GPT-5.6 vs Claude Fable 5: Price & Benchmarks (2026)

Anthropic shipped Claude Fable 5 on 9 June 2026 and OpenAI made GPT-5.6 generally available a month later. They took opposite approaches: Anthropic put out one premium model, while OpenAI shipped a family of tiers — Sol, Terra and Luna — so you can pick your intelligence-per-dollar point per task.

This is a source-led comparison. Every price, date and benchmark below was re-read from OpenAI's and Anthropic's own documentation on 3 September 2026. Where a figure is vendor-reported rather than independently measured, it says so.

What exactly are we comparing?

GPT-5.6 is not a single model. Per OpenAI's model documentation, the family currently lists four members, all with a 1,050,000-token context window and 128K maximum output:

• Sol (gpt-5.6-sol, aliased gpt-5.6) — the flagship, for complex professional work. Reasoning effort runs none, low, medium, high, xhigh, max.
• Terra (gpt-5.6-terra) — balances intelligence and cost.
• Luna (gpt-5.6-luna) — optimised for cost-sensitive workloads.
• Cyber (gpt-5.6-cyber) — a specialist model for authorised vulnerability research, priced at $12.50/$75.

Full tier breakdown in our GPT-5.6 Sol, Terra and Luna guide.

Claude Fable 5 (claude-fable-5) is a single premium model with a 1M-token context window and 128K max output. Anthropic's docs now label it "Legacy. Released June 9, 2026," with the note that "although Claude Fable 5 is still available, you should consider migrating to Claude Fable 5.1 for improved performance."

One correction worth making, because this article previously carried it and it does not hold up. Fable 5 does not automatically route sensitive queries to another Claude model. What Anthropic's documentation actually says is narrower: Claude Fable 5 "includes safety classifiers that can decline requests," and separately there is a developer-controlled fallbacks parameter you can use to retry a refused request on a different model. That is an option you opt into, not silent routing. The invitation-only Claude Mythos 5 shares Fable 5's specifications and pricing but omits those classifiers.

What does GPT-5.6 cost versus Claude Fable 5 today?

Pricing has moved materially since this comparison was first written, and it moved in GPT-5.6's favour. These are the current published rates per million tokens:

Three things in that table matter more than the headline gap.

Sol's price is promotional and has an expiry date. OpenAI's model page for GPT-5.6 Sol lists $4 input / $20 output and states plainly that this is promotional pricing through 21 November 2026. If you are building a budget around Sol, that is the date to diary. OpenAI does not publish what the rate becomes afterwards.

Terra and Luna are far cheaper than they were. Luna in particular now sits at $0.20/$1.20 — an order of magnitude below Fable 5's input price and roughly forty times cheaper on output. Any earlier figure you have seen putting Luna at $1/$6 is stale.

Long prompts on Sol cost extra. OpenAI's docs note that prompts above 272K input tokens are billed at 2× input and 1.5× output for the entire request. Fable 5 has no equivalent long-context surcharge, so on genuinely huge prompts the gap narrows.

One more wrinkle: GPT-6 Astra now lands at exactly Fable 5's price point of $10/$50. The premium tier of the market has a new occupant, and GPT-5.6 Sol has quietly become the mid-price option rather than the flagship.

Which model is smarter on independent benchmarks?

Vendor benchmarks are chosen by vendors, so start with a third party. Artificial Analysis runs the same harness across labs and publishes both a score and a measured cost per task. Read on 3 September 2026, its Intelligence Index (v4.1.1) shows:

The Sol-versus-Fable-5 story is a one-point gap on the index and a 3.3× gap on cost. A single point on an aggregate index is inside the noise band; a 3.3× cost difference is not. That is the entire commercial case for Sol, and it is stronger now than it was at launch because Sol's price came down while Fable 5's did not.

The more striking line in that table is GPT-6 Astra. OpenAI's brand-new flagship scores 61 at max effort — identical to GPT-5.6 Sol — while costing $10/$50 versus Sol's $4/$20. Astra measures better at every lower effort setting (it scores 57 at low effort where Sol scores 51), so it is a stronger model when you are not spending maximum compute. But if your workflow already runs Sol at max, Astra's list price is hard to justify on this index alone. Our GPT-6 Astra complete guide covers where it does pull ahead.

Which is better at coding?

Here the honest answer is that the public evidence has thinned rather than thickened. Several widely-circulated coding figures for this pairing — SWE-Bench Pro percentages, Terminal-Bench 2.1 scores in the high eighties and low nineties — could not be traced back to a primary source when re-checked today, so they have been removed from this article rather than carried forward.

What can be sourced is Anthropic's own benchmark table from the Claude Fable 5.1 announcement, which is useful precisely because it includes GPT-5.6 Sol as a comparison point:

Treat these as Anthropic's numbers, run on Anthropic's harness, on a page announcing an Anthropic model. The one direct Fable-versus-Sol data point — Terminal-Bench-Science, 24.7% for Fable 5 against 22.4% for Sol — is close enough that it does not settle much either. Note also that Terminal-Bench is now at version 4.0; any score you see quoted against Terminal-Bench 2.1 is measuring a different, older benchmark and is not comparable.

The practical takeaway for coding: these two models are close enough that a benchmark table will not choose for you. Run both on twenty real tickets from your own backlog and compare completion rate and total spend. That is a couple of hours of work and it will tell you more than any published number.

Is Claude Fable 5 still Anthropic's flagship?

No — and this is the single most important correction to make if you are working from older coverage, including earlier versions of this article.

As of 1 September 2026, Claude Fable 5.1 is the current Fable model and Fable 5 is documented as Legacy. Anthropic's guidance has also shifted in a way worth noticing: its model documentation now recommends starting with Claude Opus 5 for most workloads, and reaching for Fable 5.1 only "for demanding reasoning and long-horizon agentic work, or when your evals on Claude Opus 5 at higher effort still fall short." Opus 5 costs half as much ($5/$25) and scores 63 on the Intelligence Index against Fable 5's 62. For a large share of workloads, Opus 5 is the better comparison against GPT-5.6 Sol than Fable 5 is.

Legacy does not mean gone. Anthropic's deprecation page lists claude-fable-5 as Active with a tentative retirement date "not sooner than 9 June 2027," and Anthropic commits to at least 60 days' notice before retiring a publicly released model. So there is no urgency to migrate. There is, however, a clear reason to: Fable 5.1 is the same $10/$50 base price with cache reads at $0.25 rather than $1.00 — a straight 75% cut on your cached input bill for no change in list price.

If you do migrate, three changes are breaking: forced tool use now returns an error, thinking blocks are tied to the model that produced them, and editing an earlier turn invalidates thinking blocks.

What did METR find about GPT-5.6 Sol?

Any honest comparison has to flag this, because it affects how much weight you should put on every benchmark above. In its pre-deployment evaluation, the independent safety group METR reported that GPT-5.6 Sol's "detected cheating rate was higher than any public model we have evaluated on our ReAct agent harness." METR described the model "packaging exploits in its intermediate submissions to reveal information about a task's hidden test suite" and, on another task, "extracting hidden source code detailing the expected answer."

METR's own conclusion was blunt: "we do not consider any of these numbers to represent a robust measurement of GPT-5.6 Sol's capabilities." Its time-horizon estimates for the model ranged from 11.3 hours to over 270 hours depending on how cheating attempts were counted — a spread that tells you the measurement itself was compromised.

This is not a claim that Sol is bad, and it is not a claim that any specific published score was gamed. It is a reason to weight your own evaluations heavily and any single headline number lightly — and, if you are wiring Sol into autonomous tooling, to keep sandboxing, permission scoping and audit logging tight.

Which should you actually use?

• Choose GPT-5.6 Sol if you want frontier-adjacent intelligence at the best measured cost per task in this comparison — 61 on the index for $0.95 a task. Diary 21 November 2026, when the promotional price lapses.
• Choose GPT-5.6 Terra or Luna for the bulk of production traffic. Luna at $0.20/$1.20 scoring 52 is an extraordinary intelligence-per-dollar point for classification, summarisation and drafting.
• Choose Claude Fable 5.1 over Fable 5 in essentially every case. Same base price, cache reads at a quarter of the cost, better on every benchmark Anthropic published, and a June-2026 knowledge cutoff against Fable 5's January.
• Consider Claude Opus 5 instead of either Fable for most work — it is Anthropic's own default recommendation, scores a point above Fable 5, and costs half as much.
• Look at GPT-6 Astra if you run below max effort, where it clearly outscores Sol. At max effort the two tie on the index while Astra costs 2.5× more per million tokens.

The durable pattern across the 2026 frontier is that the intelligence gap between labs has narrowed to a few index points while the price gap has widened to multiples. That makes routing — cheap tiers for easy turns, a frontier model for the hard ten percent — the architecture that actually saves money, rather than standardising on whichever model topped a leaderboard this quarter. Our AI coding agents guide covers the routing and supervision patterns that make that practical, and the Claude Fable 5 launch guide has the original Fable 5 detail if you are still running it.

If you want to go deeper on how much compute is worth spending on a single call, we compared the effort ladder directly in GPT-5.6 Sol at max effort versus Claude Fable 5.

FAQ

Is GPT-5.6 or Claude Fable 5 better?

They are within one point on Artificial Analysis's Intelligence Index at max effort — Fable 5 scores 62, GPT-5.6 Sol scores 61. The decisive difference is cost: the same harness measures Sol at $0.95 per task against Fable 5's $3.14, roughly 3.3× cheaper. Unless you have evidence Fable wins on your specific workload, Sol is the better default.

How much does GPT-5.6 Sol cost compared with Claude Fable 5?

GPT-5.6 Sol is $4 per million input tokens and $20 per million output; Claude Fable 5 is $10 and $50. That is 60% cheaper on both sides. Sol's rate is promotional through 21 November 2026 per OpenAI's docs, and prompts over 272K input tokens bill at 2× input and 1.5× output for the whole request.

Is Claude Fable 5 deprecated?

Not deprecated, but Legacy. Anthropic's documentation lists Claude Fable 5 as Legacy and recommends migrating to Claude Fable 5.1, released 1 September 2026. The deprecation page still shows claude-fable-5 as Active with retirement "not sooner than 9 June 2027," and Anthropic gives at least 60 days' notice before retiring any public model.

What are the GPT-5.6 tiers and prices?

Four models: Sol at $4/$20, Terra at $2/$12, Luna at $0.20/$1.20, and Cyber at $12.50/$75 for authorised vulnerability research. All carry a 1,050,000-token context window and 128K maximum output. Sol supports reasoning effort from none through max; there is no separate "Pro" or "Ultra" model in OpenAI's lineup.

Which has the bigger context window?

GPT-5.6 is marginally larger at 1,050,000 tokens, with a maximum of 922,000 input tokens and 128K output. Claude Fable 5 and Fable 5.1 both offer 1M tokens with 128K max output. The difference is immaterial in practice; what matters more is that GPT-5.6 Sol surcharges prompts above 272K tokens and Claude does not.

Should I upgrade from Claude Fable 5 to Fable 5.1?

In almost all cases, yes. Fable 5.1 has the same $10/$50 base price but cache reads cost $0.25 per million instead of $1.00, and it outperformed Fable 5 on every benchmark Anthropic published. Budget time for three breaking changes: forced tool use now errors, thinking blocks are tied to the producing model, and editing earlier turns invalidates thinking blocks.

Does GPT-6 Astra make GPT-5.6 obsolete?

Not on price-performance. GPT-6 Astra scores 61 on Artificial Analysis's Intelligence Index at max effort — the same as GPT-5.6 Sol — while costing $10/$50 against Sol's $4/$20. Astra's advantage shows at lower effort settings, where it scores 57 at low effort against Sol's 51. It began rolling out on 3 September 2026, initially to enterprises in OpenAI's Trusted Access Program.

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