GPT-6 LunavsGPT-6 Sol
GPT-6 Luna | GPT-6 Sol | |
|---|---|---|
| Specifications | ||
Context windowHow much text the model can hold in mind at once — your question, any documents you attach, the conversation so far, and its own reply. Go past it and the earliest part falls out of view. | 1.05M | 1.05M |
| API pricingUSD per 1M tokens · lower wins · base tier | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | $0.10 | $2.00 |
Output priceWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one. | $0.50 | $10.00 |
Cached input priceA reduced rate for text you send over and over. If every request starts with the same instructions or the same document, the provider keeps a copy ready and charges less to read it again. | $0.01 | $0.20 |
| Benchmarks | ||
DeepSWE 1.1Agentic coding — Artificial Analysis' independent test of deep, agentic software-engineering work — the AI has to plan and carry out substantial coding tasks end to end. (Version 1.1 of the test.) Higher is better. | 66.6% | 68.8% |
| BenchmarksPublished by one model only | ||
OSWorld 2.0Agentic computer use — Can the AI actually operate a computer — clicking, typing, and using real apps — to finish tasks on its own? Version 2.0 is a harder, refreshed task set. Higher is better. | — | 60.5% |
Agent's Last Exam · pass@1Agentic computer use — A hard set of desktop and operating-system tasks an AI agent has to finish by looking at the screen and working the machine itself. The score is the share it passes outright — partial credit does not count. Higher is better. | — | 56.4% |
AutomationBenchBusiness workflows — Tests whether the AI can run real multi-step business workflows — the kind of end-to-end office processes companies want to automate — from start to finish. Higher is better. | — | 33.2% |
| Overview | ||
| Company | OpenAI | OpenAI |
| Release date | Sep 22 2026 | Sep 22 2026 |
| Access | Proprietary | Proprietary |
Other comparisons
GPT-6 LunavsClaude Opus 5.5GPT-6 SolvsClaude Opus 5.5GPT-6 LunavsGemini 3.8 FlashGPT-6 SolvsGemini 3.8 FlashGPT-6 LunavsMuse Spark 1.3GPT-6 SolvsMuse Spark 1.3GPT-6 LunavsGrok 4.7GPT-6 SolvsGrok 4.7GPT-6 LunavsDeepSeek-V4.1-FlashGPT-6 SolvsDeepSeek-V4.1-FlashGPT-6 LunavsMistral Medium 3.5GPT-6 SolvsMistral Medium 3.5
Frequently asked questions
GPT-6 Sol leads GPT-6 Luna on 1 of the 1 benchmark they both report (DeepSWE 1.1). GPT-6 Luna is cheaper on both input and output: $0.10 vs $2.00 per million input tokens, and $0.50 vs $10.00 per million output tokens. Figures are base-tier rates. Both models were released on the same day — Sep 22 2026.
Context windows are 1.05M (GPT-6 Luna) vs 1.05M (GPT-6 Sol).
On DeepSWE 1.1, GPT-6 Sol leads at 68.8% vs GPT-6 Luna at 66.6%.