Claude Fable 5.1 vs Opus 5: Which Should You Actually Use?

Claude Fable 5.1 shipped September 1, 2026, and it beats Opus 5 on every benchmark Anthropic published except one restricted-access outlier. It also costs exactly twice as much per token. Here's the honest read on which one to run.

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Claude Fable 5.1 vs Opus 5: Which Should You Actually Use?

Claude Fable 5.1 launched September 1, 2026, and on all 9 benchmarks Anthropic published at launch, it beats Claude Opus 5. The margins are mostly narrow, a few points here and there, except one benchmark where the gap is wide. It also costs exactly double Opus 5's price on both input and output tokens. Anthropic's own documentation doesn't hedge on which model to reach for by default, and it isn't Fable 5.1.

Here's the full comparison: specs, pricing, all 9 published benchmarks, and the actual decision framework for picking between the two.

Update, October 23, 2026: Anthropic released Claude Opus 5.5 on September 22, 2026, and its docs now say to start with Opus 5.5, not Opus 5, for most workloads. If you are choosing today, read the Fable 5.1 vs Opus 5.5 section below first. The Opus 5 comparison is kept as published.

What's the difference between Claude Fable 5.1 and Opus 5?

Fable 5.1 wins on raw benchmark scores across the board. Opus 5 costs half as much per token. At Fable 5.1's launch, Anthropic recommended Opus 5 as the default for most workloads and Fable 5.1 only for demanding reasoning and long-horizon agentic work, or when Opus 5 at higher effort still fell short of your evals. Since September 22, 2026, the same guidance names Opus 5.5 as the default.

That's not a hedge we're adding. It's Anthropic's own stated positioning, published alongside the benchmark numbers below.

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Fable 5.1 vs Opus 5.5: what changed in September

Claude Opus 5.5 shipped on September 22, 2026 at $4 per million input tokens and $20 per million output tokens, so Fable 5.1 now costs 2.5 times Opus 5.5 per token instead of 2 times Opus 5. Anthropic's models overview now reads: "start with Claude Opus 5.5 for most workloads," and use Fable 5.1 "for demanding reasoning and long-horizon agentic work, or when your evals on Claude Opus 5.5 at higher effort still fall short."

(Source: Anthropic models overview and pricing, checked October 23, 2026.)

The decision rule is the same as before, one step newer: start on Opus 5.5, raise its effort before you switch, and move to Fable 5.1 only when your evals still fall short on demanding reasoning or long-horizon agent work. Anthropic's model-selection guide puts that step at xhigh or max effort on Opus 5.5. Two Opus 5.5 changes to check before you migrate: forced tool use (tool_choice of any or tool) returns an error, and thinking can't be turned off. For release details and the cost math, see our Claude Opus 5.5 release breakdown, and for the full Haiku, Sonnet and Opus ladder, our Opus vs Sonnet vs Haiku guide.

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Specs side by side

(Source: platform.claude.com model overview for Fable 5.1 specs; this site's Claude Opus 5 pricing guide and Opus 5 benchmarks guide for Opus 5's own numbers.)

Context window and max output are identical. The gap is entirely in price and, per the benchmarks below, in raw capability.

Fable 5.1 vs Opus 5: all 9 published benchmarks

Anthropic put both models in the same comparison table at Fable 5.1's launch. Here are all 9 benchmarks where a direct Fable 5.1 vs Opus 5 number exists.

(Source: anthropic.com, Claude Fable and Mythos 5.1)

GDPval-AA v2 is a raw score, not a percentage, so read that row as a relative ranking rather than a pass rate. Fable 5.1 leads on all 9, but look at the size of each lead before drawing a conclusion. Eight of the nine are single-digit-point margins. One isn't.

Terminal-Bench-Science 0.1 is the outlier: a 23.6-point gap, Fable 5.1 nearly doubling Opus 5's score. That's the one benchmark in this table where "Fable 5.1 wins" undersells it. Everywhere else, including CursorBench 3.2.0 where Fable 5.1 posts 73.4% against Opus 5's 70.0%, the two models are close enough that price should probably be the deciding factor before benchmark score is.

Why does Mythos 5.1 show up in this conversation?

Claude Mythos 5.1 is the same underlying model as Fable 5.1, not a different model with different weights. What changes is the safety filtering. Fable 5.1 ships generally available with standard safeguards. Mythos 5.1 is restricted to vetted organizations through two channels: cybersecurity groups vetted under Anthropic's Cyber Verification Program, and life-sciences organizations vetted under the Life Sciences Verification Program, a partnership with the US government.

On Terminal-Bench 4.0 specifically, Mythos 5.1 posts a higher score than Fable 5.1, at 60.9% versus Fable 5.1's 55.8%. That's not a fair comparison to run against Opus 5 though, since Mythos 5.1 isn't something most teams can actually get access to. If you're evaluating what you can deploy, the Fable 5.1 vs Opus 5 numbers above are the ones that apply. If you're a vetted cybersecurity or life-sciences org and Mythos access is on the table, that's a separate conversation from this one.

The price-vs-performance math

Fable 5.1 wins every benchmark listed above except the Mythos-only case, and costs exactly 2x Opus 5 on both input and output tokens. That's the whole tradeoff, stated plainly.

On eight of the nine benchmarks, the performance gap is a few points, not a blowout. Paying double for a 1.4 to 4.5-point edge is a real decision, not an obvious one, and it depends entirely on what you're building. If your workload runs at volume, that 2x multiplies across every token you send. If your workload is a small number of high-stakes runs where a few extra points of accuracy change the outcome, the math looks different.

Terminal-Bench-Science 0.1 is the exception where the case for Fable 5.1 is much stronger: a 23.6-point lead isn't a rounding error, it's a different tier of result. If your evals track anything close to that benchmark's shape, that's the scenario Anthropic is actually pointing at.

Anthropic's own guidance answers the general question directly: start with Opus 5, and reach for Fable 5.1 for demanding reasoning and long-horizon agentic work, or when your evals on Opus 5 at higher effort still fall short. That's a specific bar, not a vague "it depends." If Opus 5 already clears your evals, there's no result in this comparison that argues for switching. If the workload is a long-horizon agent you need running in production rather than on a benchmark, our AI agent development team designs, builds and maintains that agent on your own systems.

When should you use Fable 5.1 instead of Opus 5?

Reach for Fable 5.1 when:

• Your evals on Opus 5, even at higher effort settings, still fall short
• The task is long-horizon agentic work: multi-step runs where the model plans, executes, and self-corrects over an extended session
• Your workload resembles Terminal-Bench-Science 0.1's shape, where the gap to Opus 5 is largest
• Cost per task matters less than the raw hit rate on hard, non-obvious reasoning

Stay on Opus 5 when:

• You haven't specifically tested Opus 5 against your own evals and found it lacking
• Cost per token matters, since Opus 5 is half the price on both input and output
• The task is closer to the workloads where the two models are within a few points of each other, which is most of the benchmark table above

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Fable 5.1 vs Opus 5: the decision table

How this compares to the last generation

The last time these two model lines faced off, the picture looked different. In our Fable 5 vs Opus 4.8 comparison, Fable 5 held a 28-point lead over Opus 4.8 on Every's Senior Engineer benchmark, big enough that the price premium was easy to justify for large, well-scoped jobs. Then Opus 5 shipped in July 2026 at half of Fable 5's price and closed most of that gap, ranking #1 on the Artificial Analysis Intelligence Index in the process (see our Opus 5 vs Fable 5 comparison for that round).

Fable 5.1 reopens a lead over Opus 5, but a much narrower one than the old Fable 5 vs Opus 4.8 gap, outside of the Terminal-Bench-Science 0.1 outlier. The two-model dynamic hasn't changed. The size of the gap has, and it's smaller than last time on most measures.

For the full pricing and benchmark rundown against Fable 5.1's own predecessor, see our Fable 5.1 pricing and benchmarks explainer and the 8 things that changed in Fable 5.1 breakdown.

FAQ

Is Claude Fable 5.1 better than Opus 5?

On all 9 benchmarks Anthropic published at launch, yes: Fable 5.1 scores higher than Opus 5 on Terminal-Bench-Science 0.1, AutomationBench, Humanity's Last Exam (no tools and with tools), Terminal-Bench 4.0, CursorBench 3.2.0, OSWorld 2.0 (partial and strict), and GDPval-AA v2. Most of those leads are a few points. Fable 5.1 also costs exactly twice as much per token. Anthropic's documentation recommended Opus 5 as the default at launch and now recommends Opus 5.5.

How much more does Fable 5.1 cost than Opus 5?

Exactly double, on both sides of the ledger. Fable 5.1 is $10 per million input tokens and $50 per million output tokens. Opus 5 is $5 per million input tokens and $25 per million output tokens.

Should I use Fable 5.1 or Opus 5?

Between those two, start with Opus 5 and move to Fable 5.1 for demanding reasoning and long-horizon agentic work, or when your evals on Opus 5 at higher effort still fall short. That was Anthropic's guidance at launch. Today Anthropic recommends starting with Opus 5.5 instead, which is cheaper than Opus 5 at $4/$20 per million tokens.

Is Opus 5.5 better than Fable 5.1?

Anthropic still positions Fable 5.1 above Opus 5.5: it is the model for "demanding reasoning and long-horizon agentic work," while Opus 5.5 is the recommended starting point for most workloads. Opus 5.5 costs $4/$20 per million tokens against Fable 5.1's $10/$50 and runs with lower latency. Test Opus 5.5 at higher effort on your own evals before paying for Fable 5.1.

Should I use Opus 5 or Opus 5.5 now?

For new work, Opus 5.5. It is cheaper per token ($4/$20 against $5/$25) and is the model Anthropic's docs now recommend first. Check its breaking changes before you switch an existing integration: forced tool use returns an error and thinking can't be disabled.

What's the biggest performance gap between the two models?

Terminal-Bench-Science 0.1, where Fable 5.1 scores 52.6% against Opus 5's 29.0%, a 23.6-point gap. The next-largest is AutomationBench at 4.5 points. Every other benchmark in Anthropic's comparison table shows a gap of 4.3 points or less.

What is Claude Mythos 5.1, and is it the same as Fable 5.1?

Same underlying model, different safety filtering. Fable 5.1 is generally available with standard safeguards. Mythos 5.1 is restricted to vetted cybersecurity organizations (via the Cyber Verification Program) and life-sciences organizations (via the Life Sciences Verification Program, a partnership with the US government). On Terminal-Bench 4.0, Mythos 5.1 scores higher than Fable 5.1 (60.9% vs 55.8%), but most teams evaluating Fable 5.1 can't get access to Mythos to reproduce that number.

Do Fable 5.1 and Opus 5 have the same context window?

Yes. Both support a 1,000,000-token (1M) context window and a 128,000-token maximum output.

Where can I compare Fable 5.1 and Opus 5 against other current models?

Our model comparison hub tracks pricing and specs across every current Claude, GPT, and Gemini release, including how both models stack up against Sonnet-tier and Haiku-tier options for lower-cost workloads.

Picking the right model shouldn't be a per-task guessing game

Every dollar spent on a task that didn't need Fable 5.1's ceiling is a dollar that should have gone to Opus 5 instead, and every task that actually needed the ceiling and got routed to a cheaper model costs you the rework. That's a routing problem, not a one-time model choice.

ManasFlow places senior AI engineers into your team to build the pipelines and routing logic that make this decision automatically instead of manually. Book a 30-minute strategy call if you want this built into your actual production stack.

Sources: Anthropic, Claude Fable and Mythos 5.1 announcement, Anthropic model overview docs

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