VQV Signal

PRODUCT UPDATE WATCH PRACTICAL

OpenAI launches GPT-6.1 Terra, a fast computer-use model at half the price of GPT-6.1 Sol

According to a post on X by @OpenAI, the company has launched GPT-6.1 Terra, a fast model for computer use. Terra costs $1 per million input tokens and $5 per million output tokens, has a 1.05 million token context window, and is available in the API, ChatGPT Work and Codex for paid plans. OpenAI says it matches GPT-6 Astra on Agents' Last Exam at a tenth of the price per token and finishes tasks more than three times faster. The snippet notes that early reactions are split, with some describing it as a Sonnet-class model at half the price.

Source: Scobleizer News Pulse (X) · x.com Found via Robert Scoble’s Scobleizer News Pulse · a post on X, not independently verified Published 2026-10-26T19:20:00+00:00 Detected 2026-10-26T21:17:26+00:00
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According to a post on X by @OpenAI, the company has launched GPT-6.1 Terra, a fast model for computer use. Terra costs $1 per million input tokens and $5 per million output tokens, has a 1.05 million token context window, and is available in the API, ChatGPT Work and Codex for paid plans. OpenAI says it matches GPT-6 Astra on Agents' Last Exam at a tenth of the price per token and finishes tasks more than three times faster. The snippet notes that early reactions are split, with some describing it as a Sonnet-class model at half the price.

AI-assisted summary based on the listed source.

Terra costs $1 per million input tokens and $5 per million output, has a 1.05 million token context window, and is live in the API, ChatGPT Work and Codex for paid plans. OpenAI says it matches GPT-6 Astra on Agents' Last Exam at a tenth of the price per token and finishes tasks more than three times faster....

Developers and businesses building agents that operate computers now have another lower-cost model to evaluate. Teams on paid ChatGPT or Codex plans can try it directly, while API users can compare its price and speed with their current models. Watch for independent benchmark results, since the performance claims come from OpenAI and reactions in the snippet are mixed.

Developers may have a new tool, API, or workflow change worth testing against their own stack.

Signal Strength 95% Technical label WATCH Public Interest 67 Category PRODUCT UPDATE Reader Depth PRACTICAL

Signal Strength reflects source quality, relevance, freshness and evidence. Public Interest helps organize discovery; it is not proof of truth.

Public Interest components
Recognizable Entity Score 90 Practical Impact Score 56 Novelty Interest Score 94 Consequence Score 34 Curiosity Score 16 Shareability Score 75

VQV surfaced this signal because it is recent, relevant to AI Agents, connected to Scobleizer News Pulse (X).