OpenAI releases GPT-6.1 Sol, pitched as near-Astra quality at a fifth of the price

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OpenAI releases GPT-6.1 Sol, pitched as near-Astra quality at a fifth of the price

OpenAI’s own post has the full price table and the benchmark-by-benchmark comparison with Astra, so you can judge "near-Astra" yourself.

OpenAI released GPT-6.1 Sol, an upgrade to GPT-6 Sol that it says nearly matches its flagship GPT-6 Astra on agentic coding, computer use and professional work. Pricing is $2 per million input tokens and $10 per million output tokens (Astra: $10 and $50), with cached input at $0.10 per million.

Read it at the source

OpenAIIntroducing GPT-6.1 Sol ↗ Hacker NewsDiscussion: GPT 6.1 Sol ↗

Cascadic Analysis 3

UndertowLoss of meaningful human control as capability and autonomy increase

What hidden risk could pull against this, even if the news is good?

At a fifth of the price for near-flagship agentic coding and computer use, teams can afford far more agent runtime per human reviewer. The cost of autonomy is falling faster than the cost of oversight, so supervision tends to thin out just as capability rises.

UndertowBenchmark scores can overstate real-world reliability

What hidden risk could pull against this, even if the news is good?

“Nearly matches Astra” is measured on evaluations OpenAI chose and ran. Benchmarks reward what they test; your codebase, data and edge cases aren’t in them, so check results on your own work before trusting the headline.

UndertowDelayed Consequence / False Success Problem

What hidden risk could pull against this, even if the news is good?

Cheaper agents get deployed widely before long-run results are in. Code and workflows that pass today’s checks can carry quiet errors that surface months later, after trust and usage have already grown.

OpenAI releases GPT-6.1 Sol, pitched as near-Astra quality at a fifth of the price

Further down the stream