GPT-5.6 Sol vs Muse Spark 1.3

GPT-5.6 Sol leads Muse Spark 1.3 on coding, 73.5 to 57.4 on the Vibe Coding Index, and Muse Spark 1.3 costs 4.7x less per output token ($4.25 vs $20.00 per million). Updated October 22, 2026; 90 benchmarks have a result for both.

Replace GPT-5.6 Sol Replace Muse Spark 1.3

GPT-5.6 SolOpenAI

Coding: 73.5
Overall: 74.7
Output $/M: $20.00

Muse Spark 1.3Meta

Coding: 57.4
Overall: 68.6
Output $/M: $4.25

vs boards won of 90 shared, 1 tied

GPT-5.6 Sol or Muse Spark 1.3: which to pick

Pick GPT-5.6 Sol for coding: it scores 73.5 on the Vibe Coding Index against 57.4 for Muse Spark 1.3.

Pick Muse Spark 1.3 for output tokens 4.7x cheaper ($4.25 vs $20.00 per million) and work measured by LiveBench coding or LMArena WebDev, where it leads.

Model AGPT-5.6 SolOpenAI73.5/1006 independent benchmarks$1.20 per solved task Model BMuse Spark 1.3Meta57.4/1004 independent benchmarksNo cost per solved task

90492

Shared results: 90
GPT-5.6 Sol only: 49
Muse Spark 1.3 only: 2
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-5.6 Sol
GPT-5.6 Sol scores 73.5 against 57.4.
6 and 4 benchmarks behind the scores
Intelligence
AA Intelligence Index
Muse Spark 1.3
Muse Spark 1.3 leads, 48.1 against 47.0.
Same board, both measured
Agentic work
AA Agentic Index
Muse Spark 1.3
Muse Spark 1.3 leads, 55.5 against 50.2.
Same board, both measured
Reasoning
GPQA Diamond
No call
Only GPT-5.6 Sol has a GPQA Diamond result, 95.2%.
Directional only
Knowledge
MMLU Pro
No call
Only GPT-5.6 Sol has a MMLU Pro result, 89.1%.
Directional only
Web design
Design Arena: websites
Muse Spark 1.3
Muse Spark 1.3 leads, 1356 against 1321.
Same board, both measured
Long documents
Listed context window
GPT-5.6 Sol
GPT-5.6 Sol takes 1.05M tokens against 1.05M.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Muse Spark 1.3
GPT-5.6 Sol $0.014, Muse Spark 1.3 $0.0034 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
No call
Only GPT-5.6 Sol has the number, $1.20.
Directional only

At a glance

Coding index: GPT-5.6 Sol 73.5 from 6 benchmarks, Muse Spark 1.3 57.4 from 4 benchmarks.
Widest category: Math, 13.7 points apart on average over 6 shared benchmarks.
Widest single gap: IOI (Vals AI): GPT-5.6 Sol 91.2% against Muse Spark 1.3 43.9%, 47.2 points apart on a 0 to 100 scale.
Output price: GPT-5.6 Sol $20.00 against Muse Spark 1.3 $4.25 per million output tokens, 4.7x apart.
Context window: GPT-5.6 Sol takes 1.05M tokens, Muse Spark 1.3 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	GPT-5.6 Sol	Muse Spark 1.3	Ties
Coding	9	9
Intelligence	1	1
Agentic work	7	7
Reasoning	5	4	1 tie
Math	5	1
Knowledge	0	4
Web design	5	4
General	5	22
All shared boards	37	52	1 tie

CodingLike-for-likeSix of these boards feed the Vibe Coding Index99

Coding benchmarks for GPT-5.6 Sol and Muse Spark 1.3
Benchmark	GPT-5.6 Sol	Muse Spark 1.3	Leader
LiveBench coding	89.7%	90.2%	Muse Spark 1.3
LMArena WebDev	1616	1659	Muse Spark 1.3
AA Coding Index	77.4	75.8	GPT-5.6 Sol
LiveCodeBench (Vals AI)	82.6%	Not measured	Only GPT-5.6 Sol measured
SWE-bench Verified (Vals AI)	96.2%	Not measured	Only GPT-5.6 Sol measured
Terminal-Bench 4 (Vals AI)	37.9%	10.6%	GPT-5.6 Sol
Vibe Code Bench (Vals AI)	80.5%	82.9%	Muse Spark 1.3
Code migration (Vals AI)	52.9%	27.6%	GPT-5.6 Sol
ProgramBench (Vals AI)	1.5%	0.5%	GPT-5.6 Sol
IOI (Vals AI)	91.2%	43.9%	GPT-5.6 Sol
Terminal-Bench 2.1 (Vals AI)	85.8%	72.3%	GPT-5.6 Sol
Vibe Code Bench 1-100 (Vals AI)	20.0%	Not measured	Only GPT-5.6 Sol measured
SkillsBench (Vals AI)	54.1%	Not measured	Only GPT-5.6 Sol measured
CyberBench (Vals AI)	76.3%	69.4%	GPT-5.6 Sol
SciCode	57.8%	59.7%	Muse Spark 1.3
Terminal-Bench Hard (Artificial Analysis run)	65.9%	Not measured	Only GPT-5.6 Sol measured
FrontierCode	47.5%	Not measured	Only GPT-5.6 Sol measured
FrontierSWE	32.2%	25.8%	GPT-5.6 Sol
GSO-Bench	76.5%	Not measured	Only GPT-5.6 Sol measured
WeirdML	88.8%	Not measured	Only GPT-5.6 Sol measured
MirrorCode	20.0%	Not measured	Only GPT-5.6 Sol measured
ALE-Bench	2176.9	1688.3	GPT-5.6 Sol
LMArena Text: coding	1496	1510	Muse Spark 1.3
LMArena Text: software and IT	1489	1511	Muse Spark 1.3
LMArena WebDev: React	1620	1672	Muse Spark 1.3
LMArena WebDev: HTML	1618	1653	Muse Spark 1.3
LMArena WebDev: from an image	1609	1640	Muse Spark 1.3
SciCode	10.8%	Not measured	Only GPT-5.6 Sol measured
Neither model has a result on the other 11 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11

Intelligence benchmarks for GPT-5.6 Sol and Muse Spark 1.3
Benchmark	GPT-5.6 Sol	Muse Spark 1.3	Leader
AA Intelligence Index	47.0	48.1	Muse Spark 1.3
Epoch Capabilities Index	162.8	157.2	GPT-5.6 Sol

Agentic workLike-for-likePublic boards, shown as published, kept out of the index77

Agentic work benchmarks for GPT-5.6 Sol and Muse Spark 1.3
Benchmark	GPT-5.6 Sol	Muse Spark 1.3	Leader
AA Agentic Index	50.2	55.5	Muse Spark 1.3
Design Arena: agents building web apps	1245	1297	Muse Spark 1.3
Design Arena: agents building full-stack apps	1261	1295	Muse Spark 1.3
Design Arena: agents building mobile apps	1248	1218	GPT-5.6 Sol
Design Arena: agents building Android apps	1240	Not measured	Only GPT-5.6 Sol measured
Design Arena: agents building Godot games	1260	1241	GPT-5.6 Sol
Design Arena: agents building games	1266	Not measured	Only GPT-5.6 Sol measured
Design Arena: HTML slides	1236	Not measured	Only GPT-5.6 Sol measured
Design Arena: PowerPoint slides	1215	1219	Muse Spark 1.3
Design Arena: spreadsheets	Not measured	1062	Only Muse Spark 1.3 measured
LiveBench research	54.5%	68.6%	Muse Spark 1.3
LiveBench browser	88.0%	80.0%	GPT-5.6 Sol
LiveBench long agentic	48.5%	40.4%	GPT-5.6 Sol
SREBench (Vals AI)	30.5%	Not measured	Only GPT-5.6 Sol measured
Finance Agent (Vals AI)	53.8%	58.9%	Muse Spark 1.3
Tax Agent Bench (Vals AI)	31.1%	36.0%	Muse Spark 1.3
Legal Research Bench (Vals AI)	48.1%	40.9%	GPT-5.6 Sol
Excel Modeling Benchmark (Vals AI)	72.3%	62.7%	GPT-5.6 Sol
BioMysteryBench (Vals AI)	71.1%	Not measured	Only GPT-5.6 Sol measured
Terminal-Bench-Science (Vals AI)	20.0%	4.3%	GPT-5.6 Sol
Vals Science Index	41.5%	Not measured	Only GPT-5.6 Sol measured
Time Horizon Index (Vals AI)	23.8%	Not measured	Only GPT-5.6 Sol measured
CUA-bench (Vals AI)	8.3%	Not measured	Only GPT-5.6 Sol measured
τ²-Bench Telecom	85.1%	Not measured	Only GPT-5.6 Sol measured
APEX-Agents	Not measured	58.6%	Only Muse Spark 1.3 measured
OSWorld 2.0	27.3%	Not measured	Only GPT-5.6 Sol measured
BALROG	60.0%	Not measured	Only GPT-5.6 Sol measured
PostTrainBench	36.2%	Not measured	Only GPT-5.6 Sol measured
Vending-Bench 2	$9,619	Not measured	Only GPT-5.6 Sol measured
LMArena Search	1261	Not measured	Only GPT-5.6 Sol measured
Neither model has a result on the other 11 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index54

Reasoning benchmarks for GPT-5.6 Sol and Muse Spark 1.3
Benchmark	GPT-5.6 Sol	Muse Spark 1.3	Leader
GPQA Diamond	95.2%	Not measured	Only GPT-5.6 Sol measured
LiveBench reasoning	91.7%	89.7%	GPT-5.6 Sol
MysteryMechanism (Vals AI)	33.3%	Not measured	Only GPT-5.6 Sol measured
MMMU Pro (Vals AI)	88.8%	Not measured	Only GPT-5.6 Sol measured
GPQA Diamond (Artificial Analysis run)	94.1%	94.1%	Tie
Humanity's Last Exam (Artificial Analysis run)	49.5%	48.7%	GPT-5.6 Sol
GPQA Diamond (Epoch AI run)	93.5%	Not measured	Only GPT-5.6 Sol measured
ARC-AGI	97.5%	Not measured	Only GPT-5.6 Sol measured
ARC-AGI-2	92.5%	Not measured	Only GPT-5.6 Sol measured
SimpleBench	64.8%	Not measured	Only GPT-5.6 Sol measured
Chess puzzles	59.0%	37.0%	GPT-5.6 Sol
Mystery game puzzles	58.0%	25.0%	GPT-5.6 Sol
EBR-bench	44.8%	Not measured	Only GPT-5.6 Sol measured
LMArena Text: hard prompts	1483	1503	Muse Spark 1.3
LMArena Text: expert	1517	1519	Muse Spark 1.3
LMArena Text: hard prompts in English	1477	1500	Muse Spark 1.3
LMArena Vision: diagrams	1305	1330	Muse Spark 1.3
LMArena Vision: homework	1305	1296	GPT-5.6 Sol
Kagi LLM Benchmark	67.0%	Not measured	Only GPT-5.6 Sol measured
Neither model has a result on the other 3 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index51

Math benchmarks for GPT-5.6 Sol and Muse Spark 1.3
Benchmark	GPT-5.6 Sol	Muse Spark 1.3	Leader
OTIS Mock AIME	100.0%	99.2%	GPT-5.6 Sol
FrontierMath, tiers 1 to 3	89.1%	74.4%	GPT-5.6 Sol
FrontierMath, tier 4	82.9%	46.3%	GPT-5.6 Sol
ProofBench	83.0%	58.0%	GPT-5.6 Sol
LMArena Text: math	1473	1497	Muse Spark 1.3
LMArena Text: mathematical work	1496	1491	GPT-5.6 Sol
Neither model has a result on the other 7 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04

Knowledge benchmarks for GPT-5.6 Sol and Muse Spark 1.3
Benchmark	GPT-5.6 Sol	Muse Spark 1.3	Leader
MMLU Pro	89.1%	Not measured	Only GPT-5.6 Sol measured
LegalBench (Vals AI)	87.0%	Not measured	Only GPT-5.6 Sol measured
CorpFin (Vals AI)	64.4%	Not measured	Only GPT-5.6 Sol measured
TaxEval (Vals AI)	74.8%	Not measured	Only GPT-5.6 Sol measured
MortgageTax (Vals AI)	67.3%	Not measured	Only GPT-5.6 Sol measured
MedCode (Vals AI)	44.0%	Not measured	Only GPT-5.6 Sol measured
SimpleQA Verified	69.7%	Not measured	Only GPT-5.6 Sol measured
LMArena Text: science	1455	1507	Muse Spark 1.3
LMArena Text: medicine and healthcare	1431	1493	Muse Spark 1.3
LMArena Text: legal and government	1476	1499	Muse Spark 1.3
LMArena Text: business and finance	1457	1490	Muse Spark 1.3
FACTS Benchmark Suite	52.4%	Not measured	Only GPT-5.6 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 index54

Web design benchmarks for GPT-5.6 Sol and Muse Spark 1.3
Benchmark	GPT-5.6 Sol	Muse Spark 1.3	Leader
Design Arena: websites	1321	1356	Muse Spark 1.3
Design Arena: UI components	1335	1349	Muse Spark 1.3
Design Arena: game dev	1367	1328	GPT-5.6 Sol
Design Arena: data viz	1322	1343	Muse Spark 1.3
Design Arena: 3D	1384	1358	GPT-5.6 Sol
Design Arena: all code categories	1341	1352	Muse Spark 1.3
Design Arena: SVG	1314	1301	GPT-5.6 Sol
Design Arena: ASCII art	1304	1278	GPT-5.6 Sol
LiveBench design	81.6%	74.8%	GPT-5.6 Sol

GeneralLike-for-likePublic boards, shown as published, kept out of the index522

General benchmarks for GPT-5.6 Sol and Muse Spark 1.3
Benchmark	GPT-5.6 Sol	Muse Spark 1.3	Leader
LiveBench data analysis	79.8%	79.6%	GPT-5.6 Sol
Public Benefits Bench (Vals AI)	66.5%	Not measured	Only GPT-5.6 Sol measured
SAGE (Vals AI)	52.6%	Not measured	Only GPT-5.6 Sol measured
MedScribe (Vals AI)	85.2%	Not measured	Only GPT-5.6 Sol measured
Vals Multimodal Index	72.6%	Not measured	Only GPT-5.6 Sol measured
IFBench	72.7%	Not measured	Only GPT-5.6 Sol measured
Long context reasoning (AA-LCR)	84.0%	83.0%	GPT-5.6 Sol
DTBench	95.7%	96.5%	Muse Spark 1.3
LMCA	58.5%	53.9%	GPT-5.6 Sol
Surface Evolver Bench	93.1%	Not measured	Only GPT-5.6 Sol measured
Furniture assembly	56.7%	Not measured	Only GPT-5.6 Sol measured
LMArena Text	1457	1490	Muse Spark 1.3
LMArena Text: instruction following	1483	1479	GPT-5.6 Sol
LMArena Text: creative writing	1449	1462	Muse Spark 1.3
LMArena Vision	1281	1308	Muse Spark 1.3
LMArena Text: English	1457	1495	Muse Spark 1.3
LMArena Text: non-English	1451	1481	Muse Spark 1.3
LMArena Text: Chinese	1525	1532	Muse Spark 1.3
LMArena Text: German	1476	1513	Muse Spark 1.3
LMArena Text: Japanese	1472	1470	GPT-5.6 Sol
LMArena Text: Korean	1442	1490	Muse Spark 1.3
LMArena Text: French	1472	1511	Muse Spark 1.3
LMArena Text: Spanish	1443	1496	Muse Spark 1.3
LMArena Text: Russian	1471	1491	Muse Spark 1.3
LMArena Text: Polish	1459	1490	Muse Spark 1.3
LMArena Text: multi-turn	1461	1487	Muse Spark 1.3
LMArena Text: longer queries	1481	1488	Muse Spark 1.3
LMArena Text: writing and language	1462	1470	Muse Spark 1.3
LMArena Text: entertainment and media	1450	1457	Muse Spark 1.3
LMArena Vision: English	1280	1298	Muse Spark 1.3
LMArena Vision: Chinese	1313	1384	Muse Spark 1.3
LMArena Vision: reading text	1290	1319	Muse Spark 1.3
LMArena Vision: humor	1246	1293	Muse Spark 1.3
LMArena Vision: creative writing	1283	1296	Muse Spark 1.3
LMArena Document	1483	Not measured	Only GPT-5.6 Sol 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 Sol and Muse Spark 1.3
Benchmark	GPT-5.6 Sol	Muse Spark 1.3	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$0.014Fits in one request

Muse Spark 1.3$0.0034Fits in one request

Muse Spark 1.3 costs less

Repository review

50K input + 3K output tokens

GPT-5.6 Sol$0.260Fits in one request

Muse Spark 1.3$0.075Fits in one request

Muse Spark 1.3 costs less

Agent loop

200K input + 10K output tokens

GPT-5.6 Sol$1.00Fits in one request

Muse Spark 1.3$0.292Fits in one request

Muse Spark 1.3 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 Sol and Muse Spark 1.3
Specification	OpenAI GPT-5.6 Sol	Meta Muse Spark 1.3
Maker	OpenAI	Meta
Weights	No public weights listed	No public weights listed
Released	July 9, 2026	September 2, 2026
Context window	1.05M	1.05M
Input $/Mtok	$4.00	$1.25
Output $/Mtok	$20.00	$4.25
Coding index	73.5	57.4
Independent measurements behind it	6	4
Cost per solved task	$1.20	Not computable
Source	OpenRouter listing	OpenRouter listing

Questions

Is GPT-5.6 Sol better than Muse Spark 1.3 for coding?

Pick GPT-5.6 Sol for coding: it scores 73.5 on the Vibe Coding Index against 57.4 for Muse Spark 1.3. Pick Muse Spark 1.3 for output tokens 4.7x cheaper ($4.25 vs $20.00 per million) and work measured by LiveBench coding or LMArena WebDev, where it leads.

Which is cheaper, GPT-5.6 Sol or Muse Spark 1.3?

GPT-5.6 Sol costs $4.00 per million input tokens and $20.00 per million output tokens; Muse Spark 1.3 costs $1.25 and $4.25. Cost per solved task is known for GPT-5.6 Sol only.

Which has the bigger context window, GPT-5.6 Sol or Muse Spark 1.3?

GPT-5.6 Sol, with 1.05M tokens against 1.05M.

How many benchmarks is the GPT-5.6 Sol vs Muse Spark 1.3 comparison based on?

90 benchmarks have a result for both models as of October 22, 2026. GPT-5.6 Sol's coding index rests on 6 independent benchmarks and Muse Spark 1.3's on 4. Where only one model has a result, the page says so instead of naming a winner.

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GPT-5.6 Sol or Muse Spark 1.3: which to pick

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

Knowledge

Web design

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