No. As of June 23, 2026, OpenAI has not announced or released GPT-5.6, and its newest official model is GPT-5.5. GPT-5.6 has surfaced only through developer-log traces and reporting, with prediction markets putting a public launch before June 30 at roughly 85%.

How much will GPT-5.6 cost compared to Claude Fable 5?

Claude Fable 5 is priced at $10 per million input tokens and $50 per million output. GPT-5.6 has no published price; the base-case projection holds it near GPT-5.5's $5 / $30, which would be half Fable 5's per-token rate. Treat the GPT-5.6 figure as a projection, not a confirmed price.

Which is cheaper per task, GPT-5.6 or Fable 5?

At equal loop counts a projected GPT-5.6 at $5 / $30 is roughly half the per-task cost of Fable 5 at $10 / $50. The gap closes only if Fable 5 finishes the same hard task in meaningfully fewer loops, which its reported token efficiency supports. Because GPT-5.6 has no benchmarks, its real per-task cost is unverifiable until launch.

Should I wait for GPT-5.6 or use Fable 5 now?

For work you need to ship now, use Fable 5; it is the only one of the two you can run, and its price and benchmarks are known. If you are choosing a standard for next month, wait for GPT-5.6's confirmed rate card and first independent benchmarks before betting on its projected price advantage.

GPT-5.6 vs Claude Fable 5: Which Costs Less Per Task?

Claude Fable 5

Anthropic · shipped June 9, 2026

GPT-5.6

OpenAI · unreleased (projected)

Shipped
Status: Rumored; $10 / $50
Price / Mtok: ~$5 / $30 (proj.); Published
Benchmarks: None yet; Yes
Runnable today: No; No
Cheaper per token: Yes (projected)

This is a fight between a model you can use and a model you cannot. Claude Fable 5 shipped on June 9, 2026 at a published $10 per million input tokens and $50 per million output. GPT-5.6 has no release, no price, and no benchmark: as of June 23, 2026, OpenAI’s newest official model is still GPT-5.5, and GPT-5.6 exists only as developer-log traces and prediction-market odds. So a clean cost comparison is impossible. What is possible, and useful, is to put Fable 5’s real numbers next to a disciplined projection of GPT-5.6 and see where the decision actually turns.

The short version: on the sticker rate, a GPT-5.6 that lands near GPT-5.5’s $5 / $30 would be half Fable 5’s per-token price. Per finished task the gap shrinks, because Fable 5’s token efficiency can claw back a rate disadvantage. But GPT-5.6 has no benchmark to prove its efficiency, and Fable 5 is the only one of the two you can run today. The rest is the math and the caveats.

What you can actually buy today

Start with the half of this comparison that is not a guess. Claude Fable 5 is Anthropic’s most capable generally available model, released June 9, 2026, and its API pricing is public: $10 per million input tokens, $50 per million output, with cached input reads billing near $1 per million. Its free-access window on Pro, Max, Team, and Enterprise plans closed on June 22, so from June 23 onward Fable 5 bills against credits at that rate. Anyone judging its cost from the promotional window is reading a discount, not a price.

GPT-5.6, by contrast, is a lead, not a product. Reporting from TestingCatalog on OpenAI’s GPT-5.6 preparation describes early Pro-subscriber build traces and a probable standard, Pro, and mini split, with no official confirmation. Prediction-market traders, per TokenMix’s GPT-5.6 release tracker, put a public launch before June 30 at roughly 85%, and coverage such as TechTimes’ report that a June launch nears frames it as imminent. None of that is a rate card. A leaked 1.5M-token context window is described as a behavioral observation, “plausible but unconfirmed.” Treat the capability claims the same way: reported, not measured.

The projected GPT-5.6 price

The only honest way to put a number on GPT-5.6 is to anchor on what GPT-5.5 actually costs and reason from OpenAI’s recent pattern. GPT-5.5, released April 23, 2026, runs $5 per million input tokens and $30 per million output. Across recent point releases, OpenAI has tended to hold per-token rates flat while improving efficiency under the hood, so the base-case projection is that GPT-5.6 lands at or near that same $5 / $30, with a plausible upper band higher if OpenAI prices the capability jump in. The deeper treatment of that projection lives in the companion piece on what GPT-5.6 will likely cost per task.

If that base case holds, the per-token comparison is stark: GPT-5.6 at $5 / $30 would be exactly half Fable 5’s $10 / $50. On a pure rate basis, the projected OpenAI model wins, and it is not close. The interesting question is what survives once you stop counting tokens and start counting finished tasks.

Cost per task, not per token

Per-token rate is the headline; per-task cost is the invoice. An agentic coding task is a loop: read files, plan, edit, run tests, read the failures, retry. The bill is tokens per loop multiplied by loop count, with output weighted heaviest. A more capable model that lands the job in fewer loops can be cheaper per task even at a higher rate. That is the same method used in this breakdown of what Claude Code costs per task, and it is exactly how Fable 5 beats cheaper models on hard work in the Fable 5 versus Opus 4.8 comparison.

Take two illustrative workloads, priced at Fable 5’s real $10 / $50 and a GPT-5.6 projected at $5 / $30. These are modeled figures from stated assumptions, not benchmarks.

Simple, well-scoped task (a single-file bug fix): about 15K input and 3K output tokens per loop, landed in 2 loops by either model, because the capability gap barely matters here.

Fable 5: 0.03 Mtok input x $10 plus 0.006 Mtok output x $50 = $0.60
GPT-5.6 (projected): 0.03 Mtok input x $5 plus 0.006 Mtok output x $30 = $0.33

Hard, multi-file task (a refactor across modules with debugging): about 60K input and 12K output tokens per loop. Hold the loop count equal at 4 each, the apples-to-apples case where neither model’s capability edge is assumed.

Fable 5: 0.24 Mtok input x $10 plus 0.048 Mtok output x $50 = $4.80
GPT-5.6 (projected): 0.24 Mtok input x $5 plus 0.048 Mtok output x $30 = $2.64

Modeled cost per task: Fable 5 (real) vs GPT-5.6 (projected)
Item	Value
Simple task: GPT-5.6 (proj.)	$0.33
Simple task: Fable 5	$0.60
Hard task: GPT-5.6 (proj.)	$2.64
Hard task: Fable 5	$4.80

Modeled cost per task at Fable 5's real $10/$50 and a GPT-5.6 projected at GPT-5.5's $5/$30, with loop counts held equal. At equal efficiency a half-price model is roughly half the per-task cost. The result only flips toward Fable 5 if it finishes hard tasks in meaningfully fewer loops, which its token-efficiency evidence supports but GPT-5.6 has no benchmark to rebut. GPT-5.6 figures are projections.Source: Modeled from Anthropic and OpenAI published API rates and stated loop assumptions

At equal loops, a half-price model is about half the cost, and the projection favors GPT-5.6 on both task types. The flip only happens when Fable 5’s capability cuts the loop count enough to overcome the 2x rate. Work the crossover: if Fable 5 lands the hard task in 3 loops while GPT-5.6 needs 5, Fable 5 costs $3.60 and projected GPT-5.6 costs $3.30, nearly even. Fable 5 only pulls clearly ahead when it needs roughly half of GPT-5.6’s loops on the same job. Its reported token efficiency, reaching a frontier physics answer with roughly 3x fewer tokens than GPT-5.5 in one Anthropic-cited customer case, is the evidence that this can happen. GPT-5.6 has no benchmark either way.

The catch the price tables hide

There is a reason this is not simply “the cheaper model wins.” You cannot run GPT-5.6. Every figure in its column is a projection of a price that does not exist for a model OpenAI has not confirmed. If GPT-5.6 prices the capability jump in rather than holding flat, the rate gap narrows or closes. If its real loop counts on hard work land well above Fable 5’s, the projected per-task advantage evaporates. Both are open questions with no data behind them yet.

Fable 5 carries the opposite risk profile: its price and benchmarks are fixed and public, so the only variable is how its loop count behaves on your specific workload. On capability it is a tier above Opus 4.8, with reported 80.3% on SWE-bench Pro, and the Terminal-Bench 2.1 leaderboard still shows Codex with GPT-5.5 leading Claude Code with Opus 4.8 on CLI work, so OpenAI’s line is not a pushover even today. The point is that you can verify all of that. You can verify none of GPT-5.6.

Which should you pick

If you need to ship work this week, the comparison is not really a comparison. Run Fable 5, measure its loop count on your own hard tasks, and bank the result. For well-scoped, simple work it is the more expensive choice and a cheaper model is the smarter spend, which is why the Fable 5 versus Opus 4.8 breakdown lands on Opus for routine work. Cross-check current subscription tiers on the AI pricing page, and watch the AI model release tracker for the moment GPT-5.6 actually lands.

If you are deciding what to standardize on next month, the honest move is to wait for GPT-5.6’s real rate card and first independent benchmarks before betting on its projected half-price advantage. A model that is cheaper on paper and unmeasured in practice is a plan, not a procurement decision. When the numbers are confirmed, drop them into the cost-per-task calculator and let your own token counts settle it.

Frequently asked questions

Is GPT-5.6 out yet?: No. As of June 23, 2026, OpenAI has not announced or released GPT-5.6, and its newest official model is GPT-5.5. GPT-5.6 has surfaced only through developer-log traces and reporting, with prediction markets putting a public launch before June 30 at roughly 85%.
How much will GPT-5.6 cost compared to Claude Fable 5?: Claude Fable 5 is priced at $10 per million input tokens and $50 per million output. GPT-5.6 has no published price; the base-case projection holds it near GPT-5.5's $5 / $30, which would be half Fable 5's per-token rate. Treat the GPT-5.6 figure as a projection, not a confirmed price.
Which is cheaper per task, GPT-5.6 or Fable 5?: At equal loop counts a projected GPT-5.6 at $5 / $30 is roughly half the per-task cost of Fable 5 at $10 / $50. The gap closes only if Fable 5 finishes the same hard task in meaningfully fewer loops, which its reported token efficiency supports. Because GPT-5.6 has no benchmarks, its real per-task cost is unverifiable until launch.
Should I wait for GPT-5.6 or use Fable 5 now?: For work you need to ship now, use Fable 5; it is the only one of the two you can run, and its price and benchmarks are known. If you are choosing a standard for next month, wait for GPT-5.6's confirmed rate card and first independent benchmarks before betting on its projected price advantage.

Sources

Anthropic. (2026). Claude Fable 5 and Claude Mythos 5. Primary announcement: Fable 5 pricing, release date, positioning, token-efficiency claim. Verified 2026-06-23. anthropic.com/news/claude-fable-5-mythos-5
Anthropic. (2026). Claude pricing. Primary; Fable 5 per-token and cached-read rates. Verified 2026-06-23. claude.com/pricing
OpenAI. (2026). API pricing. Primary; GPT-5.5 standard rates ($5 / $30) used as the GPT-5.6 projection baseline. Verified 2026-06-23. openai.com/api/pricing
TestingCatalog. (2026). OpenAI prepares GPT-5.6 models for the upcoming release. Secondary; unreleased status, probable variants, build traces. Verified 2026-06-23. testingcatalog.com
TokenMix. (2026). GPT-5.6 release date: Codex leaks, June odds, what’s real. Secondary; prediction-market odds, leaked 1.5M context (unconfirmed), pricing reasoning. Verified 2026-06-23. tokenmix.ai
TechTimes. (2026). GPT-5.6: June launch nears. Secondary; launch-imminent framing. Verified 2026-06-23. techtimes.com
Finout. (2026). Claude Fable 5 and Mythos 5: pricing, API costs, and benchmark comparison. Secondary; SWE-bench Pro figure attributed as vendor-reported. Verified 2026-06-23. finout.io
Terminal-Bench. (2026). Terminal-Bench 2.1 leaderboard. Agent-plus-model CLI benchmark. Verified 2026-06-23. tbench.ai/leaderboard