GPT-6 Sol vs Claude Opus 5.5: Same-Day Launches, Different Price Tiers

GPT-6 Sol and Claude Opus 5.5 launched within about two hours of each other on September 22, 2026, which makes them an obvious candidate for a head-to-head comparison — but the pricing gap between them tells you immediately that OpenAI and Anthropic weren't actually building to compete on the same axis. Sol is priced at exactly half Opus 5.5's rate. This post pulls together what's directly comparable between them, and is explicit about where the comparison runs out of shared data.

TL;DR

The pricing gap explains most of the benchmark gap

Opus 5.5 is priced at double GPT-6 Sol's rate on both input and output tokens. That's not a coincidence relative to the benchmark results — on every shared metric, Opus 5.5 leads, and the size of the lead roughly tracks the size of the price gap. AutomationBench: Opus 5.5's 40.0% against Sol's 33.2% at Sol's own highest (xhigh) reasoning effort. Terminal-Bench 4.0: 66.4% against 43%, a wider gap in relative terms than the price difference alone would predict, though the two figures come from different sources — Anthropic's own reporting for Opus 5.5, Artificial Analysis' independent measurement for Sol, which is worth flagging as a methodology difference rather than treating both numbers as directly equivalent apples-to-apples.

Where OpenAI actually benchmarked Sol against

OpenAI's own GPT-6 Sol launch materials didn't compare it against Opus 5.5 at all — Opus 5.5 hadn't shipped yet when OpenAI assembled its comparison charts. Instead, OpenAI's own headline claim was that GPT-6 Sol at xhigh effort "outperforms Claude Opus 5 at max effort at just 9% of Opus 5's cost per task" on AutomationBench — a real result, but one measured against Opus 5, not Opus 5.5. That distinction matters directly: Opus 5.5 launched the same day at a 20% lower list price and a 60% lower cache-read price than Opus 5, which meaningfully narrows any cost-per-task gap calculated against the older, more expensive model. OpenAI's own 9%-of-cost claim, recalculated against Opus 5.5's actual same-day pricing rather than Opus 5's, would show Sol as considerably less of a bargain than the original framing suggests — though neither company has published the exact recalculated figure.

What Anthropic said about Sol-tier models generally

Anthropic's Opus 5.5 benchmark page compared against GPT-5.6 Sol, not GPT-6 Sol, for the same reason in reverse — GPT-6 Sol hadn't launched when Anthropic's page went live. On that comparison, Opus 5.5 led GPT-5.6 Sol by a wide margin across every reported benchmark (66.4% vs 37.3% on Terminal-Bench 4.0, for instance). Given GPT-6 Sol's own reported gains over GPT-5.6 Sol are real but incremental — roughly a 2-point improvement on Artificial Analysis' Coding Agent Index — the underlying gap between Opus 5.5 and the Sol tier generally, across both the 5.6 and 6 generations, appears to be a substantial and durable one on agentic coding tasks specifically, not something GPT-6 Sol's launch closed.

What each company's own recommended use cases suggest

Reading each company's own framing of who should use which model is more informative than it might seem, because both companies were unusually explicit about it this cycle. Anthropic frames Opus 5.5 as its daily-driver flagship, explicitly claiming it beats GPT-6 Astra — not GPT-6 Sol — at a fraction of Astra's cost on shared benchmarks, meaning Anthropic itself is implicitly positioning Opus 5.5 against OpenAI's top-tier model, not its mid-tier one. OpenAI's own framing of Sol is different in kind: "GPT‑6 Sol can take on difficult work tasks while giving you more room to iterate with higher usage limits and lower cost, offering more intelligence and better results versus similarly priced competitor models" — a comparison explicitly scoped to same-price-tier competitors, not to Anthropic's flagship. Put those two framings side by side and neither company is actually claiming to have built the head-to-head winner in this specific matchup; they're each making a different comparison against a different reference point, which is exactly why stitching together a fair GPT-6 Sol vs Opus 5.5 comparison requires pulling from outside either company's own marketing material.

The cache-pricing detail that changes real costs more than the headline numbers

One pricing detail easy to miss in a straight input/output comparison: Anthropic cut Opus 5.5's cache-read price by 60%, from $0.50 to $0.20 per million tokens, a considerably steeper cut than the 20% reduction on raw input and output pricing. Since cache reads dominate the cost of any long-running agentic session — Anthropic's own materials state they make up the majority of agentic and coding work costs — that specific cut matters more for real-world monthly spend than the headline input/output prices this comparison has focused on so far. OpenAI's GPT-6 Sol launch materials didn't include an equivalently detailed cache-pricing breakdown in the portions covered by this comparison, which is itself a gap worth flagging: a full cost comparison between these two models for a long-running coding-agent workload specifically would need each company's cache-read rate, not just list price on fresh tokens, to be genuinely accurate.

Honest limitations

• This comparison mixes first-party and third-party benchmark sources — Opus 5.5's figures are Anthropic's own; GPT-6 Sol's Terminal-Bench 4.0 figure is Artificial Analysis' independent measurement, since OpenAI's own launch page didn't include a Sol-specific number on that exact benchmark.
• Reasoning-effort settings are not always matched between the two models' reported figures — Opus 5.5's headline numbers are typically at xhigh effort, and GPT-6 Sol's AutomationBench figure is also at xhigh, but not every benchmark pairing in this post confirms identical effort-level settings on both sides.
• Neither company has published a direct, controlled head-to-head comparison of these two specific models — every number here is stitched together from each company's separate launch materials plus one independent evaluator, not a single unified test.
• Cost-per-completed-task, not list price per token, is what actually determines real spend, and that figure isn't available across both models from public sources for a like-for-like task.

Watch this comparison again once Sonnet 5.5 ships

Anthropic confirmed Claude Sonnet 5.5 is coming "in the coming weeks" as of the Opus 5.5 launch, carrying forward the same efficiency and communication improvements at a lower price point than Opus 5.5 — which may end up sitting closer to GPT-6 Sol's actual price tier than Opus 5.5 does today. If that happens, this specific comparison, Opus 5.5 against Sol at a 2x price gap, may end up being less relevant a few weeks from now than a future Sonnet 5.5 vs Sol comparison at closer price parity would be. Worth revisiting once Sonnet 5.5 actually ships rather than treating this snapshot as the final word on how Anthropic's and OpenAI's lineups compare at matched price points.

What this means for builders

Treat this less as "which model wins" and more as "which price tier your task actually needs." If a workload genuinely requires Opus 5.5's level of agentic reasoning — the kind of long-horizon, multi-file coding task Anthropic's own benchmarks emphasize — GPT-6 Sol's roughly half price doesn't make it a substitute; the capability gap on shared benchmarks is real and Anthropic's own comparison against the prior GPT-5.6 Sol generation suggests it's persistent across generations. If the task is simpler and GPT-6 Sol's capability is already sufficient, its price advantage is genuine and the lack of a direct Opus 5.5 benchmark comparison from OpenAI shouldn't be read as evasion — the two models were never built to occupy the same price tier in the first place.

A closing note on why "which is better" is the wrong first question

Before picking a side in this comparison, it's worth stepping back to the question that actually determines which model is right for a given team: not "which model is objectively stronger," but "what does this specific workload actually require, and what does getting it wrong actually cost." A team building a customer-facing agent where a single bad output damages trust has a very different risk calculus than a team running high-volume, low-stakes internal automation where an occasional error is cheap to catch and fix. Opus 5.5's benchmark lead matters more in the first case; GPT-6 Sol's price advantage matters more in the second. Neither company's marketing page is built to make that distinction for you — that judgment call belongs to whoever is actually accountable for the workload's outcomes, informed by the numbers in this comparison rather than replaced by them.

Related on explainx.ai

• Claude Opus 5.5 Launch: Every Benchmark and Reaction
• GPT-6 Sol and Luna Launch: 50% Price Cuts and Where They Actually Land
• Grok 4.7 vs Claude Opus 5.5 vs GPT-6 Sol: The Only Numbers That Overlap
• Claude Fable 5.1 vs Claude Opus 5.5: Which One Actually Do You Need
• How to Read AI Benchmarks Without Getting Fooled

Primary sources: Anthropic's Opus 5.5 announcement and OpenAI's GPT-6 Sol and Luna announcement, both September 22, 2026; Artificial Analysis independent benchmarks.

This post compares publicly disclosed benchmark and pricing figures as of September 23, 2026. Figures are subject to revision.