GPT-5.6 Luna vs GPT-6.1 Sol

GPT-6.1 Sol leads GPT-5.6 Luna on coding, 82.4 to 58.0 on the Vibe Coding Index, and GPT-5.6 Luna costs 8.3x less per output token ($1.20 vs $10.00 per million). Updated October 22, 2026; 89 benchmarks have a result for both.

Replace GPT-5.6 Luna Replace GPT-6.1 Sol

GPT-5.6 LunaOpenAI

Coding: 58.0
Overall: 61.6
Output $/M: $1.20

GPT-6.1 SolOpenAI

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

vs boards won of 89 shared

GPT-5.6 Luna 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 58.0 for GPT-5.6 Luna, though on 5 benchmarks against 6.

Pick GPT-5.6 Luna for output tokens 8.3x cheaper ($1.20 vs $10.00 per million) and work measured by CyberBench (Vals AI) or Finance Agent (Vals AI), where it leads.

Model AGPT-5.6 LunaOpenAI58.0/1006 independent benchmarks$0.04 per solved task Model BGPT-6.1 SolOpenAI82.4/1005 independent benchmarksNo cost per solved task

893114

Shared results: 89
GPT-5.6 Luna only: 31
GPT-6.1 Sol only: 14
Like-for-like categories: 8 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 58.0.
6 and 5 benchmarks behind the scores
Intelligence
AA Intelligence Index
GPT-6.1 Sol
GPT-6.1 Sol leads, 51.8 against 37.3.
Same board, both measured
Agentic work
AA Agentic Index
No call
Only GPT-5.6 Luna has a AA Agentic Index result, 42.1.
Directional only
Reasoning
GPQA Diamond
No call
Only GPT-5.6 Luna has a GPQA Diamond result, 91.7%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.6 Luna has a MMLU Pro result, 86.0%.
Directional only
Web design
Design Arena: websites
GPT-6.1 Sol
GPT-6.1 Sol leads, 1321 against 1255.
Same board, both measured
General
Vals Index
No call
Only GPT-6.1 Sol has a Vals Index result, 63.9%.
Directional only
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GPT-5.6 Luna
GPT-5.6 Luna $0.0008, GPT-6.1 Sol $0.0070 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.6 Luna has the number, $0.04.
Directional only

At a glance

Coding index: GPT-5.6 Luna 58.0 from 6 benchmarks, GPT-6.1 Sol 82.4 from 5 benchmarks.
Widest category: Agentic work, 23.2 points apart on average over 12 shared benchmarks.
Widest single gap: Mystery game puzzles: GPT-5.6 Luna 21.0% against GPT-6.1 Sol 80.0%, 59.0 points apart on a 0 to 100 scale.
Output price: GPT-5.6 Luna $1.20 against GPT-6.1 Sol $10.00 per million output tokens, 8.3x apart.
Context window: Both take 1.05M tokens.

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	GPT-5.6 Luna	GPT-6.1 Sol
Coding	1	16
Intelligence	0	2
Agentic work	2	10
Reasoning	0	13
Math	0	6
Knowledge	0	7
Web design	0	7
General	2	23
All shared boards	5	84

CodingLike-for-likeSix of these boards feed the Vibe Coding Index116

Coding benchmarks for GPT-5.6 Luna and GPT-6.1 Sol
Benchmark	GPT-5.6 Luna	GPT-6.1 Sol	Leader
LiveBench coding	73.6%	96.0%	GPT-6.1 Sol
LMArena WebDev	1518	1753	GPT-6.1 Sol
AA Coding Index	71.4	Not measured	Only GPT-5.6 Luna measured
SWE-bench Verified (Vals AI)	93.0%	Not measured	Only GPT-5.6 Luna measured
Terminal-Bench 4 (Vals AI)	11.6%	55.0%	GPT-6.1 Sol
Vibe Code Bench (Vals AI)	77.1%	88.9%	GPT-6.1 Sol
Code migration (Vals AI)	44.5%	65.1%	GPT-6.1 Sol
ProgramBench (Vals AI)	0.0%	3.0%	GPT-6.1 Sol
IOI (Vals AI)	61.8%	96.9%	GPT-6.1 Sol
Terminal-Bench 2.1 (Vals AI)	79.0%	Not measured	Only GPT-5.6 Luna measured
SWE-bench Multimodal (Vals AI)	Not measured	43.5%	Only GPT-6.1 Sol measured
Vibe Code Bench 1-100 (Vals AI)	22.6%	Not measured	Only GPT-5.6 Luna measured
SkillsBench (Vals AI)	60.5%	Not measured	Only GPT-5.6 Luna measured
CyberBench (Vals AI)	73.6%	39.3%	GPT-5.6 Luna
SciCode	53.6%	55.8%	GPT-6.1 Sol
FrontierCode	39.8%	50.2%	GPT-6.1 Sol
WeirdML	60.9%	Not measured	Only GPT-5.6 Luna measured
ALE-Bench	1667.4	2743.8	GPT-6.1 Sol
LMArena Text: coding	1466	1478	GPT-6.1 Sol
LMArena Text: software and IT	1463	1476	GPT-6.1 Sol
LMArena WebDev: React	1508	1754	GPT-6.1 Sol
LMArena WebDev: HTML	1520	1800	GPT-6.1 Sol
LMArena WebDev: from an image	1517	1702	GPT-6.1 Sol
SciCode	6.2%	9.2%	GPT-6.1 Sol
SWE-Bench Pro V2	Not measured	96.1%	Only GPT-6.1 Sol measured
Neither model has a result on the other 18 boards here

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

Intelligence benchmarks for GPT-5.6 Luna and GPT-6.1 Sol
Benchmark	GPT-5.6 Luna	GPT-6.1 Sol	Leader
AA Intelligence Index	37.3	51.8	GPT-6.1 Sol
Epoch Capabilities Index	156.5	168.4	GPT-6.1 Sol

Agentic workLike-for-likePublic boards, shown as published, kept out of the index210

Agentic work benchmarks for GPT-5.6 Luna and GPT-6.1 Sol
Benchmark	GPT-5.6 Luna	GPT-6.1 Sol	Leader
AA Agentic Index	42.1	Not measured	Only GPT-5.6 Luna measured
Design Arena: agents building web apps	Not measured	1307	Only GPT-6.1 Sol measured
Design Arena: agents building mobile apps	Not measured	1224	Only GPT-6.1 Sol measured
Design Arena: spreadsheets	Not measured	1270	Only GPT-6.1 Sol measured
LiveBench research	51.0%	83.5%	GPT-6.1 Sol
LiveBench browser	68.0%	88.0%	GPT-6.1 Sol
LiveBench long agentic	30.4%	73.0%	GPT-6.1 Sol
SREBench (Vals AI)	1.5%	50.8%	GPT-6.1 Sol
Finance Agent (Vals AI)	55.0%	52.0%	GPT-5.6 Luna
Tax Agent Bench (Vals AI)	24.8%	21.8%	GPT-5.6 Luna
Legal Research Bench (Vals AI)	36.5%	38.5%	GPT-6.1 Sol
Harvey's Legal Agent Benchmark (Vals AI)	Not measured	6.3%	Only GPT-6.1 Sol measured
Excel Modeling Benchmark (Vals AI)	67.1%	70.8%	GPT-6.1 Sol
BioMysteryBench (Vals AI)	61.5%	79.6%	GPT-6.1 Sol
Terminal-Bench-Science (Vals AI)	0.0%	52.9%	GPT-6.1 Sol
Vals Science Index	25.3%	59.6%	GPT-6.1 Sol
Robo-bench (Vals AI)	Not measured	28.3%	Only GPT-6.1 Sol measured
APEX-Agents	43.0%	60.0%	GPT-6.1 Sol
BALROG	45.6%	Not measured	Only GPT-5.6 Luna measured
SpireClimb	Not measured	24.7%	Only GPT-6.1 Sol measured
Vending-Bench 2	$4,095	Not measured	Only GPT-5.6 Luna measured
Neither model has a result on the other 21 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index013

Reasoning benchmarks for GPT-5.6 Luna and GPT-6.1 Sol
Benchmark	GPT-5.6 Luna	GPT-6.1 Sol	Leader
GPQA Diamond	91.7%	Not measured	Only GPT-5.6 Luna measured
LiveBench reasoning	85.6%	92.6%	GPT-6.1 Sol
MysteryMechanism (Vals AI)	14.4%	46.4%	GPT-6.1 Sol
MMMU Pro (Vals AI)	85.0%	Not measured	Only GPT-5.6 Luna measured
GPQA Diamond (Artificial Analysis run)	91.1%	Not measured	Only GPT-5.6 Luna measured
Humanity's Last Exam (Artificial Analysis run)	39.5%	52.9%	GPT-6.1 Sol
GPQA Diamond (Epoch AI run)	91.6%	95.4%	GPT-6.1 Sol
ARC-AGI	88.0%	98.5%	GPT-6.1 Sol
ARC-AGI-2	59.5%	94.2%	GPT-6.1 Sol
SimpleBench	46.8%	Not measured	Only GPT-5.6 Luna measured
Chess puzzles	43.0%	68.0%	GPT-6.1 Sol
Mystery game puzzles	21.0%	80.0%	GPT-6.1 Sol
EBR-bench	Not measured	54.3%	Only GPT-6.1 Sol measured
LMArena Text: hard prompts	1451	1463	GPT-6.1 Sol
LMArena Text: expert	1478	1489	GPT-6.1 Sol
LMArena Text: hard prompts in English	1460	1465	GPT-6.1 Sol
LMArena Vision: diagrams	1273	1306	GPT-6.1 Sol
LMArena Vision: homework	1282	1356	GPT-6.1 Sol
Kagi LLM Benchmark	49.1%	Not measured	Only GPT-5.6 Luna measured
Neither model has a result on the other 4 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index06

Math benchmarks for GPT-5.6 Luna and GPT-6.1 Sol
Benchmark	GPT-5.6 Luna	GPT-6.1 Sol	Leader
OTIS Mock AIME	98.3%	100.0%	GPT-6.1 Sol
FrontierMath, tiers 1 to 3	82.1%	93.7%	GPT-6.1 Sol
FrontierMath, tier 4	61.0%	100.0%	GPT-6.1 Sol
ProofBench	60.0%	99.0%	GPT-6.1 Sol
LMArena Text: math	1459	1489	GPT-6.1 Sol
LMArena Text: mathematical work	1470	1513	GPT-6.1 Sol
MathArena	Not measured	84.0%	Only GPT-6.1 Sol measured
Neither model has a result on the other 7 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index07

Knowledge benchmarks for GPT-5.6 Luna and GPT-6.1 Sol
Benchmark	GPT-5.6 Luna	GPT-6.1 Sol	Leader
MMLU Pro	86.0%	Not measured	Only GPT-5.6 Luna measured
LegalBench (Vals AI)	84.0%	Not measured	Only GPT-5.6 Luna measured
CorpFin (Vals AI)	64.2%	Not measured	Only GPT-5.6 Luna measured
TaxEval (Vals AI)	76.2%	Not measured	Only GPT-5.6 Luna measured
MortgageTax (Vals AI)	67.3%	Not measured	Only GPT-5.6 Luna measured
MedCode (Vals AI)	42.4%	48.8%	GPT-6.1 Sol
SimpleQA Verified	41.0%	73.9%	GPT-6.1 Sol
LMArena Text: science	1433	1444	GPT-6.1 Sol
LMArena Text: medicine and healthcare	1399	1433	GPT-6.1 Sol
LMArena Text: legal and government	1446	1471	GPT-6.1 Sol
LMArena Text: business and finance	1439	1445	GPT-6.1 Sol
FACTS Benchmark Suite	35.0%	75.3%	GPT-6.1 Sol
PRBench Finance	Not measured	46.2%	Only GPT-6.1 Sol measured
PRBench Legal	Not measured	47.9%	Only GPT-6.1 Sol measured
Neither model has a result on the other 6 boards here

Web designLike-for-likePublic boards, shown as published, kept out of the index07

Web design benchmarks for GPT-5.6 Luna and GPT-6.1 Sol
Benchmark	GPT-5.6 Luna	GPT-6.1 Sol	Leader
Design Arena: websites	1255	1321	GPT-6.1 Sol
Design Arena: UI components	1248	1323	GPT-6.1 Sol
Design Arena: game dev	1195	1393	GPT-6.1 Sol
Design Arena: data viz	1212	1286	GPT-6.1 Sol
Design Arena: 3D	1121	1458	GPT-6.1 Sol
Design Arena: all code categories	1230	1346	GPT-6.1 Sol
Design Arena: SVG	1193	Not measured	Only GPT-5.6 Luna measured
Design Arena: ASCII art	1142	Not measured	Only GPT-5.6 Luna measured
LiveBench design	76.0%	82.1%	GPT-6.1 Sol

GeneralLike-for-likePublic boards, shown as published, kept out of the index223

General benchmarks for GPT-5.6 Luna and GPT-6.1 Sol
Benchmark	GPT-5.6 Luna	GPT-6.1 Sol	Leader
Vals Index	Not measured	63.9%	Only GPT-6.1 Sol measured
LiveBench data analysis	78.0%	82.7%	GPT-6.1 Sol
Public Benefits Bench (Vals AI)	61.2%	59.3%	GPT-5.6 Luna
SAGE (Vals AI)	44.2%	46.5%	GPT-6.1 Sol
MedScribe (Vals AI)	84.4%	86.5%	GPT-6.1 Sol
Vals Multimodal Index	69.1%	Not measured	Only GPT-5.6 Luna measured
Long context reasoning (AA-LCR)	83.7%	84.0%	GPT-6.1 Sol
DTBench	89.1%	96.5%	GPT-6.1 Sol
LMCA	48.5%	62.8%	GPT-6.1 Sol
Surface Evolver Bench	61.9%	Not measured	Only GPT-5.6 Luna measured
Furniture assembly	42.5%	80.0%	GPT-6.1 Sol
LMArena Text	1431	1443	GPT-6.1 Sol
LMArena Text: instruction following	1437	1466	GPT-6.1 Sol
LMArena Text: creative writing	1396	1425	GPT-6.1 Sol
LMArena Vision	1257	1288	GPT-6.1 Sol
LMArena Text: English	1441	1450	GPT-6.1 Sol
LMArena Text: non-English	1417	1433	GPT-6.1 Sol
LMArena Text: Chinese	1470	1487	GPT-6.1 Sol
LMArena Text: German	1455	Not measured	Only GPT-5.6 Luna measured
LMArena Text: Japanese	1415	Not measured	Only GPT-5.6 Luna measured
LMArena Text: Korean	1415	Not measured	Only GPT-5.6 Luna measured
LMArena Text: French	1458	1460	GPT-6.1 Sol
LMArena Text: Spanish	1446	1439	GPT-5.6 Luna
LMArena Text: Russian	1427	1457	GPT-6.1 Sol
LMArena Text: Polish	1405	Not measured	Only GPT-5.6 Luna measured
LMArena Text: multi-turn	1434	1442	GPT-6.1 Sol
LMArena Text: longer queries	1436	1458	GPT-6.1 Sol
LMArena Text: writing and language	1419	1444	GPT-6.1 Sol
LMArena Text: entertainment and media	1402	1426	GPT-6.1 Sol
LMArena Vision: English	1263	1274	GPT-6.1 Sol
LMArena Vision: Chinese	1294	Not measured	Only GPT-5.6 Luna measured
LMArena Vision: reading text	1264	1289	GPT-6.1 Sol
LMArena Vision: humor	1190	Not measured	Only GPT-5.6 Luna measured
LMArena Vision: creative writing	1257	1301	GPT-6.1 Sol
LMArena Document	1457	Not measured	Only GPT-5.6 Luna measured
MultiChallenge	Not measured	82.0%	Only GPT-6.1 Sol measured
EQ-Bench 4	1156	Not measured	Only GPT-5.6 Luna measured
Neither model has a result on the other 11 boards here

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

Image generation benchmarks for GPT-5.6 Luna and GPT-6.1 Sol
Benchmark	GPT-5.6 Luna	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-5.6 Luna$0.0008Fits in one request

GPT-6.1 Sol$0.0070Fits in one request

GPT-5.6 Luna costs less

Repository review

50K input + 3K output tokens

GPT-5.6 Luna$0.014Fits in one request

GPT-6.1 Sol$0.130Fits in one request

GPT-5.6 Luna costs less

Agent loop

200K input + 10K output tokens

GPT-5.6 Luna$0.052Fits in one request

GPT-6.1 Sol$0.500Fits in one request

GPT-5.6 Luna 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 GPT-5.6 Luna and GPT-6.1 Sol
Specification	OpenAI GPT-5.6 Luna	OpenAI GPT-6.1 Sol
Maker	OpenAI	OpenAI
Weights	No public weights listed	No public weights listed
Released	July 9, 2026	September 29, 2026
Context window	1.05M	1.05M
Input $/Mtok	$0.20	$2.00
Output $/Mtok	$1.20	$10.00
Coding index	58.0	82.4
Independent measurements behind it	6	5
Cost per solved task	$0.04	Not computable
Source	OpenRouter listing	OpenRouter listing

Questions

Is GPT-5.6 Luna 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 58.0 for GPT-5.6 Luna, though on 5 benchmarks against 6. Pick GPT-5.6 Luna for output tokens 8.3x cheaper ($1.20 vs $10.00 per million) and work measured by CyberBench (Vals AI) or Finance Agent (Vals AI), where it leads.

Which is cheaper, GPT-5.6 Luna or GPT-6.1 Sol?

GPT-5.6 Luna costs $0.20 per million input tokens and $1.20 per million output tokens; GPT-6.1 Sol costs $2.00 and $10.00. Cost per solved task is known for GPT-5.6 Luna only.

Which has the bigger context window, GPT-5.6 Luna or GPT-6.1 Sol?

Neither: both take 1.05M tokens.

How many benchmarks is the GPT-5.6 Luna vs GPT-6.1 Sol comparison based on?

89 benchmarks have a result for both models as of October 22, 2026. GPT-5.6 Luna's coding index rests on 6 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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GPT-5.6 Luna or GPT-6.1 Sol: which to pick

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

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