano | Leader |
|---|---|---|---|
| SWE-bench Verified | Not measured | 34.8% | Only GPT-5 Nano measured |
| 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% | 70.2% | Claude Opus 4.7 |
| 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 |
| LiveCodeBench (Artificial Analysis run) | Not measured | 78.9% | Only GPT-5 Nano measured |
| Terminal-Bench Hard (Artificial Analysis run) | 54.5% | 17.4% | Claude Opus 4.7 |
| Terminal-Bench | 80.2% | 21.8% | Claude Opus 4.7 |
| 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% | 38.1% | Claude Opus 4.7 |
| MirrorCode | 31.1% | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: coding | 1519 | 1351 | Claude Opus 4.7 |
| LMArena Text: software and IT | 1516 | 1345 | Claude Opus 4.7 |
| 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 |
| SWE Atlas: Codebase QnA | 40.3% | Not measured | Only Claude Opus 4.7 measured |
| SWE Atlas: Refactoring | 48.6% | Not measured | Only Claude Opus 4.7 measured |
| SWE Atlas: Test Writing | 38.5% | Not measured | Only Claude Opus 4.7 measured |
| Neither model has a result on the other 19 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Claude Opus 4.7 | GPT-5 Nano | Leader |
|---|---|---|---|
| AA Intelligence Index | 40.7 | 13.0 | Claude Opus 4.7 |
| Epoch Capabilities Index | 156.8 | 139.2 | Claude Opus 4.7 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
| Benchmark | Claude Opus 4.7 | GPT-5 Nano | 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% | 36.5% | Claude Opus 4.7 |
| APEX-Agents | 49.2% | Not measured | Only Claude Opus 4.7 measured |
| 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 |
| Berkeley Function Calling Leaderboard (BFCL) | Not measured | 51.4% | Only GPT-5 Nano measured |
| MCP Atlas | 79.1% | Not measured | Only Claude Opus 4.7 measured |
| Neither model has a result on the other 29 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index150
| Benchmark | Claude Opus 4.7 | GPT-5 Nano | Leader |
|---|---|---|---|
| GPQA Diamond | 90.2% | 63.4% | Claude Opus 4.7 |
| MMMU Pro (Vals AI) | 85.5% | 70.9% | Claude Opus 4.7 |
| GPQA Diamond (Artificial Analysis run) | 91.4% | 67.6% | Claude Opus 4.7 |
| Humanity's Last Exam (Artificial Analysis run) | 42.3% | 9.5% | Claude Opus 4.7 |
| GPQA Diamond (Epoch AI run) | 90.2% | 69.4% | Claude Opus 4.7 |
| ARC-AGI | 93.5% | 20.7% | Claude Opus 4.7 |
| ARC-AGI-2 | 75.8% | 2.6% | Claude Opus 4.7 |
| SimpleBench | 61.7% | Not measured | Only Claude Opus 4.7 measured |
| Chess puzzles | 41.0% | 22.0% | Claude Opus 4.7 |
| Mystery game puzzles | 28.0% | 9.0% | Claude Opus 4.7 |
| EBR-bench | 19.0% | Not measured | Only Claude Opus 4.7 measured |
| VPCT | Not measured | 37.2% | Only GPT-5 Nano measured |
| LMArena Text: hard prompts | 1506 | 1328 | Claude Opus 4.7 |
| LMArena Text: expert | 1521 | 1321 | Claude Opus 4.7 |
| LMArena Text: hard prompts in English | 1508 | 1338 | Claude Opus 4.7 |
| LMArena Vision: diagrams | 1336 | 1141 | Claude Opus 4.7 |
| LMArena Vision: homework | 1337 | 1157 | Claude Opus 4.7 |
| Kagi LLM Benchmark | 80.7% | 62.2% | Claude Opus 4.7 |
| Neither model has a result on the other 5 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index80
| Benchmark | Claude Opus 4.7 | GPT-5 Nano | Leader |
|---|---|---|---|
| AIME | 96.3% | 81.2% | Claude Opus 4.7 |
| MATH 500 (Vals AI) | Not measured | 93.8% | Only GPT-5 Nano measured |
| MGSM (Vals AI) | Not measured | 89.3% | Only GPT-5 Nano measured |
| AA Math Index | Not measured | 83.7 | Only GPT-5 Nano measured |
| AIME 2025 (Artificial Analysis run) | Not measured | 83.7% | Only GPT-5 Nano measured |
| OTIS Mock AIME | 97.8% | 81.1% | Claude Opus 4.7 |
| FrontierMath, tiers 1 to 3 | 70.2% | 20.0% | Claude Opus 4.7 |
| FrontierMath, tier 4 | 31.7% | 2.4% | Claude Opus 4.7 |
| ProofBench | 54.0% | 12.0% | Claude Opus 4.7 |
| MATH level 5 | Not measured | 95.2% | Only GPT-5 Nano measured |
| LMArena Text: math | 1498 | 1317 | Claude Opus 4.7 |
| LMArena Text: mathematical work | 1509 | 1326 | Claude Opus 4.7 |
| MathArena | 20.4% | 12.8% | Claude Opus 4.7 |
| Neither model has a result on the other 1 board here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index110
| Benchmark | Claude Opus 4.7 | GPT-5 Nano | Leader |
|---|---|---|---|
| MMLU Pro | 89.9% | 76.1% | Claude Opus 4.7 |
| LegalBench (Vals AI) | 85.3% | 50.1% | Claude Opus 4.7 |
| CaseLaw (Vals AI) | 68.4% | 52.6% | Claude Opus 4.7 |
| CorpFin (Vals AI) | 66.1% | Not measured | Only Claude Opus 4.7 measured |
| TaxEval (Vals AI) | 75.3% | 67.4% | Claude Opus 4.7 |
| MortgageTax (Vals AI) | 70.3% | 53.6% | Claude Opus 4.7 |
| MedQA (Vals AI) | Not measured | 93.3% | Only GPT-5 Nano measured |
| MedCode (Vals AI) | 54.9% | 30.4% | Claude Opus 4.7 |
| MMLU Pro (Artificial Analysis run) | Not measured | 78.0% | Only GPT-5 Nano measured |
| SimpleQA Verified | 51.7% | 11.7% | Claude Opus 4.7 |
| LMArena Text: science | 1508 | 1318 | Claude Opus 4.7 |
| LMArena Text: medicine and healthcare | 1495 | 1335 | Claude Opus 4.7 |
| LMArena Text: legal and government | 1504 | 1298 | Claude Opus 4.7 |
| LMArena Text: business and finance | 1490 | 1311 | Claude Opus 4.7 |
| 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 designDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Claude Opus 4.7 | GPT-5 Nano | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1101 | Only GPT-5 Nano measured |
| Design Arena: UI components | Not measured | 1064 | Only GPT-5 Nano measured |
| Design Arena: game dev | Not measured | 1044 | Only GPT-5 Nano measured |
| Design Arena: data viz | Not measured | 1056 | Only GPT-5 Nano measured |
| Design Arena: 3D | Not measured | 965 | Only GPT-5 Nano measured |
| Design Arena: all code categories | Not measured | 1084 | Only GPT-5 Nano measured |
| Neither model has a result on the other 3 boards here | |||
GeneralLike-for-likePublic boards, shown as published, kept out of the index261
| Benchmark | Claude Opus 4.7 | GPT-5 Nano | Leader |
|---|---|---|---|
| SAGE (Vals AI) | 56.1% | 30.4% | Claude Opus 4.7 |
| MedScribe (Vals AI) | 83.0% | 72.9% | Claude Opus 4.7 |
| Vals Multimodal Index | 67.4% | Not measured | Only Claude Opus 4.7 measured |
| IFBench | 58.6% | 67.6% | GPT-5 Nano |
| Long context reasoning (AA-LCR) | 78.7% | 45.0% | Claude Opus 4.7 |
| DTBench | 94.7% | 62.7% | Claude Opus 4.7 |
| LMCA | 52.2% | 7.9% | Claude Opus 4.7 |
| Fiction.LiveBench | Not measured | 44.4% | Only GPT-5 Nano measured |
| 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 | 1320 | Claude Opus 4.7 |
| LMArena Text: instruction following | 1498 | 1306 | Claude Opus 4.7 |
| LMArena Text: creative writing | 1486 | 1249 | Claude Opus 4.7 |
| LMArena Vision | 1317 | 1159 | Claude Opus 4.7 |
| LMArena Text: English | 1496 | 1321 | Claude Opus 4.7 |
| LMArena Text: non-English | 1480 | 1313 | Claude Opus 4.7 |
| LMArena Text: Chinese | 1531 | 1356 | Claude Opus 4.7 |
| LMArena Text: German | 1495 | 1327 | Claude Opus 4.7 |
| LMArena Text: Japanese | 1474 | 1227 | Claude Opus 4.7 |
| LMArena Text: Korean | 1464 | 1269 | Claude Opus 4.7 |
| LMArena Text: French | 1503 | Not measured | Only Claude Opus 4.7 measured |
| LMArena Text: Spanish | 1494 | 1360 | Claude Opus 4.7 |
| LMArena Text: Russian | 1494 | 1296 | Claude Opus 4.7 |
| LMArena Text: Polish | 1489 | 1314 | Claude Opus 4.7 |
| LMArena Text: multi-turn | 1505 | 1311 | Claude Opus 4.7 |
| LMArena Text: longer queries | 1505 | 1312 | Claude Opus 4.7 |
| LMArena Text: writing and language | 1492 | 1283 | Claude Opus 4.7 |
| LMArena Text: entertainment and media | 1474 | 1268 | Claude Opus 4.7 |
| LMArena Vision: English | 1322 | 1170 | Claude Opus 4.7 |
| LMArena Vision: Chinese | 1371 | 1176 | Claude Opus 4.7 |
| LMArena Vision: reading text | 1327 | 1152 | Claude Opus 4.7 |
| LMArena Vision: humor | 1309 | 1110 | Claude Opus 4.7 |
| 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 |
| EQ-Bench 4 | 1311 | 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 Nano | 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 Nano costs less
Repository review
50K input + 3K output tokens
GPT-5 Nano costs less
Agent loop
200K input + 10K output tokens
GPT-5 Nano 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 Nano |
|---|---|---|
| Maker | Anthropic | OpenAI |
| Weights | No public weights listed | No public weights listed |
| Released | April 16, 2026 | August 7, 2025 |
| Context window | 1M | 400K |
| Input $/Mtok | $5.00 | $0.05 |
| Output $/Mtok | $25.00 | $0.40 |
| Coding index | 67.5 | Not benchmarked |
| Independent measurements behind it | 4 | 0 |
| Cost per solved task | $2.95 | $0.109 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Claude Opus 4.7 better than GPT-5 Nano for coding?
Only Claude Opus 4.7 has a coding score, 67.5 on the Vibe Coding Index; GPT-5 Nano has none, so the two cannot be ranked on coding. Pick GPT-5 Nano for output tokens 62.5x cheaper ($0.40 vs $25.00 per million) and a lower cost per solved task ($0.109 against $2.95).
Which is cheaper, Claude Opus 4.7 or GPT-5 Nano?
Claude Opus 4.7 costs $5.00 per million input tokens and $25.00 per million output tokens; GPT-5 Nano costs $0.05 and $0.40. Per solved SWE-bench Verified task, Claude Opus 4.7 costs $2.95 and GPT-5 Nano $0.109.
Which has the bigger context window, Claude Opus 4.7 or GPT-5 Nano?
Claude Opus 4.7, with 1M tokens against 400K.
How many benchmarks is the Claude Opus 4.7 vs GPT-5 Nano comparison based on?
70 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 Nano's on 0. Where only one model has a result, the page says so instead of naming a winner.