Claude Opus 5.5 vs Fable 5.1: When is Fable worth it?

When Anthropic released Claude Fable 5 in June 2026, the choice between Fable and Opus was simple: Fable cost more, and teams paid for it when they needed the extra capability. Claude Opus 5, which followed in July, was priced at $5 per million input tokens and $25 per million output tokens, half the cost of Fable 5's $10 and $50.

The newer versions change the math. Anthropic positions Opus 5.5 as performing at the level of Fable 5.1 on most work, and our data goes further. In our Ready for Enterprise (RFE) LLM Benchmark, Claude Opus 5.5 ranks #1 overall, and Claude Fable 5.1 ranks #10. Opus 5.5 scores higher on every benchmark both models were tested on, generates output faster, and costs 40% of Fable's token price.

For teams and enterprises evaluating Claude for generative AI workflows, coding, agentic tasks, and knowledge work, that gap affects model cost, response speed, and task success across production use cases. This comparison covers benchmarks, pricing, and speed, and when Fable 5.1 is still worth the premium.

What is Claude Fable?

Claude Fable is Anthropic's premium tier of Claude models, positioned above Claude Opus for the hardest work. Fable 5.1 shares its underlying model with Claude Mythos 5.1, a Mythos-class model that Anthropic offers only to eligible cybersecurity and life-sciences organizations through trusted-access programs. Fable 5.1 is the generally available version, with additional safeguards for areas such as cybersecurity and biology.

Claude Opus is the tier most teams use day-to-day for coding, agentic tasks, and knowledge work. Opus 5.5 is the first Opus model to ship with safeguards similar to Fable 5.1's, so the two tiers now handle sensitive requests in similar ways.

Opus 5.5 vs Fable 5.1: Benchmark comparison

Source: FullStack RFE LLM Benchmark, data snapshot from October 26, 2026. Rankings can change as new models ship and results are added.

Our RFE score combines six independent benchmarks with price and speed, and the capability score reflects benchmark performance alone. Fable 5.1 hasn't been tested on GPQA Diamond yet, so its scores are based on five of the six benchmarks. We also leave SWE-Bench Pro out of this comparison: our benchmark shows it for reference only, because it has tested just a few models so far.

Where does Opus 5.5 lead?

Opus 5.5 scores higher than Fable 5.1 on all five benchmarks both models were tested on. On most of them, the gap is small.

Agentic tasks and coding

The clearest lead is on coding tasks and tool use. Terminal-Bench 4.0 tests agents completing real command-line tasks on a computer, including writing code and making tool calls, and these evaluations reward models that complete real work correctly rather than just describe it. 

Opus 5.5 scores 64.8%, the highest of any model in our benchmark, compared with 57.9% for Fable 5.1. It also has the top Arena WebDev rating we track, at 1807 versus 1742. If your team runs agents through Claude Code, this is the gap you're most likely to notice.

Knowledge work, accuracy, and math

On factual accuracy (SimpleQA Verified), human preference (Arena Text), and advanced math (FrontierMath), the two models are within about one to two points of each other. Neither model wins by a wide margin here, and both sit near the state of the art on these tests. For most knowledge work, the quality difference between the two models is small.

How much more does Fable 5.1 cost?

Fable 5.1 costs $10 per million input tokens and $50 per million output tokens. Opus 5.5 costs $4 per million input tokens and $20 per million output tokens, so it's 40% of Fable's price on both sides. Using our 3:1 input-to-output blend, that's $8.00 versus $20.00 per million tokens.

The gap is wider than it was for the previous generation. Opus 5.5 also costs less than its predecessor, Opus 5, while Fable 5.1 kept Fable 5's $10 and $50 pricing.

Cached input costs nearly the same on both models

Prompt caching lets agents reuse the same context, such as system instructions or a codebase, without paying the full input price each time. Cache reads cost $0.20 per million tokens on Opus 5.5 and $0.25 on Fable 5.1, after Anthropic cut Fable's cache read price by 75% with the 5.1 release. For agents that reuse the same context across many calls, that makes cached input nearly the same price on both models, so the real gap comes from uncached input and output tokens.

Both models use adaptive thinking, and thinking is billed as output tokens, so token usage matters as much as the rate. A model that uses more tokens on a task can cost more than one that finishes with fewer tokens, even at the same price per token. Compare the cost of the whole thing, not just the rate.

On Claude subscription plans, the difference shows up in usage limits. Anthropic's help center says Fable is available on all paid plans but uses weekly limits faster than other Claude models. On Max plans and premium Team and Enterprise seats, you can use up to 50% of your weekly limits on Fable at no extra cost, then keep going with usage credits. On Pro plans and standard seats, Fable runs on usage credits from the start.

Which model is faster?

Opus 5.5 is faster in our measurements, at 81 tokens per second versus 56 for Fable 5.1. Here's what that means for total response time:

Estimates use time to first token (3.42 seconds for Opus 5.5 and 5.06 seconds for Fable 5.1 in our snapshot) plus output length divided by measured output speed. Time to first token varies more than output speed and may include thinking time. Real response times also depend on effort settings, tool calls, and load.

When is Fable 5.1 worth the premium?

Anthropic still positions Fable 5.1 for demanding reasoning and long-horizon agentic work, so it can be worth testing for a few kinds of tasks:

• Opus 5.5 falls short on your own work. Benchmarks measure general ability. If a specific job still fails on Opus 5.5 after you've tried higher effort settings, test Fable 5.1 on that task, especially if it's a novel problem your evaluations haven't covered or involves especially complex multi-step workflows.
• Defensive security work. Anthropic says Fable 5.1 can help identify vulnerabilities in source code for authorized defensive work, while still redirecting requests such as penetration testing and exploit generation. Opus 5.5 is the first Opus model to ship with safeguards similar to Fable 5.1's, and Anthropic reroutes many flagged security requests to Opus 4.8. Security teams should test both models on their actual tasks.
• Tasks where a wrong answer is expensive. If a failure costs far more than the tokens, such as a flawed migration plan or analysis, running the same task on a second model is a good idea, even at 2.5 times the token price.

Both models are available through the Anthropic API and Amazon Bedrock, among other platforms, so you can test them side by side in the same setup.

^{For more on Fable 5.1's features and safeguards, read Claude Fable 5.1 is here: what it means for enterprise AI.}

What about Claude Opus 5 vs Fable 5?

If you're comparing Claude Opus 5 vs Fable 5, start with price: Claude Opus 5 cost $5 per million input tokens and $25 per million output tokens, half the cost of Claude Fable 5 at $10 and $50.

Both newer models improved on their predecessors. Fable 5.1 ranks #10 in our benchmark, up from #13 for Fable 5, with a capability score of 80.7 versus 68.6. Opus 5.5 ranks #1 at a lower price than Opus 5. If you're choosing today, compare the current versions.

How to choose between the two models

Start new workloads on Opus 5.5. Build a small evaluation set from your real workflows, including the full context your agents see in production, and the best way to compare the two models is to run the same job on both at a few effort levels. Even two tasks that look alike can need different effort settings. Then test Fable 5.1 only on the tasks where Opus 5.5 falls short, and see how the result compares on quality and the cost of the full run.

You don't have to pick one model for everything. Routing each task to the model best suited to it, whether that means your hardest tasks go to Fable or simple, high-volume jobs go to Claude Haiku, lets each model do the work it handles best. Keeping the model choice in configuration makes that easy to adjust, and it's worth keeping a watch on new releases, since rankings shift quickly.

How FullStack can help

FullStack is Anthropic Certified. We help teams test Claude models against their real workloads, route each task to the right model, and build the agentic workflows that put those models into production.

^{Compare these models in the RFE benchmark.}