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GPT-6.1 Terra vs Qwen3.8 Max (0902): Release Comparison

Comparison of the GPT-6.1 Terra and Qwen3.8 Max (0902) releases: 6 models and 1 model respectively, each with different intelligence, performance, and pricing characteristics. Below is a comparison of the key metrics across all 7 models.

  • For intelligence, GPT-6.1 Terra scores highest: GPT-6.1 Terra (Max) at 51, against Qwen3.8 Max (0902) at 34.
  • For time per task, GPT-6.1 Terra is fastest: GPT-6.1 Terra (Low) at 1.2 min, against Qwen3.8 Max (0902) at 48.2 min.
  • For cost per task, GPT-6.1 Terra is cheapest: GPT-6.1 Terra (Low) at $0.0713, against Qwen3.8 Max (0902) at $10.02.
Model Playground

Releases compared

GPT-6.1 Terra (max)GPT-6.1 Terra (xhigh)GPT-6.1 Terra (high)GPT-6.1 Terra (medium)Qwen3.8 Max (0902)GPT-6.1 Terra (non-reasoning)GPT-6.1 Terra (low)
Intelligence Index
51
45
42
38
34
31
29
Finance & Accounting
49
48
44
42
45
34
38
Strategy & Ops
50
49
47
45
47
40
42
Legal
46
44
42
40
41
28
37
Healthcare & Medical
45
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41
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Cost per TaskUSD
$0.96
$0.40
$0.26
$0.17
$10.02
$0.23
$0.0713
Time per TaskMinutes
14.1
6.4
4.3
2.8
48.2
2.4
1.2
Time to First Answer Tokens
173.08
34.45
12.60
4.96
111.02
1.96
2.78
Context Window
1M
1M
1M
1M
984k
1M
1M
Creator
OpenAI
OpenAI
OpenAI
OpenAI
Alibaba
OpenAI
OpenAI
License
Proprietary
Proprietary
Proprietary
Proprietary
Proprietary
Proprietary
Proprietary
Input Modality

Supports: text and image

Supports: text and image

Supports: text and image

Supports: text and image

Supports: text and image

Supports: text and image

Supports: text and image

Output Modality

Supports: text

Supports: text

Supports: text

Supports: text

Supports: text

Supports: text

Supports: text

Providers
OpenAI
OpenAI
OpenAI
OpenAI
Alibaba Cloud
OpenAI
OpenAI
Artificial Analysis Intelligence Index · Higher is better
Inference time (minutes) per Intelligence Index task · Lower is better
Weighted average cost (USD) per Intelligence Index task · Lower is better

Intelligence

Artificial Analysis Intelligence Index

Artificial Analysis Intelligence Index v5.0.1 incorporates 9 evaluations: AA-Briefcase v1.1, AutomationBench-AA, Terminal-Bench 4.0, FrontierCode-AA 2.0, AA-Omniscience v1.1, GDP.pdf, HLE-Diamond, CritPt v2 (Hard Subset), and Terminal-Bench-Science 0.1

Intelligence Index vs. Cost per Task

Artificial Analysis Intelligence Index · Weighted average cost (USD) per Artificial Analysis Intelligence Index task
Most attractive quadrant
GPT-6.1 Terra
Pareto line

Cost per Task (USD, Log Scale)

Cost

Cost per Intelligence Index Task

Weighted average cost (USD) per Intelligence Index task · Segmented by token type · Lower is better

Performance

Time per Intelligence Index Task

Output tokens divided by end-to-end output speed (minutes per Intelligence Index task) · Speed at the model's own endpoint or the median across providers · Lower is better

Capability Scores

Capability Indexes

Measures the performance of models on specific capabilities and industries
Finance & Accounting Index

Incorporates 5 evaluations: AA-Briefcase v1.1, AA-Omniscience v1.1, HLE-Diamond, AutomationBench-AA, GDP.pdf · Higher is better

Strategy & Ops Index

Incorporates 4 evaluations: AutomationBench-AA, AA-Briefcase v1.1, AA-Omniscience v1.1, GDP.pdf · Higher is better

Legal Index

Incorporates 5 evaluations: AA-Omniscience v1.1, AA-Briefcase v1.1, HLE-Diamond, GDP.pdf, AutomationBench-AA · Higher is better

Healthcare & Medical Index

Incorporates 5 evaluations: AA-Omniscience v1.1, AA-Briefcase v1.1, MLCR-AA, AutomationBench-AA, HLE-Diamond · Higher is better

Engineering Index

Incorporates 7 evaluations: AA-Omniscience v1.1, CritPt v2 (Hard Subset), Terminal-Bench-Science 0.1, HLE-Diamond, Terminal-Bench 4.0, FrontierCode-AA 2.0, AA-Briefcase v1.1 · Higher is better

Economics Index

Incorporates 4 evaluations: AA-Omniscience v1.1, AA-Briefcase v1.1, HLE-Diamond, GDP.pdf · Higher is better

AA-PersonalityBench

Personality Indexes

Each axis is one of 8 personality indexes: the mean of its traits’ Elo z-scores, percentile ranked from 1 to 100 across all models evaluated in the benchmark