GPT-6 vs GPT-5.6 Sol: Half the Price, the Same Score

GPT-6 Sol costs half what GPT-5.6 Sol costs, and the two land within a point of each other on the independent intelligence index. That is the whole comparison in one sentence, and it is the reason this page is short on suspense: The vendor shipped Sol on 22 September 2026 at $2.00 per million input tokens and $10.00 per million output tokens, seven weeks after GPT-5.6 Sol arrived on 9 July 2026 at $4.00 and $20.00. Same 1,050,000-token context window. Same 128,000-token output ceiling. Same 272,000-token repricing threshold. The newer model is not a capability leap; it is a price event, and the second half of that story is what the vendor did with it on 7 October.

If you are choosing between the two today, the useful question is not which is smarter. It is which one you are already integrated against, and whether your evaluation baseline is worth keeping.

What actually changed on 7 October

Through September, GPT-6 was an API family with three members and no consumer surface of its own. GPT-6 Astra sits at the top at $10.00 / $50.00, GPT-6 Sol in the middle at $2.00 / $10.00, and GPT-6 Luna at the bottom at $0.10 / $0.50. On 7 October 2026 OpenAI rolled that generation into ChatGPT itself, under a capability it calls Intelligent UI, to the more than 1.2 billion people who use ChatGPT each week.

The detail that matters for a comparison against GPT-5.6 Sol is the routing rule OpenAI states on its own announcement. GPT-6 in ChatGPT is powered by GPT-6 Sol for Plus, Pro, Business and Enterprise tiers, and by GPT-6 Luna for Free and Go tiers. In other words, the model you are being asked to compare with GPT-5.6 Sol is the same GPT-6 Sol you can call over the API — the ChatGPT rollout is not a separate, better checkpoint. The rollout reached Plus, Pro, Business and Enterprise in the Chat tab on 7 October, with Free and Go following from 8 October, and enterprise availability gated by workplace admin settings. The models powering Work and Codex were explicitly left unchanged.

GPT-5.6 Sol, by contrast, never had a consumer surface of its own. It was born an API model on 9 July 2026 and remains one. So the two products are being compared across different distribution footprints — an API model that became the default answer engine for a billion-plus weekly users, and an API model that stayed an API model.

The two rate cards, side by side

Both are two-tier cards: a standard rate up to 272,000 input tokens, and a higher rate that reprices the whole request once you cross that line. OpenAI's model pages state the rule the same way for both — prompts above 272K input tokens are charged at 2x input and cache rates and 1.5x output for the full request, not just the portion over the threshold.

• Standard input: GPT-6 Sol $2.00 per million, GPT-5.6 Sol $4.00 per million
• Standard output: GPT-6 Sol $10.00 per million, GPT-5.6 Sol $20.00 per million
• Cached input (90% off): GPT-6 Sol $0.20 per million, GPT-5.6 Sol $0.40 per million
• Cache writes: GPT-6 Sol $2.50 per million, GPT-5.6 Sol $5.00 per million
• Above 272K input tokens: GPT-6 Sol reprices to $4.00 / $15.00, GPT-5.6 Sol to $8.00 / $30.00
• Context and output: both 1,050,000 tokens in, 128,000 tokens out
• Reasoning effort: both expose a configurable reasoning.effort, running from none to max
• Modalities: both accept text, image and file input and return text

The long-context tier is where the gap is largest in absolute terms: crossing 272,000 tokens costs $8.00 / $30.00 on GPT-5.6 Sol and $4.00 / $15.00 on GPT-6 Sol. If you run long agent transcripts, the whole-request rule means a 300,000-token call is priced at the higher tier from the first token, and the difference between the two models on that call is roughly half of a very large number.

One caveat on the GPT-5.6 Sol column: OpenAI's current pricing page no longer carries a GPT-5.6 Sol row in its flagship table, because GPT-6.1 Sol now holds that slot. The figures above are read off the GPT-5.6 Sol model page, which still documents them, and its $4.00 / $20.00 headline is a promotional rate that OpenAI says runs at least through 21 November 2026. OpenAI told press that the GPT-6 rates are permanent rather than promotional, which is a spokesperson statement rather than a written commitment — treat the GPT-6 price as stable and the GPT-5.6 Sol price as dated.

The independent numbers

The vendor-versus-vendor framing would have you compare OpenAI's own launch charts. Those are vendor-reported and the two models were never published against each other by their maker in a form worth quoting. The cleaner read is the one independent evaluator both models carry.

Artificial Analysis scores GPT-6 Sol at 47.6 on its Intelligence Index, with GPT-5.6 Sol at 47.0. That is inside the noise of a single index revision — not a win for either model. On the individual benchmarks carried alongside them, the ordering is mixed rather than decisive. Against GPT-6 Sol's published figures, GPT-5.6 Sol posts a higher GPQA Diamond (94.1 versus the GPT-6 Sol figure) and a comparable SciCode, while GPT-6 Sol leads on Humanity's Last Exam and long-context recall.

Two honesty notes about those numbers. First, the index values in OrcaRouter's catalogue for each model were evaluated on different dates, so a same-week head-to-head is not what you are looking at; a couple of tenths of a point between two revisions is not evidence of anything. Second, GPT-5.6 Sol has been on the board longer and has had more runs; a newer model's first index score tends to move as more evaluations land, usually slightly upward. If the difference between these two models is the deciding factor for your workload, the honest instruction is to benchmark on your own traffic rather than on either model's index position.

Where GPT-5.6 Sol is still the right answer

There are three honest reasons to keep calling GPT-5.6 Sol rather than switching. The first is a frozen evaluation baseline: if your regression suite or your cost model was calibrated against GPT-5.6 Sol's exact outputs and token profile, a model swap invalidates the baseline, and the engineering time to re-establish it can outweigh the per-token saving for a while. The second is a pinned snapshot in a deployed system where nothing has broken. The third is that the price cut does not apply to you if your prompts sit under 272K tokens and your volume is small enough that the absolute saving is trivial — a $2 versus $4 input rate is a rounding error at a few million tokens a month.

What is not a reason is capability. There is no benchmark in the public record on which GPT-5.6 Sol's case for itself depends on staying ahead of GPT-6 Sol, and the price is against it in every tier including long context.

Routing between them

The practical problem with a two-generation comparison is that you usually want both for a while. That is the case OrcaRouter is built for: one API with the provider's list price passed through at 0% markup, so a vendor price change lands the same day rather than at your next billing reconciliation, and automatic failover across providers if one route degrades. Both openai/gpt-5.6-sol on OrcaRouter and GPT-6 Sol are live routes in the same catalogue, called through the OpenAI-compatible chat completions and Responses endpoints, which means moving traffic from one to the other is a model-id change and not a rewrite. The routing DSL lets you split by request size, so a short prompt can go to the cheap tier and anything over your own threshold can be pinned to the model you trust at length.

The one-line verdict

GPT-6 Sol is the model to start with. It is half the price of GPT-5.6 Sol at every tier, it now sits behind the ChatGPT surface that reaches 1.2 billion weekly users, and the independent index puts it level rather than behind. GPT-5.6 Sol remains a valid answer only where a frozen baseline or an unchanged deployment is worth more than the price difference — and that is a statement about your engineering calendar, not about the models.