GPT-6.1-Terra
A large language model in the GPT series released by OpenAI, positioned around low cost and high response speed; it is relatively strong in backend processing and automated operations, while its frontend design capability is comparatively weak.
Timeline (last 90 days)
GPT-6.1-Terra's cost consumption for completing the same task is 0.85, while Claude Opus 5.5's is 13.41 and GPT-6.2's is 7.
Under the Pro subscription quota, GPT-6.1-Terra's quota consumption for completing a full 3D parking lot webpage build task is only about 1%.
GPT-6.1-Terra's overall score ranks eighth among the evaluated models.
GPT-6.1-Terra's backend processing capability ranks third among the evaluated models.
GPT-6.1-Terra's front-end interaction ranks around 18th.
The uploader believes DeepSeek scores very high on front-end design-related tasks and is a more suitable choice than GPT-6.1-Terra.
GPT-6.1-Terra completed the 3D parking lot webpage development via Codex in a total of 10 minutes 52 seconds, including a few minutes of network connection troubleshooting, with pure development time under 10 minutes.
The finished 3D parking lot webpage generated by GPT-6.1-Terra supports freely switching viewpoints, zooming in to view details, and clicking a vehicle to switch to a nearby viewpoint.
The uploader commented that the 3D parking lot quickly produced by GPT-6.1-Terra meets expectations, but the result is not as good as DeepSeek's, and further adjustments in front-end design are needed to improve the result.
GPT-6.1-Terra is positioned as suitable for cost-sensitive backend processing and automated operation scenarios that require fast responses, rather than as an all-rounder.
All Facts (10)
GPT-6.1-Terra is positioned as suitable for cost-sensitive backend processing and automated operation scenarios that require fast responses, rather than as an all-rounder.
50%UnverifiedUnder the Pro subscription quota, GPT-6.1-Terra's quota consumption for completing a full 3D parking lot webpage build task is only about 1%.
50%UnverifiedGPT-6.1-Terra's overall score ranks eighth among the evaluated models.
50%UnverifiedGPT-6.1-Terra's backend processing capability ranks third among the evaluated models.
50%UnverifiedGPT-6.1-Terra's front-end interaction ranks around 18th.
50%UnverifiedThe uploader believes DeepSeek scores very high on front-end design-related tasks and is a more suitable choice than GPT-6.1-Terra.
50%UnverifiedGPT-6.1-Terra's cost consumption for completing the same task is 0.85, while Claude Opus 5.5's is 13.41 and GPT-6.2's is 7.
50%UnverifiedThe finished 3D parking lot webpage generated by GPT-6.1-Terra supports freely switching viewpoints, zooming in to view details, and clicking a vehicle to switch to a nearby viewpoint.
50%UnverifiedThe uploader commented that the 3D parking lot quickly produced by GPT-6.1-Terra meets expectations, but the result is not as good as DeepSeek's, and further adjustments in front-end design are needed to improve the result.
50%UnverifiedGPT-6.1-Terra completed the 3D parking lot webpage development via Codex in a total of 10 minutes 52 seconds, including a few minutes of network connection troubleshooting, with pure development time under 10 minutes.
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