GPT-6.1 Terra
- ID
- 39799
- Status
- summarized
- Published
- 27 Oct 2026, 7:53 AM
- Fetched
- 29 Oct 2026, 8:28 AM
- Provider
- Simon Willison
- Category
- developer-ai
- Original URL
- https://simonwillison.net/2026/Oct/26/gpt-61-terra/
- Source URL
- https://simonwillison.net/atom/everything/
Summary
- Score
- 6.5
- Created
- 29 Oct 2026, 8:28 AM
- Tags
- Audience
- developersai_ml_learnersai_agent_userssaas_founders
What happened
Simon Willison flags OpenAI's GPT-6.1 Terra, a midrange model positioned like Anthropic's Sonnet, with emphasis in the announcement on visual reasoning and computer use. Pricing is $1 per million input tokens and $5 per million output — roughly half the price of GPT-5.6 Terra and GPT-6.1 Sol, and about 10x GPT-6 Luna. In a Hacker News comment, OpenAI's Ted Sanders is quoted saying Terra is probably better than Astra and Sol at technical communication, similar on vision and computer use but much faster, and a bit worse on most other things; Willison's max-reasoning pelican test cost 11.3161 cents and took 4 minutes 11 seconds.
Why it matters
If you route agent work through a frontier model, Terra changes the cost math for repetitive computer-use and vision tasks: at $1/$5 per million tokens you can run automated form-filling, drawing interpretation or video editing at roughly half what Sol or GPT-5.6 Terra cost, while accepting that it is weaker on non-vision, non-communication tasks. The concrete decision is tiering — keep hard reasoning on Sol/Astra and push high-volume, latency-sensitive agent loops to Terra, but note the 4m11s max-reasoning run before assuming 'faster' applies at every reasoning level.
Discussion angle
Walk through a real agent workload and decide the routing rule: which tasks go to Terra at $1/$5 versus Sol or Luna, and whether the quoted 'much faster' computer use holds at max reasoning where the pelican run took over four minutes.