OpenAI Releases GPT-6.1 Sol: Near-Astra Coding and Computer Use at One-Fifth of Astra's Token Price
By Michal Sutter | September 30, 2026
This week, OpenAI released GPT-6.1 Sol, an upgrade to GPT-6 Sol, the mid-tier model in the GPT-6 family. OpenAI's claim is specific: near-Astra results on agentic coding, computer use, and professional work — at one-fifth of GPT-6 Astra's standard input and output rates. Cached input drops to $0.10 per million tokens, 50% below GPT-6 Sol.
Is it deployable? Yes, as a hosted model. It is live today in the OpenAI API as gpt-6.1-sol, and in ChatGPT Work and Codex.
Where Sol Sits in the GPT-6 Lineup
OpenAI now ships three GPT-6 tiers. GPT-6 Astra costs $10 input, $50 output, and $1 cached input per million tokens. GPT-6.1 Sol costs $2, $10, and $0.10. GPT-6 Luna costs $0.10, $0.50, and $0.01.
The cached price matters most for agents. Agents resend the same system prompt, tool schemas, and history on every step. Cached reads now cost 5% of the uncached input rate, down from 10% on GPT-6 Sol.
Benchmark Results
All figures below are vendor-reported in OpenAI's launch post. OpenAI states that competitor numbers came from public reports.
- Coding: On DeepSWE v1.1, GPT-6.1 Sol matches GPT-6 Astra at roughly one-fifth of the cost. It beats GPT-6 Sol's best score by 6.4 percentage points, at a lower reasoning effort.
- Professional work: On GDP.pdf, which tests answers over complex professional PDFs, Sol beats Claude Opus 5.5 with fallbacks. It does so at less than half the cost per task. On AutomationBench 1.0.6, Sol scores 2.2 points above Opus 5.5 at medium effort. That result comes at roughly one-third the cost.
- Computer use: On the OSWorld 2.0 offline set, Sol ga...
via MarkTechPost