OpenAI just cut GPT-5.

OpenAI cut prices for GPT-5.6 Sol, its reasoning-heavy model, reducing input tokens to $2.40 per million (from $3.00) and output to $9.60 (from $12.00), a 20% reduction. The move comes as Anthropic's Claude 3.5 Sonnet gains traction for similar workloads, and the batch API discount can stack to effectively 50% off new rates, making Sol batch processing $1.20/$4.80 per million tokens. The price cut applies only to the Sol reasoning tier, leaving other models unchanged, and may be a defensive strategy to retain enterprise customers.

OpenAI just cut GPT-5. GPT-5.6 Sol has been the go-to for reasoning-heavy tasks since it launched — code generation with complex constraints, multi-step analysis, the kind of prompts where you need the model to actually think instead of pattern-match. The problem was always the per-token bill. At the old rates, a single sophisticated agent loop with tool calls and reflection cycles could easily run $0.40-$0.60. Run that a few thousand times a day and you're looking at serious money. The new pricing brings input tokens down to $2.40 per million from $3.00 and output to $9.60 from $12.00 . Credits follow the same ratio. That's not a rounding error — it's a 20% reduction on the most expensive part of the stack. What's interesting is the timing. This dropped right as Anthropic's Claude /en/tags/claude/ 3.5 Sonnet started gaining serious traction for the same workloads. Sonnet's pricing has been aggressive from day one, and their 200k context window made it a natural competitor for long-context reasoning tasks. OpenAI isn't dumb — they know developers were running side-by-side evals. This cut narrows the gap enough that switching costs become the deciding factor again. For teams already invested in the OpenAI ecosystem — function calling patterns, assistant API threads, the whole tooling chain — this removes the financial pressure to migrate. The switching cost of rewriting prompt architectures and revalidating evals across providers is real. A 20% savings on the incumbent model often beats a 30% savings on a new one when you factor in engineering time. The credit pricing adjustment is particularly relevant for enterprise accounts on committed spend. If you pre-purchased credits at the old rate, check your dashboard — some accounts are seeing retroactive adjustments applied to unused balances. Not universal yet, but worth opening a support ticket if you're sitting on a large credit pool. One thing the pricing page doesn't highlight: the batch API discount still stacks on top. If you can tolerate async processing and for eval pipelines, background analysis, nightly report generation — you usually can , you're looking at effectively 50% off the new rates. That puts GPT-5.6 Sol batch processing at $1.20/$4.80 per million tokens. For high-volume reasoning workloads, that's genuinely competitive with self-hosted 70B models once you factor in GPU costs and engineering overhead. The real question is whether this signals a broader pricing strategy shift or a targeted defensive move. GPT-5.6 non-Sol pricing is unchanged. Embedding models unchanged. This feels surgical — protecting the reasoning tier specifically. Which makes sense: that's where the highest-value, highest-margin enterprise workloads live, and it's where competition is fiercest. If you're building on Sol today, re-run your cost projections. If you evaluated it three months ago and walked away due to price, the math has shifted enough to warrant a second look. The model hasn't changed — but the economics just did. Next SalesMind AI's homepage promises don't match what independent → /en/news/7270/