Claude Fable 5.1 vs GPT-5.6 Sol: The New #1 vs the Pricing Undercut

Pick up any coverage of Claude Fable 5.1 and GPT-5.6 Sol from the first week of September and you will meet the same sentence: Anthropic's new flagship, released September 1, 2026, beat OpenAI's GPT-5.6 Sol on essentially every benchmark Anthropic ran. That sentence is true, and it is also the smaller half of the story. The larger half is that GPT-5.6 Sol, OpenAI's flagship that has been in production since July 9, 2026, is roughly 2.5x cheaper at list price, is measured to use about a third fewer tokens on the same work, and — as of an Epoch AI repricing analysis on September 8 — only looks more attractive the shorter your prompts are. Claude Fable 5.1 is the new #1 on the independent index, at 66 against GPT-5.6 Sol's 61. Whether that five-point lead is worth what it costs is the entire argument of this page.

The scoreboard, and who reported each number

Start with the one figure neither vendor controls. On the Artificial Analysis Intelligence Index at max effort, Claude Fable 5.1 scores 66 — the highest AA has ever recorded — against GPT-5.6 Sol's 61, though AA's model page for the default-fallback configuration Anthropic actually serves lists 53, still #1 of 201. That is the cleanest independent statement of the matchup: Anthropic's flagship is the current ceiling, and the gap to OpenAI's is real but not enormous.

Below that, the component benchmarks split by who ran them, and that is worth keeping straight. Anthropic reports Claude Fable 5.1 at 52.6% on Terminal-Bench-Science 0.1 against GPT-5.6 Sol's 22.4%, at 55.8% on Terminal-Bench 4.0 against 37.3%, at 73.4% on CursorBench 3.2.0 against 67.2%, and at 1,853 on GDPval-AA v2 against 1,711. OpenAI, for its part, reports GPT-5.6 Sol at roughly 96% on SWE-bench Verified — a software-engineering figure higher than anything Anthropic publishes for Fable 5.1, because Anthropic does not report that benchmark at all. Read the pattern honestly: each vendor leads on the metrics it chooses to publish, the two companies barely share a benchmark, and the component numbers should be treated as vendor-reported direction, not cross-vendor fact. The index and your own evals are the only apples-to-apples signals.

The spec sheet, side by side

• Price — Claude Fable 5.1 $10.00 / $50.00 per 1M, flat at all lengths vs GPT-5.6 Sol $4.00 / $20.00 per 1M up to 272K input, then the whole request reprices at $8.00 / $30.00 (per Epoch AI's September 8 analysis). Cache reads $0.25 vs $0.40.

• Context / max output — Claude Fable 5.1: 1M in / 128K out. GPT-5.6 Sol: ~1.05M in / 128K out.

• Inputs — both take text and image.

• Independent score — Claude Fable 5.1 at 66 on the AA Intelligence Index (max) vs GPT-5.6 Sol at 61.

• Tokenizer — OpenAI reports GPT-5.6 Sol's tokenizer uses roughly 34% fewer tokens on typical text, which is a price cut that never appears on the rate card.

• Status — Claude Fable 5.1 GA 2026-09-01; GPT-5.6 Sol GA 2026-07-09 with a promotional input/output rate in effect through late 2026.

The price gap, the token gap, and the cliff

The arithmetic starts at list price and gets more interesting from there. At $4 / $20 against $10 / $50, GPT-5.6 Sol is 2.5x cheaper per token. Add OpenAI's reported tokenizer efficiency — roughly 34% fewer tokens on the same text — and the same logical task costs meaningfully less on Sol than even the rate-card ratio suggests. This is why Anthropic's launch coverage leaned on cache reads instead: Claude Fable 5.1's $0.25 cache-read rate is genuinely cheap, and it is what rescues long re-read agent sessions from the $10 / $50 headline. A 100K-token context re-read fifty times costs $1.25 on Claude Fable 5.1 versus $2.00 on GPT-5.6 Sol at its $0.40 cache rate.

Then there is the cliff, which cuts the other way. GPT-5.6 Sol's $4 / $20 tier only applies up to 272K tokens of input; past that, Epoch AI's September 8 analysis shows the whole request repricing at $8 in / $30 out. Claude Fable 5.1 has no such cliff — its $10 / $50 is flat at every length, and at very long input sizes the flat rate can undercut Sol's repriced tier outright. For teams whose prompts routinely exceed a quarter-million tokens, the "cheap OpenAI model" framing collapses; for everyone else, Sol's price and tokenizer advantages are the headline.

What the five index points buy

The five-point index gap is concentrated in exactly the work where a model that gives up early costs the whole run. Anthropic's reported margins on Terminal-Bench-Science (52.6% to 22.4%) and AutomationBench are the largest between any two current flagships, and Artificial Analysis's own model page shows what that costs in practice: $7.63 of model spend and 190M output tokens to run the index, against a 92M median, because the stronger model writes far more before it stops. If your work is autonomous research, long-horizon agents, or tasks where a wrong early decision compounds, that premium buys the current ceiling. If your work is software engineering where GPT-5.6 Sol already passes your evals, the five points are a tax.

The honest way to choose

There is no stable winner here, and pretending otherwise is how teams overpay. The defensible position is to treat Claude Fable 5.1 as the capability ceiling and GPT-5.6 Sol as the value standard, then measure your own workload against both — which is cheap to do because Claude Fable 5.1 and GPT-5.6 Sol are both on OrcaRouter at their providers' list prices with zero markup, behind one OpenAI-compatible endpoint. Route the long-horizon and agentic traffic to Claude Fable 5.1, keep the high-volume software-engineering traffic on GPT-5.6 Sol, and let the routing DSL move a model up or down the moment your evals — or the price cards — change. OpenAI's promotional rate expires, Anthropic's point releases land, and the tokenizer advantage shows up differently on every corpus; the models will keep trading places, and the setup that can trade with them is worth more than either flagship alone.