Muse Wonder vs Claude Fable 5.1: One Index Point Apart, Two and a Half Times the Price

On Artificial Analysis' current Intelligence Index, Claude Fable 5.1 reads 53 and Muse Wonder reads 52. One point. On the rate card, Claude Fable 5.1 is $10.00 per million input tokens and $50.00 per million output tokens, while Muse Wonder is $4.00 and $20.00. Two and a half times. That is the whole matchup in two sentences, and it is a much stranger comparison than a one-point gap normally implies — because the cheaper model is one day old with a thin independent record, the dearer one has been shipping since September 1 with six weeks of provider coverage behind it, and the two of them do not agree at all about how much of your bill should be cached tokens.

Here is the useful framing before the detail. If your traffic is a long agentic loop over a stable prompt prefix, the price gap between Muse Wonder and Claude Fable 5.1 mostly evaporates, and you should pick on measured capability. If your traffic is short calls at volume with little cacheable prefix, the gap is real and it is 2.5×, and one index point is not a reason to pay it.

The two models, dated

Claude Fable 5.1 is the Claude maker's Mythos-class model — a capability tier the company places above the Opus class — released on September 1, 2026 as the successor to Claude Fable 5. It takes text, image and file input, writes text, carries a 1,000,000-token context window with a 128,000-token output ceiling, and supports adaptive reasoning and structured outputs. Six weeks of independent measurement exist for it, it is served by multiple API providers, and its rate card includes a batch mode at $5.00 / $25.00 that halve-cheapens asynchronous work.

Muse Wonder is Meta Superintelligence Labs' frontier release of October 12, 2026, announced alongside a second checkpoint called Muse Wonder Full. Only muse-wonder-1.0 has an endpoint you can call — on the Meta Model API and inside Muse Code — and it is the one every figure below refers to. It carries a 1,048,576-token context window, an output budget that caps at 943,718 tokens in a single response, and accepts text, image, speech and video input against text output. Muse Wonder Full is the higher-scoring of the two and is Muse Code subscription only, so it has no per-token price to compare against anything here.

That asymmetry is the first thing to hold onto. Fable 5.1 is a settled quantity you can benchmark against your own workload this afternoon. Muse Wonder is a two-day-old release whose independent record consists of one evaluator's row.

Head to head, dimension by dimension

Index figures are Artificial Analysis' own measurement on its current revision; prices are each vendor's published rate card per million tokens. Anything labelled vendor-reported is Meta's, from Meta's harness.

• Intelligence Index — Claude Fable 5.1 53 (max effort); Muse Wonder 52 (max). One point apart on the same revision of the same board.

• Input price — Claude Fable 5.1 $10.00 per million; Muse Wonder $4.00. 2.5× the spend per input token.

• Output price — Claude Fable 5.1 $50.00 per million; Muse Wonder $20.00. Also 2.5×, and this is the line that dominates an agentic bill.

• Cached input — Claude Fable 5.1 $0.25 per million against Muse Wonder's $0.20. Both vendors advertise roughly 95–98% discounts, but in absolute money the two cached rates are five cents apart, which is the most consequential number on this page.

• Context and output ceiling — Fable 5.1 1,000,000 in and 128,000 out; Muse Wonder 1,048,576 in and 943,718 out. Effectively level on input, and not comparable at all on output.

• Modalities — Fable 5.1 takes text, image and file input; Muse Wonder takes text, image, speech and video. If your pipeline transcribes audio before it reasons, that is an architectural difference rather than a rounding error.

• Reasoning control — Fable 5.1 supports adaptive reasoning with a documented fallback configuration and a batch mode for asynchronous work; Muse Wonder's reasoning is mandatory, with an effort ladder from minimal to max defaulting to medium.

• Availability — Fable 5.1 is served across multiple API providers as well as the vendor's own; Muse Wonder is on Meta's API and inside Muse Code, with no third-party coverage yet.

Why the cache line decides more than the index line

Both vendors sell caching as an 85-to-95-percent discount off input, and that framing hides the thing that matters. What a cache read actually costs is the absolute rate, and there the two models are five cents apart: $0.20 per million on Muse Wonder against $0.25 on Claude Fable 5.1. Uncached, Fable 5.1's input is 2.5× Muse Wonder's. Cached, it is 1.25×.

So the 2.5× headline is really a statement about how much of your prompt is fresh. A workload built on a large stable prefix — a codebase in context, a long policy document, a fixed tool schema that never changes — spends most of its input tokens at the cached rate, and the effective gap between these two models collapses toward that five-cent difference. A workload of short independent calls with no reusable prefix has nothing to cache and pays the full 2.5× on every request. Same two models, same rate cards, completely different conclusion, and the deciding variable is the shape of your traffic rather than the model's quality.

Meta's own vendor-reported table covers Claude Fable 5.1 alongside the Muse Wonder series at maximum effort, and it also points the other way on one suite and back the other on others — Fable 5.1 at 62.1 on AutomationBench-AA against Muse Wonder's 60.5, 27.6 on JobBench against 30.8, 79.0 on Terminal-Bench 4.0-AA against 85.6. All vendor numbers, all unreproduced, and the only safe reading is that these two models are close enough on agentic work that a scoreboard should start the test and not end it.

Where the one-point gap is not the story

There is a real argument for paying 2.5× and it has little to do with the index. Fable 5.1's reasoning is adaptive with a documented fallback configuration, which means the model's thinking depth can be tuned against cost rather than being mandatory on every call. Muse Wonder's ladder has a floor — minimal — but no off switch, and thinking tokens bill at $20 per million. On high-volume, latency-sensitive traffic, a model that can decline to think is cheaper than a cheaper model that always thinks, and that comparison never appears on a leaderboard.

The second argument is provider breadth. Fable 5.1 being served by several providers means regional availability and latency competition, and an outage at one endpoint is an inconvenience rather than an incident. A one-day-old model with a single vendor path is a different risk posture, and gateways that adopt it in the next fortnight will often trail the vendor's parameter surface — the reasoning-effort enumeration in particular is the field that goes stale first after a launch.

The case for Muse Wonder at the lower price rests on three things that Fable 5.1 does not offer. The output ceiling is the largest of them: 943,718 tokens in one response against 128,000 is not a specification detail if you are generating long documents, whole modules of code, or a complete migration plan in a single turn, because the alternative is stitching outputs together yourself. Speech and video going in natively is the second. The third is simply the invoice — at $4 and $20 against $10 and $50, a team with no cacheable prefix and a lot of output can run roughly two and a half times the volume for the same money and lose one index point for it.

Running this comparison without three accounts

Claude Fable 5.1 is on OrcaRouter at the vendor's own list price — $10.00 per million input tokens, $50.00 per million output, and the $0.25 cache-read rate — with no markup added on our side and the 1M-token context window passed through unchanged. That makes it a one-key reference point for everything above.

Muse Wonder is not on OrcaRouter, and we will not imply otherwise: there is no meta/muse-wonder entry in our catalogue, and today the honest answer is Meta's own API and Muse Code. What we do carry from the same lab is Muse Spark 1.2 and Muse Spark 1.1, so the Muse family is reachable from the same key if you want Meta's reasoning lineage while the Wonder checkpoint is still settling.

The way to settle a 2.5× price question is not to read two rate cards, it is to run your own tasks twice and read the token counts. OrcaRouter routes across 200-plus models behind one OpenAI-compatible endpoint with provider list prices passed through unchanged, so the Fable 5.1 side of that test is available now at vendor rates, and the day a provider we route starts serving Muse Wonder the other half of the test becomes a model-name change rather than a new integration.

Which one to pick

• Pick Claude Fable 5.1 if your workload has a large stable prefix and would rather buy certainty: six weeks of independent measurement, several providers, a batch lane at half price, and adaptive reasoning you can turn down.

• Pick Muse Wonder if your traffic is output-heavy, uncacheable, and long-form — the 943,718-token output budget and the $20 output rate are both consequences of a model priced for exactly that, and speech and video input come with them.

• Do not pick between them on the one index point. A single point on a composite index is inside the noise of most real workloads, and it is not worth 2.5× unless something else on this page is doing the work.

• Run the cache test before you decide. If more than half your input tokens hit the cache in production, the two models are closer than their rate cards suggest and the decision belongs to capability, modality and provider risk instead.

One point of measured capability, two and a half times the list price, and a cached-input line that quietly closes most of the gap. This is a matchup that a leaderboard genuinely cannot settle — which is why the number worth trusting here is one you produce yourself.