Claude Opus 5.5 vs GPT-6 Sol: Half the Price, Until the Context Gets Long

Ant​hropic and Open​AI shipped competing flagships on the same afternoon. Claude Opus 5.5 went out on September 22, 2026 at $4 per million input and $20 per million output tokens, a 20% cut on both lines from Claude Opus 5. GPT-6 Sol went out the same day at $2 in and $10 out, a straight 50% cut from GPT-5.6 Sol, which Open​AI described as permanent rather than promotional. Read only those two sentences and the matchup looks settled before it starts: the Open​AI model is half price, and half price is half price. Read the rest of both rate cards and the gap mostly closes — not because either vendor changed anything, but because both models apply a surcharge to the same kind of request, and it costs Sol far more of its advantage than it costs Ant​hropic.

Two rate cards, both with a step in them

Below 272,000 input tokens, this is the simplest comparison in the current frontier:

• Input — GPT-6 Sol $2.00 per million vs Claude Opus 5.5 $4.00

• Output — GPT-6 Sol $10.00 per million vs Claude Opus 5.5 $20.00

• Cached input — GPT-6 Sol roughly 90% off the cached portion vs Claude Opus 5.5 $0.20 per million, a 5% multiplier on base input

• Context and output — GPT-6 Sol 872K as measured by Artificial Analysis, 1M claimed elsewhere, 128K max output vs Claude Opus 5.5 1M and 128K

• Knowledge cutoff — Claude Opus 5.5 June 2026 vs GPT-6 Sol not stated in the same terms

Above 272,000 input tokens, the arithmetic changes on both sides, and not by the same amount. GPT-6 Sol reprices the entire request — not the excess, the whole call — at roughly double the input rate and half again the output rate, landing near $4.00 in and $15.00 out. Claude Opus 5.5's rate card has no long-context step: Anthropic bills $4.00 and $20.00 across the full 1M-token window and states that a 900K-token request costs the same per token as a 9K-token one.

Put those together and the ordering flips in an unexpected place. On a long-context call, input rates converge at roughly $4 on both models — Sol's half-price advantage on input disappears entirely — while output narrows from a 2x gap to about $15 against $20, a 25% advantage rather than 50%. Sol is still cheaper. It is no longer cheap enough to be the only number in the decision, and the reason is that the two surcharges are different shapes: Anthropic's model charges a flat rate that happens to be higher, OpenAI's charges a penalty that lands hardest exactly on the agentic, repository-reading, document-set workloads both companies are selling these models for.

The independent score, which is the only same-conditions comparison

Neither launch table contains the other's new model — both were written before the same-day releases landed — so the vendor material cannot rank these two at all. Artificial Analysis can, because it runs every model in one published configuration:

• Intelligence Index — Claude Opus 5.5 58, ranked #1 of 210 vs GPT-6 Sol 48, ranked #18

• Configuration label — both scored at max effort; Claude Opus 5.5 additionally labelled "Default Fallback"

• Output speed — GPT-6 Sol 113.3 tokens/sec, ranked 38th vs Claude Opus 5.5 not yet published

• Time to first token — GPT-6 Sol 142.74s vs a board median of 3.83s; Claude Opus 5.5 not yet published

• Price — GPT-6 Sol $2.00 / $10.00 per million vs Claude Opus 5.5 $4.00 / $20.00

Ten index points and seventeen ranks is the widest separation in any current Claude-versus-OpenAI pairing, and it runs against the cheaper model for the second time this month — the same pattern showed up when GPT-6 Sol met Claude Opus 5 in an earlier comparison and lost by three points at 60% lower cost. The speed row cuts the other way and matters more than it looks: 113.3 tokens per second is roughly double what the GPT-6 Astra flagship manages, and it is the fastest figure in this group. Combined with a 142-second first token, the profile is a model that thinks for a long time and then writes quickly, which is a poor fit for anything interactive and a reasonable one for long unattended runs.

Both figures carry the same caveat the vendors' do: they are max-effort measurements, and neither model's shipping default is max effort. Claude Opus 5.5 defaults to medium on an effort scale running low to max; GPT-6 Sol exposes a scale running none to max. A max-effort index is a fair way to compare ceilings and a misleading way to predict your bill.

What breaks when you switch, in both directions

The migration friction here is asymmetric and worth knowing before either move.

Claude Opus 5.5 is not a drop-in for Claude Opus 5. Thinking can no longer be disabled, so code that set a non-thinking path will error or change behaviour silently. Forced tool use returns an error. Thinking blocks are bound to the model and conversation that produced them, so they cannot be replayed across models. The older computer_20251124 computer-use tool is not accepted on the Claude API or Google Cloud. Separately, text between tool calls now returns inside thinking blocks that are empty at the default display setting, so an application streaming that text as progress will simply go quiet between calls without throwing anything.

GPT-6 Sol's effort scale is the more flexible of the two: it can be changed mid-conversation without invalidating the prompt cache, which means a cheap first pass and an expensive retry on the same context is a supported pattern rather than a cache-busting one. That is a genuine engineering advantage for anyone running tiered reasoning inside a single session, and it is the strongest argument for Sol that does not appear in any price table.

Running both, and deciding with your own numbers

The honest position on this matchup is that the vendor tables cannot settle it and the independent index settles only the ceiling. What is left is the workload question — how long your contexts actually run, and how much a failed attempt costs — and that is measurable on your own traffic rather than arguable from a press release.

Both models are routable from OrcaRouter at provider list price with 0% markup: GPT-6 Sol at OpenAI's $2.00 / $10.00 and Claude Opus 5.5 at Anthropic's $4.00 / $20.00. Because the pass-through is exact and the prices move the day the vendors move them, the ratio you measure in staging is the ratio you pay in production, with no markup layer to re-derive. One key covers both, so the routing rule that sends sub-272K calls to Sol and long-context calls to whichever model wins on your evals is a configuration change rather than a second integration — and automatic failover means a same-day launch on either side is something you can put a slice of traffic on rather than a bet you make with a whole pipeline.

The version of this that survives contact with a bill

GPT-6 Sol is the cheaper model on every line, in every configuration, and that is not in dispute. What does not survive is the assumption that "half price" is the number to plan against: on a long-context call the input rates meet at roughly $4 and the output gap narrows to a quarter, which is a different decision from the one the launch pages describe. Weight that against a ten-point index gap, seventeen ranks, and a measured 142-second first token, and the split writes itself for most workloads — Sol as the high-volume default on short and medium contexts, Claude Opus 5.5 where the context runs long or the task is hard enough that a retry costs more than the token difference. The mistake worth avoiding is picking one of these on the headline rate alone, because it is the second number on each rate card that decides the case both models were built for.