Compare / GPT-6.1 Terra vs GPT-6 Luna
GPT-6.1 Terra vs GPT-6 Luna
Which is cheaper, which is more capable, and which does better at each kind of work, from 67 results on 4 sources that measured both models.
OpenAIGPT-6.1 Terra
OpenAIGPT-6 Luna
GPT-6.1 Terra wins 3020 too close to callGPT-6 Luna wins 17
Of the 67 results both models have, the better value on each. Results whose reported ranges overlap are too close to call.
Results as of 5 November 2026 (catalogue release 2026-11-05-44c5fb63d296).
GPT-6.1 Terra or GPT-6 Luna? The short answer
Pick GPT-6.1 Terra if quality matters most: it scores higher (Spring Prompt overall 83 against 39). Pick GPT-6 Luna if cost matters more: it costs 7.5 times less per product listing on CatalogBench.
- Spring Prompt overall: GPT-6.1 Terra 83, GPT-6 Luna 39 (out of 100; how the score works).
- GPT-6 Luna is cheaper to run: $0.000 against $0.004 per product listing on CatalogBench (7.5 times less).
- GPT-6.1 Terra is newer: released 26 Oct 2026, against 22 Sep 2026 for GPT-6 Luna.
- On our own benchmarks, on the results both models have: GPT-6.1 Terra does better for product listings and marketing planning.
Head to head
83
Spring Prompt overall
39
$2.00
Price per million tokens, blendedlower is better
$0.20
1,050,000
Context window, tokens
1,050,000
Every fact side by side
| GPT-6.1 Terra | GPT-6 Luna | |
|---|---|---|
| Price per million tokens | $1.00 in · $5.00 out | $0.10 in · $0.50 out |
| Blended (3 in : 1 out) | $2.00 | $0.20 |
| Cheapest host, blended | $2.00 (Azure) | $0.20 (Amazon Bedrock) |
| Cost per product listing (CatalogBench) | $0.004 | $0.000 |
| Cached input, per million | $0.050 cached input | $0.010 cached input |
| Intelligence Index | – | 38.1 |
| Spring Prompt overall | 83 | 39 |
| Output speed, tokens a second | – | 127 |
| Context window | 1,050,000 tokens | 1,050,000 tokens |
| Released | 26 Oct 2026 (newer) | 22 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
4 of 27
6 of 27
Decks from an analysisTurning a finished analysis into a deck you could present as it is
6 of 28
9 of 28
User surveysPlanning a user survey and reading its results without being misled
5 of 17
not measured
Marketing planningPlanning a year of ad spend without overspending
1 of 28
5 of 28
Agents and tool useMulti-step tasks with tools: support desks, coding agents, function calls
not measured
50 of 160
Professional workReal tasks from banking, consulting and law, business documents and freelance projects
not measured
25 of 51
Reasoning and knowledgeHard questions across science, maths and general knowledge
not measured
46 of 188
WritingWhat people prefer in blind comparisons, and judged writing quality
not measured
61 of 173
Sticking to the factsSummarising without inventing things, and factual answers
not measured
89 of 143
Speed under pressureGood decisions against a real clock (fast chess)
16 of 31
21 of 31
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
- GPT-6.1 Terra review: close to the top of our business tests at half the price of Sol 5 Nov 2026
- Kimi K3.1 Pro first look: the best open-weight model on our board, and very slow 5 Nov 2026
- Best AI for Product Descriptions: Accuracy, Cost and Real Examples 20 Oct 2026
- Mercury 3 first look: very fast with thinking off, too slow with it on 20 Oct 2026
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 | GPT-6.1 Terra | GPT-6 Luna |
|---|---|---|
| BulletBench measured by Spring Prompt · 3 results | ||
| Cost per game · Blitz 3+2US dollars, lower is better 7 · 1 of 16 measured | $0.0706 | $0.0072 |
| Cost per game · Bullet 60sUS dollars, lower is better 26 · 6 of 36 measured | $0.0172low reasoning | $0.0016no reasoning |
| Ladder Elo · Bullet 60sladder Elo, higher is better 23 · 27 of 36 measured | 358low reasoning | 249no reasoning |
| CatalogBench measured by Spring Prompt · 3 results | ||
| Cost per productUS dollars, lower is better 8 · 2 of 28 measured | $0.0036 | $0.0005 |
| Reliably publish-ready% of products, higher is better 5 · 8 of 27 measured | 64.3% | 55.4% |
| Reliably publish-ready · sales brief% of products, higher is better 2 · 5 of 27 measured | 67.9% | 51.8% |
| DeckBench measured by Spring Prompt · 3 results | ||
| Cost per deckUS dollars, lower is better 15 · 3 of 28 measured | $0.0672 | $0.0087 |
| 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. 6 · 9 of 28 measured | 1,344 | 1,296 |
| Accurate decks% of tasks, higher is better 1 · 12 of 28 measured | 100.0% | 50.0% |
| ROASBench measured by Spring Prompt · 3 results | ||
| Overall scorescore out of 100, higher is better 1 · 5 of 28 measured | 58.4 | 53.4 |
| Audience scorescore out of 100, higher is better 1 · 4 of 28 measured | 69.4 | 68.3 |
| Business scorescore out of 100, higher is better 1 · 5 of 28 measured | 59.1 | 54.8 |
Show all 67 results (55 more)
| Measure | GPT-6.1 Terra | GPT-6 Luna |
|---|---|---|
| BulletBench measured by Spring Prompt · 7 results | ||
| Games lost on time · Blitz 3+2% of games, lower is better 8 · 13 of 16 measured | 25.0% | 50.0% |
| Games lost on time · Bullet 60s% of games, lower is better 28 · 21 of 36 measured | 75.0%low reasoning | 50.0%no reasoning |
| Invalid moves · Blitz 3+2% of moves, lower is better 1 · 1 of 16 measured | 0.0% | 0.0% |
| Invalid moves · Bullet 60s% of moves, lower is better 1 · 1 of 36 measured | 0.0%low reasoning | 0.0%no reasoning |
| Ladder Elo · Blitz 3+2ladder Elo, higher is better 6 · 8 of 16 measured | 683 | 557 |
| Median move time · Blitz 3+2milliseconds, lower is better 7 · 13 of 16 measured | 3.7 s | 7.0 s |
| Median move time · Bullet 60smilliseconds, lower is better 30 · 21 of 36 measured | 2.8 slow reasoning | 1.5 sno reasoning |
| CatalogBench measured by Spring Prompt · 28 results | ||
| Channel compliance% of products, higher is better 27 · 1 of 28 measured | 98.2% | 100.0% |
| Channel rules broken% of products, lower is better 25 · 1 of 28 measured | 1.8% | 0.0% |
| Channel rules broken · sales brief% of products, lower is better 1 · 1 of 28 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 28 measured | 100.0% | 100.0% |
| Content quality% of checks, higher is better 9 · 14 of 28 measured | 97.7% | 97.0% |
| Content quality · sales brief% of checks, higher is better 5 · 11 of 28 measured | 98.3% | 97.4% |
| Decision accuracy% of decisions, higher is better 5 · 11 of 28 measured | 98.1% | 97.0% |
| Failed outputs% of products, lower is better 1 · 1 of 28 measured | 0.0% | 0.0% |
| Failed outputs · sales brief% of products, lower is better 1 · 1 of 28 measured | 0.0% | 0.0% |
| Field accuracy% of missing fields, higher is better 6 · 13 of 28 measured | 94.4% | 93.7% |
| Invented values% of filled values, lower is better 12 · 14 of 28 measured | 1.5% | 1.7% |
| Missing UK information% of products, lower is better 1 · 1 of 28 measured | 0.0% | 0.0% |
| Missing UK information · sales brief% of products, lower is better 1 · 1 of 28 measured | 0.0% | 0.0% |
| Not findable% of products, lower is better 25 · 24 of 28 measured | 10.7% | 10.1% |
| Not findable · sales brief% of products, lower is better 27 · 24 of 28 measured | 13.7% | 10.1% |
| Publish-ready listings% of products, higher is better 6 · 10 of 28 measured | 74.4% | 67.9% |
| Publish-ready listings · sales brief% of products, higher is better 3 · 6 of 28 measured | 74.4% | 67.9% |
| Time per productseconds, lower is better 9 · 6 of 28 measured | 10.1 | 8.20 |
| Unsupported claims% of products, lower is better 3 · 8 of 28 measured | 0.6% | 8.9% |
| Unsupported claimsclaims per product, lower is better 4 · 7 of 28 measured | 0.03 | 0.31 |
| Unsupported claims · sales briefclaims per product, lower is better 3 · 6 of 28 measured | 0.09 | 0.35 |
| Unsupported claims · sales brief% of products, lower is better 1 · 6 of 28 measured | 1.8% | 8.3% |
| Wrong attributes% of products, lower is better 5 · 17 of 28 measured | 14.9% | 18.5% |
| Wrong attributes · sales brief% of products, lower is better 7 · 16 of 28 measured | 14.9% | 19.1% |
| Wrong category or variant% of products, lower is better 5 · 5 of 28 measured | 1.8% | 1.8% |
| Wrong category or variant · sales brief% of products, lower is better 5 · 1 of 28 measured | 1.8% | 0.0% |
| DeckBench measured by Spring Prompt · 14 results | ||
| Caveat dropped% of tasks, lower is better 1 · 1 of 28 measured | 0.0% | 0.0% |
| Clean layout% of tasks, higher is better 3 · 7 of 28 measured | 83.3% | 66.7% |
| Design quality% of the maximum, higher is better 5 · 7 of 28 measured | 80.8% | 78.1% |
| Draft figure quoted% of tasks, lower is better 1 · 15 of 28 measured | 0.0% | 33.3% |
| Findings missing% of tasks, lower is better 1 · 1 of 28 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. 17 · 8 of 28 measured | 48.3% | 72.5% |
| Layout defects% of tasks, lower is better 3 · 7 of 28 measured | 16.7% | 33.3% |
| Misleading metric used% of tasks, lower is better 1 · 1 of 28 measured | 0.0% | 0.0% |
| Presentable decks% of tasks, higher is better 2 · 13 of 28 measured | 50.0% | 0.0% |
| Recommendation late or wrong% of tasks, lower is better 1 · 12 of 28 measured | 0.0% | 16.7% |
| Slides needing work% of tasks, lower is better 8 · 3 of 28 measured | 33.3% | 16.7% |
| Time per deckseconds, lower is better 16 · 14 of 28 measured | 135 | 101 |
| Unsupported claims% of tasks, lower is better 1 · 1 of 28 measured | 0.0% | 0.0% |
| Unsupported numbers% of tasks, lower is better 1 · 1 of 28 measured | 0.0% | 0.0% |
| ROASBench measured by Spring Prompt · 6 results | ||
| Consistency scorescore out of 100, higher is better 1 · 6 of 28 measured | 48.8 | 35.8 |
| Contribution profitsimulated US dollars, higher is better 6 · 5 of 28 measured | $701,059 | $738,879 |
| Cost of a runUS dollars, lower is better 10 · 2 of 28 measured | $0.11 | $0.0142 |
| Months over budgetmonths of 12, lower is better 1 · 1 of 28 measured | 0 | 0 |
| Planning scorescore out of 100, higher is better 7 · 15 of 28 measured | 55.0 | 54.8 |
| Return on ad spendprofit per $1 spent, higher is better 2 · 6 of 28 measured | $0.71 | $0.66 |
Compare them with other models
- GPT-6.1 Terra vs Claude Opus 5.5Highest-scoring overall available today
- GPT-6.1 Terra vs GPT-6.1 SolJust below overall
- GPT-6 Luna vs Claude Haiku 5.5Most intelligent at under $0.25 per million tokens
- GPT-6 Luna vs DeepSeek-V4.1-FlashFastest with similar intelligence
- GPT-6 Luna vs Claude Opus 5.5Most intelligent available today
Quick answers
Is GPT-6.1 Terra better than GPT-6 Luna?
Pick GPT-6.1 Terra if quality matters most: it scores higher (Spring Prompt overall 83 against 39). Pick GPT-6 Luna if cost matters more: it costs 7.5 times less per product listing on CatalogBench.
Which is cheaper, GPT-6.1 Terra or GPT-6 Luna?
GPT-6 Luna is cheaper to run: $0.000 against $0.004 per product listing on CatalogBench (7.5 times less).
Which is better for product listings, GPT-6.1 Terra or GPT-6 Luna?
GPT-6.1 Terra ranks 4 of 27 models on sale for turning a sparse product feed and photos into listings that can go live, against 6 for GPT-6 Luna.
Which is better for decks from an analysis, GPT-6.1 Terra or GPT-6 Luna?
GPT-6.1 Terra ranks 6 of 28 models on sale for turning a finished analysis into a deck you could present as it is, against 9 for GPT-6 Luna.
Which is better for marketing planning, GPT-6.1 Terra or GPT-6 Luna?
GPT-6.1 Terra ranks 1 of 28 models on sale for planning a year of ad spend without overspending, against 5 for GPT-6 Luna.
Which is better for speed under pressure, GPT-6.1 Terra or GPT-6 Luna?
GPT-6.1 Terra ranks 16 of 31 models on sale for good decisions against a real clock (fast chess), against 21 for GPT-6 Luna.
Run GPT-6.1 Terra and GPT-6 Luna on your own prompt
Benchmarks aren't your data. Try both side by side in the playground, with the cost of every answer.