GPT-6.1 Terra · Data analysis
GPT-6.1 Terra for data analysis: our test runs
GPT-6.1 Terra ran our 5 data analysis prompts in llmwise, through the same pipeline your messages take. Here's every reply as it came, whether it passed, what it cost and what it counts as on Pro, next to the other models.
Based on 5 of our test runs on , through OpenRouter with the app's own prompt and settings. Updated .
Short answer
In our test runs on October 27, 2026, GPT-6.1 Terra passed 5 of 5 of our data analysis prompts (both hard ones): tied 1st of 21 models. Each reply counted as 1 message on Pro, where it has 250 a month, and cost $0.0008 to run on average.
Prompt by prompt
Each of the 5 data analysis prompts, and how GPT-6.1 Terra's reply did.
| Prompt | Result | Cost | Time |
|---|---|---|---|
| The region with the most revenueEveryday | Passed: Final answer North, 1,085: right. | $0.0007 | 2.4 s |
| Average order value in AugustEveryday | Passed: Final answer 300.00: right. | $0.0006 | 2.2 s |
| Revenue change from July to AugustEveryday | Passed: Final answer 67.4% increase: right. | $0.0008 | 2.3 s |
| A median, filtered two waysHard | Passed: Final answer 6.25 hours: right. | $0.0006 | 2.5 s |
| Correlation between ad spend and sign-upsHard | Passed: Final answer 0.97: right. | $0.0014 | 3.3 s |
Every data analysis reply from GPT-6.1 Terra
The region with the most revenue
An everyday prompt: “The region with the most revenue”, in full.
Passed: Final answer North, 1,085: right.
- West: 90 + 310 + 240 + 225 = 865 - East: 120 + 135 + 310 + 360 = 925 - North: 180 + 240 + 620 + 45 = 1,085 Final answer: North, 1,085
814 tokens in, 108 out (37 of them reasoning) · 2.4 s · $0.0007 · 1 message on Pro · answered by openai/gpt-6.1-terra via OpenAI ·
Average order value in August
An everyday prompt: “Average order value in August”, in full.
Passed: Final answer 300.00: right.
August revenue: 240 + 310 + 620 + 225 + 360 + 45 = 1,800 Average per order: 1,800 ÷ 6 = 300.00 Final answer: 300.00
821 tokens in, 81 out (24 of them reasoning) · 2.2 s · $0.0006 · 1 message on Pro · answered by openai/gpt-6.1-terra via OpenAI ·
Revenue change from July to August
An everyday prompt: “Revenue change from July to August”, in full.
Passed: Final answer 67.4% increase: right.
- July revenue: $90 + $120 + $310 + $180 + $135 + $240 = **$1,075** - August revenue: $240 + $310 + $620 + $225 + $360 + $45 = **$1,800** - Percentage change: ($1,800 − $1,075) ÷ $1,075 × 100 = **67.4%** Final answer: 67.4% increase
826 tokens in, 159 out (58 of them reasoning) · 2.3 s · $0.0008 · 1 message on Pro · answered by openai/gpt-6.1-terra via OpenAI ·
A median, filtered two ways
A hard prompt: “A median, filtered two ways”, in full.
Passed: Final answer 6.25 hours: right.
The six qualifying times, sorted, are 2, 4, 5.5, 7, 9, and 26 hours. Median = (5.5 + 7) ÷ 2 = 6.25 hours. Final answer: 6.25 hours
686 tokens in, 90 out (25 of them reasoning) · 2.5 s · $0.0006 · 1 message on Pro · answered by openai/gpt-6.1-terra via OpenAI ·
Correlation between ad spend and sign-ups
A hard prompt: “Correlation between ad spend and sign-ups”, in full.
Passed: Final answer 0.97: right.
The means are 768.75 for ad spend and 54.25 for sign-ups. Using Pearson’s formula: \[ r=\frac{23{,}912.5}{\sqrt{624{,}687.5 \times 971.5}}\approx 0.97 \] Final answer: 0.97625 tokens in, 432 out (356 of them reasoning) · 3.3 s · $0.0014 · 1 message on Pro · answered by openai/gpt-6.1-terra via OpenAI ·
How it compares on data analysis
GPT-6.1 Terra beside the job's picks among every model. 17 models share the hard-problems pick, GPT-6.1 Terra among them.
| Model | Passed | On Pro | Cost per reply |
|---|---|---|---|
| GPT-6.1 TerraOur pick: hard problems (shared), best value | 5 of 5 | 250 a month on Pro | $0.0008 |
| GPT-6 LunaOur pick: hard problems (shared), everyday | 5 of 5 | 60 a day on Pro | $0.0002 |
Every limit is published. Paid plans also have a monthly fair-use limit on AI cost: Plus $3.75, Pro $7.50, Max $20, Ultra $42, Studio $85. Using every message on your plan at typical sizes stays under it; very large messages and heavy research use it faster. Every limit, explained.
GPT-6.1 Terra next to each model on data analysis
GPT-6.1 Terra against each model on the same 5 data analysis prompts. One run each, through OpenRouter: a wait depends on the provider and the load that day, so a lead under 10% counts as close.
Against Claude Fable 5.1: GPT-6.1 Terra answered 2.0× sooner (2.4 s to 4.9 s), cost 34.8× less, and passed 5 of 5 to its 5.
Against Claude Opus 5.5: GPT-6.1 Terra answered 1.9× sooner (2.4 s to 4.6 s), cost 16.1× less, and passed 5 of 5 to its 5.
Against Claude Sonnet 5.5: GPT-6.1 Terra answered within 10% of its time (2.4 s to 2.3 s), cost 5.8× less, and passed 5 of 5 to its 5.
Against Claude Sonnet 5: GPT-6.1 Terra answered 2.2× sooner (2.4 s to 5.3 s), cost 8.5× less, and passed 5 of 5 to its 4. Only GPT-6.1 Terra passed Correlation between ad spend and sign-ups.
Against Claude Haiku 5.5: GPT-6.1 Terra answered 1.3× sooner (2.4 s to 3.3 s), cost 2.3× more, and passed 5 of 5 to its 5.
Against Claude Haiku 4.5: GPT-6.1 Terra answered 1.1× sooner (2.4 s to 2.7 s), cost 3.1× less, and passed 5 of 5 to its 3. Only GPT-6.1 Terra passed Average order value in August; Correlation between ad spend and sign-ups.
Against GPT-6 Astra: GPT-6.1 Terra answered 1.3× sooner (2.4 s to 3.3 s), cost 19.0× less, and passed 5 of 5 to its 5.
Against GPT-6.1 Sol: GPT-6.1 Terra answered 1.2× sooner (2.4 s to 3.0 s), cost 2.0× less, and passed 5 of 5 to its 5.
Against GPT-6 Sol: GPT-6.1 Terra answered 1.1× sooner (2.4 s to 2.8 s), cost 4.2× less, and passed 5 of 5 to its 5.
Against GPT-6 Luna: GPT-6.1 Terra answered within 10% of its time (2.4 s to 2.5 s), cost 4.6× more, and passed 5 of 5 to its 5.
Against Gemini 4 Argon: GPT-6.1 Terra answered 2.8× sooner (2.4 s to 6.9 s), cost 3.5× less, and passed 5 of 5 to its 5.
Against Gemini 3.1 Pro (preview): GPT-6.1 Terra answered 3.5× sooner (2.4 s to 8.6 s), cost 19.0× less, and passed 5 of 5 to its 5.
Against Gemini 3.8 Flash: GPT-6.1 Terra answered 2.2× sooner (2.4 s to 5.4 s), cost 3.4× less, and passed 5 of 5 to its 4. Only GPT-6.1 Terra passed Correlation between ad spend and sign-ups.
Against DeepSeek V4.1 Flash: GPT-6.1 Terra answered 2.8× later (2.4 s to 0.9 s), cost within 10% of it, and passed 5 of 5 to its 5.
Against DeepSeek V4 Pro: GPT-6.1 Terra answered 1.7× sooner (2.4 s to 4.1 s), cost 3.5× less, and passed 5 of 5 to its 5.
Against Grok 4.7: GPT-6.1 Terra answered 3.7× sooner (2.4 s to 8.9 s), cost 13.7× less, and passed 5 of 5 to its 5.
Against Kimi K3: GPT-6.1 Terra answered 1.4× sooner (2.4 s to 3.5 s), cost 8.4× less, and passed 5 of 5 to its 5.
Against GLM 5.3: GPT-6.1 Terra answered 1.3× later (2.4 s to 1.9 s), cost 2.4× less, and passed 5 of 5 to its 5.
Against GLM 5.3 Flash: GPT-6.1 Terra answered 4.0× sooner (2.4 s to 9.8 s), cost 2.1× more, and passed 5 of 5 to its 4. Only GPT-6.1 Terra passed Correlation between ad spend and sign-ups.
Against Mistral Large 4: GPT-6.1 Terra answered 6.5× sooner (2.4 s to 15.8 s), cost 4.6× less, and passed 5 of 5 to its 5.
How these runs were done
Final answer. Automatic. The reply's last “Final answer:” line must hold the right value.
GPT-6.1 Terra, and data analysis, elsewhere
- GPT-6.1 Terra: price, limits and messages on every plan
- GPT-6 for data analysis
- GPT-6.1 Terra for coding: our test runs
- GPT-6.1 Terra for writing: our test runs
- GPT-6.1 Terra for math: our test runs
- GPT-6.1 Sol vs GPT-6.1 Terra
- GPT-6.1 Terra vs GPT-6 Luna
- GPT-6.1 Terra vs Claude Haiku 4.5
- GPT-6.1 Terra vs Gemini 3.8 Flash
- GPT-6.1 Terra vs GLM 5.3
- GPT-6.1 Terra vs Grok 4.7
- Analyze a CSV with code: the prompt, and its price
- AI prompts for business, tested on four models
- Our test runs: 50 prompts on every model
Questions
Is GPT-6.1 Terra good for data analysis?
In our test runs it passed 5 of 5 data analysis prompts, tied 1st of the 21 models in llmwise. Every reply is on this page, so you can judge them yourself.
How many of my messages does a data analysis reply from GPT-6.1 Terra use?
1 message each on Pro, where it has 250 a month on Pro. The price of a message is fixed and shown before you send it, however long the reply.
How were these runs done?
The same way for every model: each prompt sent through llmwise's own pipeline, each reply checked the same way. The methods page has every prompt and how each is scored.
Claude, GPT, Gemini, DeepSeek, Grok, Kimi, GLM, and Mistral, in one chat.
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