Compare / Muse Spark 1.3 vs GPT-6.1 Terra
Muse Spark 1.3 vs GPT-6.1 Terra
Which is cheaper, which is more capable, and which does better at each kind of work, from 62 results on 4 sources that measured both models.
MetaMuse Spark 1.3
OpenAIGPT-6.1 Terra
Muse Spark 1.3 wins 914 too close to callGPT-6.1 Terra wins 39
Of the 62 results both models have, the better value on each. Results whose reported ranges overlap are too close to call.
Results as of 4 November 2026 (catalogue release 2026-11-04-56cfea57899a). See also Meta vs OpenAI, every model from both labs.
Muse Spark 1.3 or GPT-6.1 Terra? The short answer
Pick GPT-6.1 Terra: it scores higher (Spring Prompt overall 81 against 61) and costs less.
- Spring Prompt overall: Muse Spark 1.3 61, GPT-6.1 Terra 81 (out of 100; how the score works).
- GPT-6.1 Terra is cheaper to run: $0.004 against $0.016 per product listing on CatalogBench (4.6 times less).
- On our own benchmarks, on the results both models have: GPT-6.1 Terra does better for product listings, decks from an analysis and marketing planning.
Head to head
61
Spring Prompt overall
81
$2.00
Price per million tokens, blendedlower is better
$2.20
1,048,576
Context window, tokens
1,050,000
Every fact side by side
| Muse Spark 1.3 | GPT-6.1 Terra | |
|---|---|---|
| Price per million tokens | $1.25 in · $4.25 out | $1.10 in · $5.50 out |
| Blended (3 in : 1 out) | $2.00 | $2.20 |
| Cheapest host, blended | – | $2.00 (Azure) |
| Cost per product listing (CatalogBench) | $0.016 | $0.004 |
| Cached input, per million | $0.15 cached input | – |
| Intelligence Index | 48.1 | – |
| Spring Prompt overall | 61 | 81 |
| Output speed, tokens a second | 254 | – |
| Context window | 1,048,576 tokens | 1,050,000 tokens |
| Released | 2 Sep 2026 | – |
| Weights | Closed | Closed |
| Developer based in | the US | the 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
13 of 25
4 of 25
Decks from an analysisTurning a finished analysis into a deck you could present as it is
18 of 26
7 of 26
User surveysPlanning a user survey and reading its results without being misled
not measured
5 of 15
Marketing planningPlanning a year of ad spend without overspending
18 of 26
1 of 26
Agents and tool useMulti-step tasks with tools: support desks, coding agents, function calls
11 of 160
not measured
Professional workReal tasks from banking, consulting and law, business documents and freelance projects
8 of 51
not measured
Reasoning and knowledgeHard questions across science, maths and general knowledge
10 of 188
not measured
WritingWhat people prefer in blind comparisons, and judged writing quality
7 of 173
not measured
Sticking to the factsSummarising without inventing things, and factual answers
11 of 143
not measured
Speed under pressureGood decisions against a real clock (fast chess)
27 of 29
16 of 29
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.
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.
| Measure | Muse Spark 1.3 | GPT-6.1 Terra |
|---|---|---|
| BulletBench measured by Spring Prompt · 3 results | ||
| Cost per game · Bullet 60sUS dollars, lower is better 20 · 24 of 34 measured | $0.0142minimal reasoning | $0.0172low reasoning |
| Ladder Elo · Bullet 60sladder Elo, higher is better 31 · 23 of 34 measured | 33minimal reasoning | 358low reasoning |
| Games lost on time · Bullet 60s% of games, lower is better 33 · 27 of 34 measured | 91.7%minimal reasoning | 75.0%low reasoning |
| CatalogBench measured by Spring Prompt · 3 results | ||
| Cost per productUS dollars, lower is better 16 · 7 of 26 measured | $0.0164 | $0.0036 |
| Reliably publish-ready% of products, higher is better 11 · 5 of 25 measured | 48.2% | 64.3% |
| Reliably publish-ready · sales brief% of products, higher is better 13 · 2 of 25 measured | 10.7% | 67.9% |
| DeckBench measured by Spring Prompt · 3 results | ||
| Cost per deckUS dollars, lower is better 10 · 13 of 26 measured | $0.0463 | $0.0672 |
| 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. 18 · 7 of 26 measured | 867 | 1,355 |
| Accurate decks% of tasks, higher is better 19 · 1 of 26 measured | 16.7% | 100.0% |
| ROASBench measured by Spring Prompt · 3 results | ||
| Overall scorescore out of 100, higher is better 18 · 1 of 26 measured | 34.1 | 58.4 |
| Audience scorescore out of 100, higher is better 18 · 1 of 26 measured | 51.6 | 69.4 |
| Business scorescore out of 100, higher is better 18 · 1 of 26 measured | 25.8 | 59.1 |
Show all 62 results (50 more)
| Measure | Muse Spark 1.3 | GPT-6.1 Terra |
|---|---|---|
| BulletBench measured by Spring Prompt · 2 results | ||
| Invalid moves · Bullet 60s% of moves, lower is better 1 · 1 of 34 measured | 0.0%minimal reasoning | 0.0%low reasoning |
| Median move time · Bullet 60smilliseconds, lower is better 33 · 29 of 34 measured | 4.2 sminimal reasoning | 2.8 slow reasoning |
| CatalogBench measured by Spring Prompt · 28 results | ||
| Channel compliance% of products, higher is better 1 · 25 of 26 measured | 100.0% | 98.2% |
| Channel rules broken% of products, lower is better 1 · 23 of 26 measured | 0.0% | 1.8% |
| Channel rules broken · sales brief% of products, lower is better 1 · 1 of 26 measured | 0.0% | 0.0% |
| Claims to check% of products, lower is better 1 · 1 of 26 measured | 0.0% | 0.0% |
| Claims to check · sales brief% of products, lower is better 1 · 1 of 26 measured | 0.0% | 0.0% |
| Conflicts caught% of conflicts, higher is better 1 · 1 of 26 measured | 100.0% | 100.0% |
| Content quality% of checks, higher is better 10 · 9 of 26 measured | 97.7% | 97.7% |
| Content quality · sales brief% of checks, higher is better 7 · 5 of 26 measured | 98.2% | 98.3% |
| Decision accuracy% of decisions, higher is better 9 · 5 of 26 measured | 97.6% | 98.1% |
| Failed outputs% of products, lower is better 1 · 1 of 26 measured | 0.0% | 0.0% |
| Failed outputs · sales brief% of products, lower is better 1 · 1 of 26 measured | 0.0% | 0.0% |
| Field accuracy% of missing fields, higher is better 16 · 6 of 26 measured | 92.9% | 94.4% |
| Invented values% of filled values, lower is better 5 · 12 of 26 measured | 0.7% | 1.5% |
| Missing UK information% of products, lower is better 1 · 1 of 26 measured | 0.0% | 0.0% |
| Missing UK information · sales brief% of products, lower is better 1 · 1 of 26 measured | 0.0% | 0.0% |
| Not findable% of products, lower is better 15 · 23 of 26 measured | 6.0% | 10.7% |
| Not findable · sales brief% of products, lower is better 15 · 25 of 26 measured | 5.4% | 13.7% |
| Publish-ready listings% of products, higher is better 11 · 6 of 26 measured | 65.5% | 74.4% |
| Publish-ready listings · sales brief% of products, higher is better 12 · 3 of 26 measured | 34.5% | 74.4% |
| Time per productseconds, lower is better 22 · 9 of 26 measured | 47.5 | 10.1 |
| Unsupported claims% of products, lower is better 11 · 3 of 26 measured | 14.9% | 0.6% |
| Unsupported claimsclaims per product, lower is better 10 · 4 of 26 measured | 0.44 | 0.03 |
| Unsupported claims · sales brief% of products, lower is better 12 · 1 of 26 measured | 57.7% | 1.8% |
| Unsupported claims · sales briefclaims per product, lower is better 12 · 3 of 26 measured | 1.50 | 0.09 |
| Wrong attributes% of products, lower is better 12 · 5 of 26 measured | 16.7% | 14.9% |
| Wrong attributes · sales brief% of products, lower is better 4 · 7 of 26 measured | 14.3% | 14.9% |
| Wrong category or variant% of products, lower is better 22 · 5 of 26 measured | 4.2% | 1.8% |
| Wrong category or variant · sales brief% of products, lower is better 20 · 5 of 26 measured | 3.6% | 1.8% |
| DeckBench measured by Spring Prompt · 14 results | ||
| Caveat dropped% of tasks, lower is better 13 · 1 of 26 measured | 16.7% | 0.0% |
| Clean layout% of tasks, higher is better 24 · 3 of 26 measured | 0.0% | 83.3% |
| Design quality% of the maximum, higher is better 19 · 5 of 26 measured | 56.1% | 80.8% |
| Draft figure quoted% of tasks, lower is better 11 · 1 of 26 measured | 16.7% | 0.0% |
| Findings missing% of tasks, lower is better 1 · 1 of 26 measured | 0.0% | 0.0% |
| 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. 18 · 15 of 26 measured | 43.0% | 48.3% |
| Layout defects% of tasks, lower is better 24 · 3 of 26 measured | 100.0% | 16.7% |
| Misleading metric used% of tasks, lower is better 1 · 1 of 26 measured | 0.0% | 0.0% |
| Presentable decks% of tasks, higher is better 13 · 2 of 26 measured | 0.0% | 50.0% |
| Recommendation late or wrong% of tasks, lower is better 22 · 1 of 26 measured | 66.7% | 0.0% |
| Slides needing work% of tasks, lower is better 13 · 8 of 26 measured | 50.0% | 33.3% |
| Time per deckseconds, lower is better 11 · 16 of 26 measured | 89.4 | 135 |
| Unsupported claims% of tasks, lower is better 13 · 1 of 26 measured | 16.7% | 0.0% |
| Unsupported numbers% of tasks, lower is better 1 · 1 of 26 measured | 0.0% | 0.0% |
| ROASBench measured by Spring Prompt · 6 results | ||
| Consistency scorescore out of 100, higher is better 14 · 1 of 26 measured | 26.7 | 48.8 |
| Contribution profitsimulated US dollars, higher is better 17 · 6 of 26 measured | $337,251 | $701,059 |
| Cost of a runUS dollars, lower is better 13 · 9 of 26 measured | $0.18 | $0.11 |
| Months over budgetmonths of 12, lower is better 1 · 1 of 26 measured | 0 | 0 |
| Planning scorescore out of 100, higher is better 11 · 7 of 26 measured | 54.8 | 55.0 |
| Return on ad spendprofit per $1 spent, higher is better 17 · 2 of 26 measured | $0.29 | $0.71 |
Compare them with other models
- Meta vs OpenAIEvery model from both labs, best against best
- Muse Spark 1.3 vs DeepSeek-V4.1-Flash-1017Cheapest with similar intelligence
- Muse Spark 1.3 vs Claude Opus 5.5Most intelligent available today
- GPT-6.1 Terra vs Claude Opus 5.5Highest-scoring overall available today
- GPT-6.1 Terra vs GPT-6.1 SolJust below overall
Quick answers
Is Muse Spark 1.3 better than GPT-6.1 Terra?
Pick GPT-6.1 Terra: it scores higher (Spring Prompt overall 81 against 61) and costs less.
Which is cheaper, Muse Spark 1.3 or GPT-6.1 Terra?
GPT-6.1 Terra is cheaper to run: $0.004 against $0.016 per product listing on CatalogBench (4.6 times less).
Which is better for product listings, Muse Spark 1.3 or GPT-6.1 Terra?
GPT-6.1 Terra ranks 4 of 25 models on sale for turning a sparse product feed and photos into listings that can go live, against 13 for Muse Spark 1.3.
Which is better for decks from an analysis, Muse Spark 1.3 or GPT-6.1 Terra?
GPT-6.1 Terra ranks 7 of 26 models on sale for turning a finished analysis into a deck you could present as it is, against 18 for Muse Spark 1.3.
Which is better for marketing planning, Muse Spark 1.3 or GPT-6.1 Terra?
GPT-6.1 Terra ranks 1 of 26 models on sale for planning a year of ad spend without overspending, against 18 for Muse Spark 1.3.
Which is better for speed under pressure, Muse Spark 1.3 or GPT-6.1 Terra?
GPT-6.1 Terra ranks 16 of 29 models on sale for good decisions against a real clock (fast chess), against 27 for Muse Spark 1.3.
Which has the bigger context window, Muse Spark 1.3 or GPT-6.1 Terra?
GPT-6.1 Terra: 1,050,000 tokens, against 1,048,576 for Muse Spark 1.3.
Run Muse Spark 1.3 and GPT-6.1 Terra on your own prompt
Benchmarks aren't your data. Try both side by side in the playground, with the cost of every answer.