Is Claude Opus 4.7 better than GPT-6 Sol?

Claude Opus 4.7 and GPT-6 Sol (max) are neck and neck on quality (63.2 vs 62.9, within the ±4.2 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 9 Nov 2026, so check the category scores for your use.

Claude Opus 4.7 vs GPT-6 Sol: which is cheaper, and will that change?

GPT-6 Sol is cheaper today: $4.00 against $10.00 per million tokens, blended at three input tokens per output token. No price change has been announced for either.

Is Claude Opus 4.7 or GPT-6 Sol better for coding?

GPT-6 Sol scores higher in coding (67 vs 61 on the category index, where 50 is average). On Arena WebDev, the top shared coding benchmark, it is 1555 for Claude Opus 4.7 against 1674 for GPT-6 Sol.

Which is faster, Claude Opus 4.7 or GPT-6 Sol?

GPT-6 Sol streams ~2× faster (121 vs 48 output tokens per second, Artificial Analysis 7-day median).

Is Claude Opus 4.7 or GPT-6 Sol better for agents and tool use?

Claude Opus 4.7 scores higher in agentic tasks (65 vs 60 on the category index, where 50 is average). On Terminal-Bench, the top shared agents & tools benchmark, it is 80.2% for Claude Opus 4.7 against 50.3% for GPT-6 Sol.

Which is better for long documents?

Both take about 1.1M tokens: Claude Opus 4.7 1,000,000, GPT-6 Sol 1,050,000.

Which has lower latency?

Claude Opus 4.7 answers first: 1.0 s against 72.1 s to the first answer token, as Artificial Analysis measures it. Reasoning effort drives most of this: a higher setting thinks longer before it answers.

When was GPT-6 Sol released?

GPT-6 Sol was released on 22 Sep 2026.

Claude Opus 4.7 vs GPT-6 Sol

Full profiles: Claude Opus 4.7 (Anthropic) and GPT-6 Sol (OpenAI): every benchmark, price and rank.

Updated 9 Nov 2026 · Data from 13 sources

As of 9 Nov 2026, Claude Opus 4.7 and GPT-6 Sol are neck and neck on quality (63.2 vs 62.9 on the BenchLeader Index, inside the ±4.2 margin), and GPT-6 Sol is 2.5× cheaper at $4.00 vs $10.00 per 1M tokens blended. Choose Claude Opus 4.7 for multimodal (67 vs 61), agents & tools (65 vs 60), and human preference (67 vs 64) and fast first answers (1.0 s vs 72.1 s); choose GPT-6 Sol for coding (67 vs 61), maths (69 vs 67), and reasoning (66 vs 65), where it also streams ~2× faster.

Key facts (as of 9 Nov 2026)

Claude Opus 4.7 scores 63.2 on the BenchLeader Index and GPT-6 Sol scores 62.9 (BenchLeader, 9 Nov 2026).
Claude Opus 4.7 costs $10.00 per 1M tokens blended (list price, 9 Nov 2026).
GPT-6 Sol costs $4.00 per 1M tokens blended (list price, 9 Nov 2026).
GPT-6 Sol streams ~2× faster than Claude Opus 4.7 (Artificial Analysis, 7-day median, 9 Nov 2026).
Of the 25 benchmarks both models have, Claude Opus 4.7 leads 15 (BenchLeader, 9 Nov 2026).
On Arena WebDev, Claude Opus 4.7 is rated 1555 and GPT-6 Sol 1674 (LMArena, as published by 9 Nov 2026).

Claude Opus 4.7 benchmarks Anthropic

GPT-6 Sol benchmarks max OpenAI Add a third model

Which to pick for…

The pick's numbers come first. Category scores on the BenchLeader scale (50 is the average model, 15 points one standard deviation). High confidence means a lead of half a standard deviation or more; under one point is called either.

Use case	Pick	Why	Confidence
Coding	GPT-6 Sol	67 vs 61 category score; Arena WebDev 1674 vs 1555	Medium
Agents & tool use	Claude Opus 4.7	65 vs 60 category score; Terminal-Bench 80.2% vs 50.3%	Medium
Maths	GPT-6 Sol	69 vs 67 category score; Arena Maths 1440 vs 1490	Medium
Reasoning	GPT-6 Sol	66 vs 65 category score; Arena Hard Prompts 1483 vs 1519	Medium
Knowledge	Either	62 vs 62 category score; Excel Modeling Benchmark 63.7% vs 71.5%	Either
Images and other media	Claude Opus 4.7	67 vs 61 category score; Arena Vision 1319 vs 1232	Medium
Chat quality (human preference)	Claude Opus 4.7	67 vs 64 on Arena votes	Medium
Lowest cost	GPT-6 Sol	$4.00 vs $10.00 per 1M blended; agentic coding session $0.160 vs $0.400	–
Fastest first answer	Claude Opus 4.7	1.0 s (Claude Opus 4.7) vs 72.1 s (GPT-6 Sol (max)) to the first answer token	–
High volume on a budget	Neither flagship	A smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs	–

Key differences

Claude Opus 4.7 and GPT-6 Sol (max) are neck and neck on quality (63.2 vs 62.9, within the ±4.2 margin).
Claude Opus 4.7 is stronger in agents & tools, human preference, knowledge, multimodal.
GPT-6 Sol (max) is stronger in coding, maths, reasoning, long context.
GPT-6 Sol (max) is 2.5× cheaper ($4.00 vs $10.00 per 1M blended).
GPT-6 Sol (max) streams 2.5× faster (121 vs 48 tokens per second).

At a glance

Spec	Claude Opus 4.7	GPT-6 Sol
Developer	Anthropic	OpenAI
Released	16 Apr 2026	22 Sep 2026
Context window (tokens)	1,000,000	1,050,000
Compared at	Claude Opus 4.7	GPT-6 Sol (max)
Open weights	No	No
Price in / out / cached input per 1M	$5.00 / $25.00 / $0.500	$2.00 / $10.00 / $0.200

Category by category

Category scores on the BenchLeader scale: 50 is the average evaluated model, 15 points is one standard deviation. A gap under one point is called level.

Category	Claude Opus 4.7	GPT-6 Sol (max)	Leader
Reasoning	65.0	66.2	GPT-6 Sol
Coding	61.3	66.5	GPT-6 Sol
Agents & tools	65.1	59.6	Claude Opus 4.7
Maths	66.7	68.5	GPT-6 Sol
Knowledge	62.4	61.5	level
Human preference	67.4	64.2	Claude Opus 4.7
Multimodal	67.1	60.7	Claude Opus 4.7
Long context	–	66.6	not comparable

On one chart

Each domain on the index's own scale, where 50 is an average model. Click a domain to see the benchmarks behind it. Pick up to 5 models from the list.

Not drawn, measured for fewer than two of these models: Instruction following, Long context.

ModelIndex

Where sources disagree

Across the 25 benchmarks both have, Claude Opus 4.7 leads 15, GPT-6 Sol leads 10. Every overall index that rates both puts Claude Opus 4.7 ahead.

Overall index	Claude Opus 4.7	GPT-6 Sol (max)	Leader
BenchLeader Index	63.2	62.9	neck and neck
Arena Text	1494	1457	Claude Opus 4.7

Each publisher runs its own tasks, harnesses and effort settings, so their overall verdicts can differ; BenchLeader reconciles them on one scale. † measured at another effort setting of the same model (the publisher did not test the one compared here).

Price, speed and latency

List prices blended at three input tokens per output token. Per-task prices use the token counts on the methodology page. Cost, tokens and time per benchmark task are measured: Artificial Analysis’ averages over its whole Intelligence Index run.

Measure	Claude Opus 4.7	GPT-6 Sol (max)
Blended price per 1M tokens	$10.00	$4.00
Input / output per 1M	$5.00 / $25.00	$2.00 / $10.00
Cached input per 1M	$0.500	$0.200
Price per task: chat reply	$0.0095	$0.0038
Price per task: summarize a 30-page report	$0.075	$0.030
Price per task: code edit	$0.068	$0.027
Price per task: agentic coding session	$0.400	$0.160
Price per task: structured extraction	$0.015	$0.0060
Agentic coding session, input mostly cached	$0.198	$0.079
Cost per benchmark task (AA Index)	–	$2.47
Output tokens per task (AA Index)	–	54k
Of which reasoning	–	35k
Time per task (AA Index)	–	7 min
Output speed	48 tok/s	121 tok/s
Time to first answer	1.0 s	72.1 s
Time to a complete answer	–	130.2 s

Each model is compared at its best-ranked reasoning-effort setting. Claude Opus 4.7 scores 63.2 and takes 1 s to its first answer token; Claude Opus 4.7 (high) scores 60.9 in 1 s, Claude Opus 4.7 (max) scores 59.5 in 25 s. GPT-6 Sol (max) scores 62.9 and takes 72 s to its first answer token; GPT-6 Sol (xhigh) scores 58.6 in 24 s, GPT-6 Sol (high) scores 58.2 in 9 s. Higher effort means more thinking before the answer: better scores, longer waits and more tokens billed. How reasoning effort changes scores and cost.

Every benchmark

141 benchmarks, grouped by category; each name links to the board and its leaders. † measured at another effort setting of the same model, shown for reference and not counted as a win.

Metric	Publisher	Claude Opus 4.7	GPT-6 Sol (max)
BenchLeader Index	BenchLeader	63.2	62.9
Agents & tools score	BenchLeader	65.1	59.6
Coding score	BenchLeader	61.3	66.5
Human preference score	BenchLeader	67.4	64.2
Knowledge score	BenchLeader	62.4	61.5
Maths score	BenchLeader	66.7	68.5
Multimodal score	BenchLeader	67.1	60.7
Reasoning score	BenchLeader	65.0	66.2
Long context score	BenchLeader	–	66.6
Blended price $/M	BenchLeader	$10.00	$4.00
Output speed	BenchLeader	48 tok/s	121 tok/s
Time to first answer	BenchLeader	1.0 s	72.1 s
Context window	BenchLeader	1,000,000 tokens	1,050,000 tokens
Reasoning
GPQA Diamond	Epoch AI Benchmarking Hub	86.4%†	94.3%
Humanity's Last Exam	Scale AI / CAIS	36.2%	–
SimpleBench	SimpleBench	61.7%	–
Arena Hard Prompts	Arena (LMArena)	1519	1483
LiveBench 1.0 Reasoning	LiveBench	87.2%†	88.7%
GPQA Diamond (AA)	Artificial Analysis	91.4%†	–
Humanity's Last Exam (AA)	Artificial Analysis	42.3%†	47.9%
HLE-Diamond (AA)	Artificial Analysis	–	45.2%
GPQA Diamond (Vals)	Vals AI	90.2%	–
Kagi LLM Benchmark	Kagi LLM Benchmark	73.3%	–
ARC-AGI-1	ARC Prize	–	95.5%
ARC-AGI-2	ARC Prize	–	89.6%
ARC-AGI-3	ARC Prize	0.2%†	23.0%
CritPt	Artificial Analysis	12.0%†	30.9%
CritPt v2 hard subset (AA)	Artificial Analysis	–	66.5%
MysteryMechanism	Vals AI	–	30.2%
Chess Puzzles	Epoch AI Benchmarking Hub	41.0%†	56.0%
Mystery Game Puzzles	Epoch AI Benchmarking Hub	13.0%	56.0%
LMCA	Epoch AI Benchmarking Hub	52.2%†	59.1%
DTBench	Epoch AI Benchmarking Hub	94.7%†	97.3%
ForecastBench	ForecastBench	63.1%	–
Coding
SWE-bench Verified (Epoch)	Epoch AI Benchmarking Hub	83.5%†	–
SciCode	SciCode	54.5%†	57.6%
WeirdML	WeirdML	76.4%	–
FrontierCode	Cognition	38.5%	49.3%

Show all 141 benchmarks

Metric	Publisher	Claude Opus 4.7	GPT-6 Sol (max)
Coding
GSO-Bench	GSO-Bench	44.1%	–
Arena Coding	Arena (LMArena)	1546	1520
Arena WebDev	Arena (LMArena)	1555	1674
LiveBench 1.0 Coding	LiveBench	82.1%†	81.8%
SciCode (AA)	Artificial Analysis	–	57.6%
LiveCodeBench	Vals AI	85.1%	–
IOI	Vals AI	–	82.6%
SWE-bench (Vals)	Vals AI	82.0%	–
Code Migration	Vals AI	43.9%	57.2%
ProgramBench	Vals AI	0.0%	2.0%
Vibe Code Bench v1.1	Vals AI	71.0%	87.8%
SWE Atlas: Codebase QnA	Scale AI SEAL	40.3%	–
SWE Atlas: Refactoring	Scale AI SEAL	48.6%	–
SWE Atlas: Test Writing	Scale AI SEAL	38.5%	–
MirrorCode	Epoch AI Benchmarking Hub	31.1%†	–
ALE-Bench	Epoch AI Benchmarking Hub	1323.0	2462
Terminal-Bench 4.0 (AA)	Artificial Analysis	–	43.9%
Terminal-Bench 2.1 (AA)	Artificial Analysis	83.2%†	–
GameBench 2 Overall	DuelLab GameBench 2	–	72.9†
GameBench 2 by reasoning setting	DuelLab GameBench 2	–	79.3†
Design Arena Website	Design Arena	–	1285†
FrontierCode 2.0 (AA)	Artificial Analysis	–	35.6%
Agents & tools
Terminal-Bench	Terminal-Bench	80.2%	50.3%
OSWorld-Verified 2.0	OSWorld	18.2%†	–
APEX-Agents	Mercor	49.2%†	54.3%
Arena Agent	Arena (LMArena)	–	7
LiveBench Agentic Coding	LiveBench	50.7%†	52.9%
Terminal-Bench Hard	Artificial Analysis	51.5%†	–
τ²-Bench Telecom (AA)	Artificial Analysis	88.6%†	–
Terminal-Bench 2.1 (Vals)	Vals AI	68.5%	83.2%
MCP Atlas	Scale AI SEAL	79.1%†	–
HiL-Bench	Scale AI SEAL	41.7%	–
τ³-bench Banking	τ²-bench	40.2%†	–
τ³-Banking (AA)	Artificial Analysis	34.6%†	–
ITBench SRE (AA)	Artificial Analysis	46.7%†	49.4%
Analyst Agent (AA)	Artificial Analysis	43.8%†	–
CyberBench	Vals AI	–	78.0%
Finance Agent v2	Vals AI	51.5%	49.0%
Harvey's Legal Agent Benchmark v1	Vals AI	6.7%	1.7%
Legal Research Bench	Vals AI	38.5%	28.9%
SREBench	Vals AI	–	30.5%
Tax Agent Bench	Vals AI	23.7%	15.0%
Terminal-Bench 2.0 (Vals)	Vals AI	68.5%	–
Terminal-Bench 4.0 (Vals)	Vals AI	–	44.4%
Terminal-Bench Science	Vals AI	–	30.0%
Arena Search	Arena (LMArena)	1210	1229
PostTrainBench	Epoch AI Benchmarking Hub	28.6%†	–
ExploitBench	Epoch AI Benchmarking Hub	26.5%	–
GBAEval	Epoch AI Benchmarking Hub	43.8%	–
Vending-Bench 2	Andon Labs	10936.8	14427.9†
AutomationBench	Artificial Analysis	–	61.6%
GDP.pdf (AA)	Artificial Analysis	–	25.2%
Harvey LAB-AA v1.1	Harvey	–	3.6%
AA-Briefcase v1.1	Artificial Analysis	–	1476
Design Arena Agentic	Design Arena	–	1212†
Terminal-Bench-Science 0.1 (AA)	Artificial Analysis	–	30.0%
CWE-Bench (AA)	Artificial Analysis	–	64.2%
DeepSec-Bench (AA)	Artificial Analysis	–	46.3%
CyberGym end-to-end (AA)	Artificial Analysis	–	0.0%
Maths
FrontierMath Tiers 1–3	Epoch AI Benchmarking Hub	70.2%†	89.8%
FrontierMath Tier 4	Epoch AI Benchmarking Hub	31.7%†	90.0%
OTIS Mock AIME	Epoch AI Benchmarking Hub	86.7%†	100.0%
ProofBench	Vals AI	54.0%†	83.0%†
LiveBench Mathematics	LiveBench	92.8%†	96.4%
AIME (Vals)	Vals AI	96.3%	–
AIME 2026	MathArena	95.8%†	–
HMMT February 2026	MathArena	93.9%†	–
MathArena Apex	MathArena	40.6%†	–
Arena Maths	Arena (LMArena)	1490	1440
Knowledge
SimpleQA Verified	Epoch AI Benchmarking Hub	51.7%†	60.7%
LiveBench 1.0 Data Analysis	LiveBench	78.3%†	81.2%
AA-Omniscience v1.1	Artificial Analysis	–	21.4
MMLU-Pro	Vals AI	89.9%	–
LegalBench	Vals AI	85.3%	–
CorpFin	Vals AI	66.1%	–
TaxEval	Vals AI	75.3%	–
PRBench Legal	Scale AI SEAL	–	38.6%†
BioMysteryBench	Vals AI	–	74.8%
CaseLaw v2	Vals AI	68.4%	–
Excel Modeling Benchmark	Vals AI	63.7%	71.5%
MedCode	Vals AI	54.9%	47.1%
MedScribe	Vals AI	83.0%	82.0%
Public Benefits Bench v1.1	Vals AI	–	56.6%
EBR-bench	Epoch AI Benchmarking Hub	19.1%†	53.3%
GDP.pdf	Epoch AI Benchmarking Hub	21.0%†	26.4%
AA-Omniscience v1.1: accuracy	Artificial Analysis	–	51.1%
AA-Omniscience v1.1: non-hallucination	Artificial Analysis	–	39.1%
HealthBench Professional (AA)	OpenAI	–	62.3%
Instruction following
LiveBench Language	LiveBench	77.9%†	85.3%
LiveBench Instruction Following	LiveBench	66.7%†	68.6%
IFBench	Artificial Analysis	58.6%†	–
Arena Instruction Following	Arena (LMArena)	1493	1448
Human preference
Arena Text	Arena (LMArena)	1494	1457
EQ-Bench 4	EQ-Bench	1293	–
Arena Creative Writing	Arena (LMArena)	1482	1430
Arena Multi-turn	Arena (LMArena)	1514	1466
Arena Longer Queries	Arena (LMArena)	1507	1466
Multimodal
Arena Vision	Arena (LMArena)	1319	1232
MMMU-Pro	Artificial Analysis	78.8%†	83.0%
MMMU-Pro (Vals)	Vals AI	85.5%	–
MortgageTax	Vals AI	70.3%	–
Blueprint-Bench 2	Epoch AI Benchmarking Hub	24.5%	36.9%†
AA-3D	Artificial Analysis	–	1131
Long context
AA-LCR v1.1	Artificial Analysis	78.7%†	83.7%
Arena Document	Arena (LMArena)	1494	–
MLCR	Artificial Analysis	–	33.9%
Composite
Epoch Capabilities Index	Epoch AI Benchmarking Hub	157.6	164.1†
LiveBench 1.0	LiveBench	76.5%†	79.3%
AA Intelligence Index v5.0	Artificial Analysis	–	44.2
AA Intelligence Index v4.3.2	Artificial Analysis	40.7†	47.6
AA Progress Index v1	Artificial Analysis	312.5†	334
Vals RSI Index	Vals AI	19.1%†	28.1%
Vals Science Index	Vals AI	–	45.0%
Vals Multimodal Index	Vals AI	67.4%	–
AA Cyber Index	Artificial Analysis	–	36.8
Safety & honesty
FORTRESS	Scale AI SEAL	–	13.5%†

Data as of 2026-11-09. Best configuration of each model; every score links to its source on the model pages.

DuelLab GameBench 2, release gb2-20261103-eaea31df94e6 (https://benchmarks.duellab.org/releases/gb2-20261103-eaea31df94e6/), CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Scores mapped to BenchLeader model names; not endorsed by DuelLab.

What changed

9 Nov 2026 GPT-6 Sol (max): BenchLeader Index 63.5 → 62.9.
9 Nov 2026 GPT-6 Sol (max): 2 score revisions.
8 Nov 2026 GPT-6 Sol (max): 1 score revision.
5 Nov 2026 Claude Opus 4.7: 1 score revision.
5 Nov 2026 GPT-6 Sol (max): 1 score revision.
4 Nov 2026 GPT-6 Sol (max): 6 new results (AA Intelligence Index v5.0, AA-Omniscience v1.1, CritPt v2 hard subset (AA)…).
3 Nov 2026 GPT-6 Sol (max): 1 score revision.
29 Oct 2026 GPT-6 Sol (max): 1 score revision.
28 Oct 2026 GPT-6 Sol (max): BenchLeader Index 64.1 → 63.5.
28 Oct 2026 GPT-6 Sol (max): 2 new results (AA Progress Index v1, HLE-Diamond (AA)).

Rankings: Best LLM overall · Best LLM for agents · Best cheap LLMs