Claude Opus 4.7 vs GPT-6.1 Sol

GPT-6.1 Sol leads Claude Opus 4.7 on coding, 82.4 to 67.5 on the Vibe Coding Index, and GPT-6.1 Sol costs 2.5x less per output token ($10.00 vs $25.00 per million). Updated October 22, 2026; 65 benchmarks have a result for both.

Replace Claude Opus 4.7 Replace GPT-6.1 Sol

Claude Opus 4.7Anthropic

Coding: 67.5
Overall: 71.6
Output $/M: $25.00

GPT-6.1 SolOpenAI

Coding: 82.4
Overall: 81.4
Output $/M: $10.00

vs boards won of 65 shared, 1 tied

Claude Opus 4.7 or GPT-6.1 Sol: which to pick

Pick GPT-6.1 Sol for coding: it scores 82.4 on the Vibe Coding Index against 67.5 for Claude Opus 4.7.

Pick Claude Opus 4.7 for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Model AClaude Opus 4.7Anthropic67.5/1004 independent benchmarks$2.95 per solved task Model BGPT-6.1 SolOpenAI82.4/1005 independent benchmarksNo cost per solved task

653833

Shared results: 65
Claude Opus 4.7 only: 38
GPT-6.1 Sol only: 33
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
GPT-6.1 Sol
GPT-6.1 Sol scores 82.4 against 67.5.
4 and 5 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-6.1 Sol
GPT-6.1 Sol leads, 51.8 against 40.7.
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
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
Web design
Design Arena: websites
No call
Only GPT-6.1 Sol has a Design Arena: websites result, 1321.
Directional only
General
Vals Index
No call
Only GPT-6.1 Sol has a Vals Index result, 63.9%.
Directional only
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 4.7 $0.018, GPT-6.1 Sol $0.0070 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-6.1 Sol 82.4 from 5 benchmarks.
Widest category: Math, 23.5 points apart on average over 6 shared benchmarks.
Widest single gap: FrontierMath, tier 4: Claude Opus 4.7 31.7% against GPT-6.1 Sol 100.0%, 68.3 points apart on a 0 to 100 scale.
Output price: Claude Opus 4.7 $25.00 against GPT-6.1 Sol $10.00 per million output tokens, 2.5x apart.
Context window: Claude Opus 4.7 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.

Boards won, where both have a result
Category	Claude Opus 4.7	GPT-6.1 Sol	Ties
Coding	2	8
Intelligence	0	2
Agentic work	1	3	1 tie
Reasoning	4	8
Math	1	5
Knowledge	5	2
General	18	5
All shared boards	31	33	1 tie

CodingLike-for-likeSix of these boards feed the Vibe Coding Index28

Coding benchmarks for Claude Opus 4.7 and GPT-6.1 Sol
Benchmark	Claude Opus 4.7	GPT-6.1 Sol	Leader
LiveBench coding	Not measured	96.0%	Only GPT-6.1 Sol measured
LMArena WebDev	1558	1753	GPT-6.1 Sol
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
Terminal-Bench 4 (Vals AI)	Not measured	55.0%	Only GPT-6.1 Sol measured
Vibe Code Bench (Vals AI)	71.0%	88.9%	GPT-6.1 Sol
Code migration (Vals AI)	43.9%	65.1%	GPT-6.1 Sol
ProgramBench (Vals AI)	0.0%	3.0%	GPT-6.1 Sol
IOI (Vals AI)	Not measured	96.9%	Only GPT-6.1 Sol measured
Terminal-Bench 2.1 (Vals AI)	68.5%	Not measured	Only Claude Opus 4.7 measured
SWE-bench Multimodal (Vals AI)	Not measured	43.5%	Only GPT-6.1 Sol measured
CyberBench (Vals AI)	Not measured	39.3%	Only GPT-6.1 Sol measured
SciCode	Not measured	55.8%	Only GPT-6.1 Sol 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%	50.2%	GPT-6.1 Sol
GSO-Bench	44.1%	Not measured	Only Claude Opus 4.7 measured
WeirdML	76.4%	Not measured	Only Claude Opus 4.7 measured
MirrorCode	31.1%	Not measured	Only Claude Opus 4.7 measured
ALE-Bench	Not measured	2743.8	Only GPT-6.1 Sol measured
LMArena Text: coding	1519	1478	Claude Opus 4.7
LMArena Text: software and IT	1516	1476	Claude Opus 4.7
LMArena WebDev: React	1560	1754	GPT-6.1 Sol
LMArena WebDev: HTML	1554	1800	GPT-6.1 Sol
LMArena WebDev: from an image	1577	1702	GPT-6.1 Sol
SciCode	Not measured	9.2%	Only GPT-6.1 Sol measured
Neither model has a result on the other 12 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02

Intelligence benchmarks for Claude Opus 4.7 and GPT-6.1 Sol
Benchmark	Claude Opus 4.7	GPT-6.1 Sol	Leader
AA Intelligence Index	40.7	51.8	GPT-6.1 Sol
Epoch Capabilities Index	156.8	168.4	GPT-6.1 Sol

Agentic workLike-for-likePublic boards, shown as published, kept out of the index13

Agentic work benchmarks for Claude Opus 4.7 and GPT-6.1 Sol
Benchmark	Claude Opus 4.7	GPT-6.1 Sol	Leader
AA Agentic Index	38.6	Not measured	Only Claude Opus 4.7 measured
Design Arena: agents building web apps	Not measured	1306	Only GPT-6.1 Sol measured
Design Arena: agents building mobile apps	Not measured	1213	Only GPT-6.1 Sol measured
Design Arena: spreadsheets	Not measured	1259	Only GPT-6.1 Sol measured
LiveBench research	Not measured	83.5%	Only GPT-6.1 Sol measured
LiveBench browser	Not measured	88.0%	Only GPT-6.1 Sol measured
LiveBench long agentic	Not measured	73.0%	Only GPT-6.1 Sol measured
SREBench (Vals AI)	Not measured	50.8%	Only GPT-6.1 Sol measured
Finance Agent (Vals AI)	51.5%	52.0%	GPT-6.1 Sol
Tax Agent Bench (Vals AI)	23.7%	21.8%	Claude Opus 4.7
Legal Research Bench (Vals AI)	38.5%	38.5%	Tie
Harvey's Legal Agent Benchmark (Vals AI)	Not measured	6.3%	Only GPT-6.1 Sol measured
Excel Modeling Benchmark (Vals AI)	63.7%	70.8%	GPT-6.1 Sol
BioMysteryBench (Vals AI)	Not measured	79.6%	Only GPT-6.1 Sol measured
Terminal-Bench-Science (Vals AI)	Not measured	52.9%	Only GPT-6.1 Sol measured
Vals Science Index	Not measured	59.6%	Only GPT-6.1 Sol measured
Robo-bench (Vals AI)	Not measured	28.3%	Only GPT-6.1 Sol measured
τ²-Bench Telecom	88.6%	Not measured	Only Claude Opus 4.7 measured
APEX-Agents	49.2%	60.0%	GPT-6.1 Sol
OSWorld 2.0	18.2%	Not measured	Only Claude Opus 4.7 measured
PostTrainBench	28.6%	Not measured	Only Claude Opus 4.7 measured
SpireClimb	Not measured	24.7%	Only GPT-6.1 Sol 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 17 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index48

Reasoning benchmarks for Claude Opus 4.7 and GPT-6.1 Sol
Benchmark	Claude Opus 4.7	GPT-6.1 Sol	Leader
GPQA Diamond	90.2%	Not measured	Only Claude Opus 4.7 measured
LiveBench reasoning	Not measured	92.6%	Only GPT-6.1 Sol measured
MysteryMechanism (Vals AI)	Not measured	46.4%	Only GPT-6.1 Sol 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%	52.9%	GPT-6.1 Sol
GPQA Diamond (Epoch AI run)	90.2%	95.4%	GPT-6.1 Sol
ARC-AGI	93.5%	98.5%	GPT-6.1 Sol
ARC-AGI-2	75.8%	94.2%	GPT-6.1 Sol
SimpleBench	61.7%	Not measured	Only Claude Opus 4.7 measured
Chess puzzles	41.0%	68.0%	GPT-6.1 Sol
Mystery game puzzles	28.0%	80.0%	GPT-6.1 Sol
EBR-bench	19.0%	54.3%	GPT-6.1 Sol
LMArena Text: hard prompts	1506	1463	Claude Opus 4.7
LMArena Text: expert	1521	1489	Claude Opus 4.7
LMArena Text: hard prompts in English	1508	1465	Claude Opus 4.7
LMArena Vision: diagrams	1336	1306	Claude Opus 4.7
LMArena Vision: homework	1337	1356	GPT-6.1 Sol
Kagi LLM Benchmark	80.7%	Not measured	Only Claude Opus 4.7 measured
Neither model has a result on the other 3 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index15

Math benchmarks for Claude Opus 4.7 and GPT-6.1 Sol
Benchmark	Claude Opus 4.7	GPT-6.1 Sol	Leader
AIME	96.3%	Not measured	Only Claude Opus 4.7 measured
OTIS Mock AIME	97.8%	100.0%	GPT-6.1 Sol
FrontierMath, tiers 1 to 3	70.2%	93.7%	GPT-6.1 Sol
FrontierMath, tier 4	31.7%	100.0%	GPT-6.1 Sol
ProofBench	54.0%	99.0%	GPT-6.1 Sol
LMArena Text: math	1498	1489	Claude Opus 4.7
LMArena Text: mathematical work	1509	1513	GPT-6.1 Sol
Neither model has a result on the other 6 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index52

Knowledge benchmarks for Claude Opus 4.7 and GPT-6.1 Sol
Benchmark	Claude Opus 4.7	GPT-6.1 Sol	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%	48.8%	Claude Opus 4.7
SimpleQA Verified	51.7%	73.9%	GPT-6.1 Sol
LMArena Text: science	1508	1444	Claude Opus 4.7
LMArena Text: medicine and healthcare	1495	1433	Claude Opus 4.7
LMArena Text: legal and government	1504	1471	Claude Opus 4.7
LMArena Text: business and finance	1490	1445	Claude Opus 4.7
FACTS Benchmark Suite	45.5%	75.3%	GPT-6.1 Sol
Neither model has a result on the other 5 boards here

Web designDirectional onlyPublic boards, shown as published, kept out of the index7 boards, none shared

Web design benchmarks for Claude Opus 4.7 and GPT-6.1 Sol
Benchmark	Claude Opus 4.7	GPT-6.1 Sol	Leader
Design Arena: websites	Not measured	1321	Only GPT-6.1 Sol measured
Design Arena: UI components	Not measured	1317	Only GPT-6.1 Sol measured
Design Arena: game dev	Not measured	1389	Only GPT-6.1 Sol measured
Design Arena: data viz	Not measured	1281	Only GPT-6.1 Sol measured
Design Arena: 3D	Not measured	1460	Only GPT-6.1 Sol measured
Design Arena: all code categories	Not measured	1345	Only GPT-6.1 Sol measured
LiveBench design	Not measured	82.1%	Only GPT-6.1 Sol measured
Neither model has a result on the other 2 boards here

GeneralLike-for-likePublic boards, shown as published, kept out of the index185

General benchmarks for Claude Opus 4.7 and GPT-6.1 Sol
Benchmark	Claude Opus 4.7	GPT-6.1 Sol	Leader
Vals Index	Not measured	63.9%	Only GPT-6.1 Sol measured
LiveBench data analysis	Not measured	82.7%	Only GPT-6.1 Sol measured
Public Benefits Bench (Vals AI)	Not measured	59.3%	Only GPT-6.1 Sol measured
SAGE (Vals AI)	56.1%	46.5%	Claude Opus 4.7
MedScribe (Vals AI)	83.0%	86.5%	GPT-6.1 Sol
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%	84.0%	GPT-6.1 Sol
DTBench	94.7%	96.5%	GPT-6.1 Sol
LMCA	52.2%	62.8%	GPT-6.1 Sol
Furniture assembly	33.3%	80.0%	GPT-6.1 Sol
ExploitBench	26.5%	Not measured	Only Claude Opus 4.7 measured
LMArena Text	1490	1443	Claude Opus 4.7
LMArena Text: instruction following	1498	1466	Claude Opus 4.7
LMArena Text: creative writing	1486	1425	Claude Opus 4.7
LMArena Vision	1317	1288	Claude Opus 4.7
LMArena Text: English	1496	1450	Claude Opus 4.7
LMArena Text: non-English	1480	1433	Claude Opus 4.7
LMArena Text: Chinese	1531	1487	Claude Opus 4.7
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	1460	Claude Opus 4.7
LMArena Text: Spanish	1494	1439	Claude Opus 4.7
LMArena Text: Russian	1494	1457	Claude Opus 4.7
LMArena Text: Polish	1489	Not measured	Only Claude Opus 4.7 measured
LMArena Text: multi-turn	1505	1442	Claude Opus 4.7
LMArena Text: longer queries	1505	1458	Claude Opus 4.7
LMArena Text: writing and language	1492	1444	Claude Opus 4.7
LMArena Text: entertainment and media	1474	1426	Claude Opus 4.7
LMArena Vision: English	1322	1274	Claude Opus 4.7
LMArena Vision: Chinese	1371	Not measured	Only Claude Opus 4.7 measured
LMArena Vision: reading text	1327	1289	Claude Opus 4.7
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	1301	Claude Opus 4.7
LMArena Document	1495	Not measured	Only Claude Opus 4.7 measured
Neither model has a result on the other 9 boards here

Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared

Image generation benchmarks for Claude Opus 4.7 and GPT-6.1 Sol
Benchmark	Claude Opus 4.7	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

Claude Opus 4.7$0.018Fits in one request

GPT-6.1 Sol$0.0070Fits in one request

GPT-6.1 Sol costs less

Repository review

50K input + 3K output tokens

Claude Opus 4.7$0.325Fits in one request

GPT-6.1 Sol$0.130Fits in one request

GPT-6.1 Sol costs less

Agent loop

200K input + 10K output tokens

Claude Opus 4.7$1.25Fits in one request

GPT-6.1 Sol$0.500Fits in one request

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.

Specifications of Claude Opus 4.7 and GPT-6.1 Sol
Specification	Anthropic Claude Opus 4.7	OpenAI GPT-6.1 Sol
Maker	Anthropic	OpenAI
Weights	No public weights listed	No public weights listed
Released	April 16, 2026	September 29, 2026
Context window	1M	1.05M
Input $/Mtok	$5.00	$2.00
Output $/Mtok	$25.00	$10.00
Coding index	67.5	82.4
Independent measurements behind it	4	5
Cost per solved task	$2.95	Not computable
Source	OpenRouter listing	OpenRouter listing

Questions

Is Claude Opus 4.7 better than GPT-6.1 Sol for coding?

Pick GPT-6.1 Sol for coding: it scores 82.4 on the Vibe Coding Index against 67.5 for Claude Opus 4.7. Pick Claude Opus 4.7 for work measured by LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, Claude Opus 4.7 or GPT-6.1 Sol?

Claude Opus 4.7 costs $5.00 per million input tokens and $25.00 per million output tokens; GPT-6.1 Sol costs $2.00 and $10.00. Cost per solved task is known for Claude Opus 4.7 only.

Which has the bigger context window, Claude Opus 4.7 or GPT-6.1 Sol?

GPT-6.1 Sol, with 1.05M tokens against 1M.

How many benchmarks is the Claude Opus 4.7 vs GPT-6.1 Sol comparison based on?

65 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-6.1 Sol's on 5. Where only one model has a result, the page says so instead of naming a winner.

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Claude Opus 4.7 or GPT-6.1 Sol: which to pick

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

Math

Knowledge

Web design

General

Long documents

Everyday cost

Cost per solved task

At a glance

Benchmark by benchmark

What each workload costs

Chat turn

Repository review

Agent loop

Specification differences

Questions

Compare next