Claude Fable 5 vs GPT-5.5 Pro: The Frontier of Artificial Intelligence in Two Models

Since June 9, 2026, the public has had access to the two most capable models ever released by Anthropic and OpenAI: Claude Fable 5 and GPT-5.5 Pro. Together they represent the best that commercial artificial intelligence can offer today, but they do so with very different philosophies, prices, and strengths.

This comparison is not about crowning an absolute winner — there isn’t one — but rather drawing a map so that every team knows which to choose based on the work they need to solve.

The Context of the Comparison

Claude Fable 5 arrived yesterday, June 9, as the public version of Mythos 5, Anthropic’s Mythos-class model that until now was only available to government cybersecurity agencies. Fable 5 is the same model, but with safety classifiers that redirect high-risk queries (cyber, biology, distillation) to Opus 4.8.

GPT-5.5 Pro launched on April 23, 2026 as the premium tier of GPT-5.5. It is a deep reasoning model designed for tasks that demand maximum precision: research mathematics, legal analysis, high-risk data science.

Both models have a context window of approximately 1 million tokens and can generate up to 128 thousand output tokens. But that’s where the similarities end.

Prices: The Gap Is Enormous

The price difference between the two models is so wide that the first decision filter should be economic:

Claude Fable 5 costs 3 times less on input and 3.6 times less on output than GPT-5.5 Pro. For a monthly volume of 10 million output tokens, the difference is $500/month vs $1,800/month.

There is an important nuance: GPT-5.5 applies a long-context surcharge above 272 thousand input tokens (2× on input, 1.5× on output over the entire session). Fable 5 has no published surcharge. For jobs with very long documents or complete repositories, GPT-5.5’s price advantage erodes, and GPT-5.5 Pro’s directly reverses.

Benchmarks: The Complete Table

The only table that directly pits both models against each other under the same conditions was published by Anthropic. Where the numbers overlap with OpenAI’s, both sources agree:

* Marks the unrestricted Mythos 5 model; in Fable 5 these domains are redirected to Opus 4.8. † GPT-5.5 via Codex CLI, its own evaluation harness.

Fable 5 leads in every row of the table. The most notable differences are in agentic coding: FrontierCode Diamond shows a gap of 23.6 points, and SWE-Bench Pro a gap of 21.7 points.

And GPT-5.5 Pro? The Pro variant of GPT-5.5 stands out in benchmarks that Anthropic did not include in its table:

• FrontierMath Tier 4: 39.6% — the hardest research mathematics evaluation
• BrowseComp: 90.1% — search and synthesis of information across multiple web sources
• ARC-AGI-2: 85.0% — abstract reasoning and adaptation to novel tasks
• GPQA Diamond: 93.6% — STEM reasoning at PhD level
• MRCR v2 (512K-1M): 74.0% — long-context retrieval

Where Each One Wins

Claude Fable 5

Fable 5’s strength lies in long-horizon agentic work: autonomous sessions that can last days, delegating tasks to sub-agents and validating their own work. It is designed for massive code migrations, issue resolution in complex repositories, and multi-step analysis.

Key advantage: token efficiency. Early clients report that Fable 5 completes complex tasks using one-third of the tokens that GPT-5.5 needs to match the result. In multi-step reasoning work, the real cost can be lower even if the per-token price is higher.

On multimodal benchmarks, Fable 5 averages 92.4 vs 70.4 for GPT-5.5 (BenchLM), with advantages in complex documents (GDP.pdf), computer use (OSWorld), and legal reasoning.

GPT-5.5 Pro

GPT-5.5 Pro is the model for maximum precision in specific niches: frontier research mathematics, deep web search, and abstract reasoning. On FrontierMath Tier 4 (39.6%) and BrowseComp (90.1%) it stands alone or clearly ahead of any public alternative.

Its integration with Codex is another real advantage: more than 85% of OpenAI staff use Codex weekly, and GPT-5.5 is tuned to complete terminal tasks with fewer tokens than its predecessor. Terminal-Bench 2.0 at 82.7% is its flagship coding result.

For teams already living in the OpenAI ecosystem (Codex, ChatGPT, API), GPT-5.5 Pro is the natural evolution with no integration friction.

Safety Posture: Convergence

Both labs reached the same conclusion: cybersecurity and biology are domains that require controlled access.

Anthropic solved it by separating Fable 5 (with classifiers that redirect risky queries to Opus 4.8) from Mythos 5 (unrestricted, only for Project Glasswing partners). Fable 5’s classifiers activate in less than 5% of sessions, according to early data.

OpenAI classifies cyber and biology as “High” under its Preparedness Framework, with stricter classifiers and a Trusted Access for Cyber program for verified defenders.

In practice: if your work involves vulnerabilities, biological weapons, or model distillation, expect rejections or redirections from both.

Which One to Choose?

The mature answer for most teams is not to choose just one: use GPT-5.5 or Fable 5 as a daily driver depending on the task, GPT-5.5 Pro for jobs requiring maximum precision, and Opus 4.8 at $5/$25 as an economical backup option.

In the one place where the comparison is direct —the benchmark table— Fable 5 leads in nearly every metric. But leadership in raw capabilities does not always translate into the best tool for day-to-day work. The right decision depends on your task profile, your budget, and your investment in each provider’s ecosystem.

Primary source: Anthropic — System Card: Claude Fable 5 & Claude Mythos 5 · OpenAI — Introducing GPT-5.5