Compare / Muse Wonder vs GPT-6 Sol

Muse Wonder vs GPT-6 Sol

Which is cheaper, which is more capable, and which does better at each kind of work, from 60 results on 4 sources that measured both models.

MetaMuse Wonder Released 12 Oct 2026 · $4.00 in · $20.00 out
OpenAIGPT-6 Sol Released 22 Sep 2026 · $2.00 in · $10.00 out
Muse Wonder wins 1419 too close to callGPT-6 Sol wins 27

Of the 60 results both models have, the better value on each. Results whose reported ranges overlap are too close to call.

Results as of 13 October 2026 (catalogue release 2026-10-13-2e2420e3c5cc). See also Meta vs OpenAI, every model from both labs.

Muse Wonder or GPT-6 Sol? The short answer

They score about the same, so pick GPT-6 Sol: it costs 4.2 times less per product listing on CatalogBench.

  • Spring Prompt overall: Muse Wonder 70, GPT-6 Sol 69 (out of 100; how the score works).
  • GPT-6 Sol is cheaper to run: $0.009 against $0.036 per product listing on CatalogBench (4.2 times less).
  • Muse Wonder is newer: released 12 Oct 2026, against 22 Sep 2026 for GPT-6 Sol.
  • On our own benchmarks, on the results both models have: GPT-6 Sol does better for product listings and marketing planning.

Head to head

70
Spring Prompt overall
69
$8.00
Price per million tokens, blendedlower is better
$4.00
1,048,576
Context window, tokens
1,050,000

Every fact side by side

Muse WonderGPT-6 Sol
Price per million tokens$4.00 in · $20.00 out$2.00 in · $10.00 out
Blended (3 in : 1 out)$8.00$4.00
Cheapest host, blended–$4.00 (Azure)
Cost per product listing (CatalogBench)$0.036$0.009
Cached input, per million$0.20 cached input$0.20 cached input
Intelligence Index–47.6
Spring Prompt overall7069
Output speed, tokens a second––
Context window1,048,576 tokens1,050,000 tokens
Released12 Oct 2026 (newer)22 Sep 2026
WeightsClosedClosed
Developer based inthe USthe US

Prices are the developer's list price where we have read it, otherwise the typical host on OpenRouter; see every model's price. Intelligence and speed from Artificial Analysis.

Which is better for what

Each model's rank among the models on sale today, for each kind of work, from our own benchmarks and licensed sources. Further right is better; the better rank is in green.

Product listingsTurning a sparse product feed and photos into listings that can go live 4 of 21 3 of 21
Decks from an analysisTurning a finished analysis into a deck you could present as it is 8 of 20 2 of 20
User surveysPlanning a user survey and reading its results without being misled 2 of 9 not measured
Marketing planningPlanning a year of ad spend without overspending 10 of 20 2 of 20
Agents and tool useMulti-step tasks with tools: support desks, coding agents, function calls not measured 5 of 164
Professional workReal tasks from banking, consulting and law, business documents and freelance projects not measured 13 of 51
Reasoning and knowledgeHard questions across science, maths and general knowledge not measured 11 of 198
WritingWhat people prefer in blind comparisons, and judged writing quality not measured 51 of 188
Sticking to the factsSummarising without inventing things, and factual answers not measured 49 of 152
Speed under pressureGood decisions against a real clock (fast chess) 12 of 24 10 of 24

Their slides, side by side

The same brief for both: Manchester store investment review for Hearthside Coffee, an invented company. First slide of each deck from DeckBench.

First slide of Muse Wonder's deck for Hearthside Coffee
Muse Wonder · deck rating 1,273 · needs work
First slide of GPT-6 Sol's deck for Hearthside Coffee
GPT-6 Sol · deck rating 1,464 · needs work

Every slide, side by side →

From our research

Every shared result

Each model's best result on every measure both have, grouped by benchmark, with the setting that produced it. Under each measure, every model that benchmark has measured is a grey tick, best to the right, so you can see where the two sit in the field. The headline measures of each benchmark come first; the rest are under "Show all". Green marks the better value; where a source reports ranges that overlap, neither is marked.

MeasureMuse WonderGPT-6 Sol
BulletBench measured by Spring Prompt · 3 results
Cost per game · Bullet 60sUS dollars, lower is better 28 · 24 of 29 measured $0.0663minimal reasoning $0.0297no reasoning
Ladder Elo · Bullet 60sladder Elo, higher is better 19 · 17 of 29 measured 409minimal reasoning 445no reasoning
Games lost on time · Bullet 60s% of games, lower is better 23 · 19 of 29 measured 58.3%minimal reasoning 50.0%no reasoning
CatalogBench measured by Spring Prompt · 3 results
Cost per productUS dollars, lower is better 17 · 10 of 21 measured $0.0361 $0.0085
Reliably publish-ready% of products, higher is better 3 · 3 of 21 measured 66.1% 66.1%
Reliably publish-ready · sales brief% of products, higher is better 4 · 2 of 21 measured 51.8% 67.9%
DeckBench measured by Spring Prompt · 3 results
Cost per deckUS dollars, lower is better 14 · 15 of 20 measured $0.18 $0.21
Deck ratingrating, higher is betterThe rating weighs each win by how strong the other deck was; the win rate counts wins against whichever decks a model happened to meet, so the two can disagree. 8 · 2 of 20 measured 1,273 1,464
Accurate decks% of tasks, higher is better 1 · 4 of 20 measured 100.0% 83.3%
ROASBench measured by Spring Prompt · 3 results
Overall scorescore out of 100, higher is better 10 · 2 of 20 measured 38.9 54.1
Audience scorescore out of 100, higher is better 12 · 1 of 20 measured 54.7 69.4
Business scorescore out of 100, higher is better 10 · 4 of 20 measured 34.5 52.9
Show all 60 results (48 more)
MeasureMuse WonderGPT-6 Sol
BulletBench measured by Spring Prompt · 2 results
Invalid moves · Bullet 60s% of moves, lower is better 1 · 1 of 29 measured 0.0%minimal reasoning 0.0%no reasoning
Median move time · Bullet 60smilliseconds, lower is better 25 · 20 of 29 measured 1.9 sminimal reasoning 1.6 sno reasoning
CatalogBench measured by Spring Prompt · 27 results
Channel compliance% of products, higher is better 14 · 1 of 21 measured 99.4% 100.0%
Channel rules broken% of products, lower is better 11 · 1 of 21 measured 0.6% 0.0%
Channel rules broken · sales brief% of products, lower is better 1 · 10 of 21 measured 0.0% 0.6%
Claims to check% of products, lower is better 1 · 1 of 21 measured 0.0% 0.0%
Claims to check · sales brief% of products, lower is better 1 · 1 of 21 measured 0.0% 0.0%
Conflicts caught% of conflicts, higher is better 1 · 1 of 21 measured 100.0% 100.0%
Content quality% of checks, higher is better 3 · 5 of 21 measured 98.3% 97.8%
Content quality · sales brief% of checks, higher is better 3 · 4 of 21 measured 98.5% 98.3%
Decision accuracy% of decisions, higher is better 3 · 4 of 21 measured 98.3% 98.0%
Failed outputs% of products, lower is better 1 · 1 of 21 measured 0.0% 0.0%
Failed outputs · sales brief% of products, lower is better 1 · 1 of 21 measured 0.0% 0.0%
Field accuracy% of missing fields, higher is better 1 · 9 of 21 measured 96.1% 93.7%
Invented values% of filled values, lower is better 11 · 10 of 21 measured 1.4% 1.0%
Missing UK information% of products, lower is better 1 · 1 of 21 measured 0.0% 0.0%
Missing UK information · sales brief% of products, lower is better 1 · 1 of 21 measured 0.0% 0.0%
Not findable% of products, lower is better 4 · 14 of 21 measured 3.6% 7.7%
Not findable · sales brief% of products, lower is better 8 · 16 of 21 measured 3.6% 7.1%
Publish-ready listings% of products, higher is better 3 · 3 of 21 measured 75.0% 75.0%
Publish-ready listings · sales brief% of products, higher is better 5 · 1 of 21 measured 67.3% 76.2%
Unsupported claimsclaims per product, lower is better 4 · 3 of 21 measured 0.21 0.08
Unsupported claims% of products, lower is better 4 · 3 of 21 measured 7.1% 1.8%
Unsupported claims · sales briefclaims per product, lower is better 5 · 3 of 21 measured 0.36 0.09
Unsupported claims · sales brief% of products, lower is better 5 · 2 of 21 measured 17.9% 3.0%
Wrong attributes% of products, lower is better 2 · 4 of 21 measured 13.1% 14.3%
Wrong attributes · sales brief% of products, lower is better 4 · 3 of 21 measured 14.3% 13.7%
Wrong category or variant% of products, lower is better 10 · 16 of 21 measured 2.4% 3.6%
Wrong category or variant · sales brief% of products, lower is better 10 · 14 of 21 measured 2.4% 3.0%
DeckBench measured by Spring Prompt · 13 results
Caveat dropped% of tasks, lower is better 1 · 1 of 20 measured 0.0% 0.0%
Clean layout% of tasks, higher is better 18 · 6 of 20 measured 16.7% 66.7%
Design quality% of the maximum, higher is better 9 · 2 of 20 measured 67.1% 87.9%
Draft figure quoted% of tasks, lower is better 1 · 1 of 20 measured 0.0% 0.0%
Findings missing% of tasks, lower is better 1 · 15 of 20 measured 0.0% 16.7%
Head-to-head win rate% of comparisons, higher is betterThe rating weighs each win by how strong the other deck was; the win rate counts wins against whichever decks a model happened to meet, so the two can disagree. 10 · 2 of 20 measured 63.2% 85.7%
Layout defects% of tasks, lower is better 18 · 6 of 20 measured 83.3% 33.3%
Misleading metric used% of tasks, lower is better 1 · 1 of 20 measured 0.0% 0.0%
Presentable decks% of tasks, higher is better 10 · 2 of 20 measured 16.7% 50.0%
Recommendation late or wrong% of tasks, lower is better 1 · 1 of 20 measured 0.0% 0.0%
Slides needing work% of tasks, lower is better 15 · 1 of 20 measured 66.7% 0.0%
Unsupported claims% of tasks, lower is better 1 · 1 of 20 measured 0.0% 0.0%
Unsupported numbers% of tasks, lower is better 1 · 1 of 20 measured 0.0% 0.0%
ROASBench measured by Spring Prompt · 6 results
Consistency scorescore out of 100, higher is better 12 · 2 of 20 measured 25.9 42.9
Contribution profitsimulated US dollars, higher is better 11 · 6 of 20 measured $489,176 $600,357
Cost of a runUS dollars, lower is better 15 · 11 of 20 measured $0.57 $0.24
Months over budgetmonths of 12, lower is better 1 · 1 of 20 measured 0 0
Planning scorescore out of 100, higher is better 4 · 9 of 20 measured 55.0 54.8
Return on ad spendprofit per $1 spent, higher is better 11 · 5 of 20 measured $0.41 $0.65

Quick answers

Is Muse Wonder better than GPT-6 Sol?

They score about the same, so pick GPT-6 Sol: it costs 4.2 times less per product listing on CatalogBench.

Which is cheaper, Muse Wonder or GPT-6 Sol?

GPT-6 Sol is cheaper to run: $0.009 against $0.036 per product listing on CatalogBench (4.2 times less).

Which is better for product listings, Muse Wonder or GPT-6 Sol?

GPT-6 Sol ranks 3 of 21 models on sale for turning a sparse product feed and photos into listings that can go live, against 4 for Muse Wonder.

Which is better for decks from an analysis, Muse Wonder or GPT-6 Sol?

GPT-6 Sol ranks 2 of 20 models on sale for turning a finished analysis into a deck you could present as it is, against 8 for Muse Wonder.

Which is better for marketing planning, Muse Wonder or GPT-6 Sol?

GPT-6 Sol ranks 2 of 20 models on sale for planning a year of ad spend without overspending, against 10 for Muse Wonder.

Which is better for speed under pressure, Muse Wonder or GPT-6 Sol?

GPT-6 Sol ranks 10 of 24 models on sale for good decisions against a real clock (fast chess), against 12 for Muse Wonder.

Which has the bigger context window, Muse Wonder or GPT-6 Sol?

GPT-6 Sol: 1,050,000 tokens, against 1,048,576 for Muse Wonder.

Run Muse Wonder and GPT-6 Sol on your own prompt

Benchmarks aren't your data. Try both side by side in the playground, with the cost of every answer.

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