Ett hero-titelkort för en jämförelse av Muse Spark 1.3 och Claude Opus 5.5, med titeln "Muse Spark vs Claude Opus 5.5" och undertexten "Tio indexpoäng, eller en 3,7 gånger så hög faktura". Två kort sitter på varsin sida om en avdelare: det vänstra är märkt Muse Spark 1.3 och visar "48 Intelligence Index"; det högra är märkt Claude Opus 5.5 och visar "58 Intelligence Index". En underrad nedanför lyder "$1.60 vs $5.98 per slutförd uppgift". OrcaRouter-logotyp komponerad i nedre högra hörnet.
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Muse Spark vs Claude Opus 5.5: Tio intelligenspoäng och en 3,7x faktura

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Magnus Corvin

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Benchmarks: Artificial Analysis · uppdateras dagligen
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The comparison between Muse Spark and Claude Opus 5.5 is usually written as a scoreboard, and the scoreboard does have a winner: on Artificial Analysis' Intelligence Index the current Muse Spark — Muse Spark 1.3 at its max reasoning setting — scores 48, while Claude Opus 5.5 at max effort with default fallback scores 58 and sits first on the board. That is the number everyone quotes. The number almost nobody quotes sits on the same page: completing one Intelligence Index task costs $1.60 on Muse Spark 1.3 and $5.98 on O​pus 5.5. Ten index points for roughly 3.7x the money per task, with Muse Spark also running about 28% faster and emitting a third fewer tokens to get there. Neither of those figures is ours — both come from Artificial Analysis' own hosted listings — and which one matters depends entirely on what you are doing, so this piece is about separating the two questions rather than picking a side.

Först, det som modellnamnet döljer

Muse Spark is not one model, and the matchup only makes sense once you fix a version. The line runs Muse Spark 1.1 (July 16, 2026), Muse Spark 1.2 (August 5, 2026) and Muse Spark 1.3 (September 2, 2026), all from M​eta Superintelligence Labs, all sharing a 1,048,576-token context window and a text-out modality. M​eta labels 1.3 current. Muse Spark 1.3 also gained its "max" reasoning level on September 4, two days after launch, after M​eta finished additional safety testing — and that matters here because every AI-lab scorecard, M​eta's included, was produced at that setting, while the model most developers actually called for the first two days was capped at xhigh.

Claude Opus 5.5 arrived on September 22, 2026, the first release in A​nthropic's 5.5 family, and it is a simpler object: one GA model, adaptive thinking always on, effort selectable from low to max. A​nthropic's own framing was cost — it says O​pus 5.5 costs 40% less to run than Claude Opus 5, with input and output at $4 and $20 per million tokens and cache reads at $0.20, a 60% cut on cache reads versus its predecessor. Claude Fable 5.1 still sits above it for the hardest reasoning work.

Så den ärliga beskrivningen är en jämförelse mellan en modell som gång på gång riktas om under samma familjenamn och en modell som släpptes en gång i en fast konfiguration och inte har rört sig sedan dess.

De oberoende talen, med sin asterisk

Artificial Analysis är den enda tredje parten med offentliga listningar för båda, och den jämför dem inte i samma kategori – öppenviktsmodeller rankas mot öppenviktsmodeller i samma storleksklass, proprietära modeller mot det bredare fältet. Båda dessa är proprietära, så just den snedvridningen spelar ingen roll; det som spelar roll är att ingen av listningarna är en kontrollerad omkörning av den andras testramverk.

• Muse Spark 1.3 (max) — Intelligensindex 48, rang 24 av 217; utdatastighet 121,9 tokens/sekund; $1,25 in / $4,25 ut per miljon tokens; $1,60 per indexuppgift; 170M utdatatokens genererade under indexet.

• Claude Opus 5.5 (max, standardreserv) — Intelligensindex 58, rang 1 av 217; utdatahastighet 95,2 tokens/sekund; $4,00 in / $20,00 ut; $5,98 per indexuppgift; 260 mn utdatatokens.

Read those two lists side by side and the shape of the trade is visible without any interpretation. O​pus 5.5 wins intelligence by 10 points and wins it while being more verbose, not less — 260M tokens against 170M — so it is not buying its score with economy. Muse Spark 1.3 is faster, cheaper per token, cheaper per completed task, and less talkative. On the price-per-task line is where the gap is widest: you can run roughly 3.7 Muse Spark 1.3 index tasks for the cost of one O​pus 5.5 index task.

A two-column scoreboard titled "Muse Spark 1.3 vs Claude Opus 5.5 — the scoreboard". The left column, Muse Spark 1.3, reads: Intelligence Index 48; list price in / out $1.25 / $4.25; cost per index task $1.60; output speed 121.9 tokens/s; context window 1M tokens; video input Yes. The right column, Claude Opus 5.5, reads: Intelligence Index 58; list price in / out $4.00 / $20.00; cost per index task $5.98; output speed 95.2 tokens/s; context window 1M tokens; video input No. A footer reads "Both rows measured by Artificial Analysis at max reasoning effort; no vendor figures used." OrcaRouter logo composited bottom-right.

Ännu en oberoende datapunkt, eftersom den pekar i motsatt riktning och är värd att nämna: LMArenas texttopplista placerar en Claude Opus 5.5-konfiguration på plats 3 totalt med 1508 i Elo, och Muse Spark 1.3 finns inte alls med på den listan. Röstning utifrån mänskliga preferenser och ett benchmarkindex är inte överens om storleken, vilket är normalt, men det betyder att gapet på 10 punkter inte ska läsas som "10 % sämre på allt".

Där gapet är som störst, enligt leverantörerna

Leverantörernas poängkort är inte jämförbara med varandra och ingen av leverantörerna publicerade samma riktmärken, men överlappningen är lärorik. Allt nedan är leverantörsrapporterat och har inte reproducerats av oss.

• Terminal-Bench 4.0 — O​pus 5.5: 66.4%, run at xhigh effort per A​nthropic's note. M​eta reports Muse Spark on Terminal-Bench 2.1 instead, where the family's published score is 76.4 with the Terminus 2 agent. Different benchmark versions, different agents — do not subtract them.

• GDPval-AA — O​pus 5.5: 1846 Elo on v2.1. Muse Spark 1.3: 1,754 on v2. The version moved between the two measurements, so the 92-point gap is directionally real and numerically soft.

• Agentic computer use — O​pus 5.5: 81.8% on OSWorld 2.1, marked "partial". Muse Spark 1.3: 66.9 on OSWorld 2.0. Again, different revisions of the same benchmark family.

• Terminal-Bench-Science 0.1 — O​pus 5.5: 58.7%. M​eta publishes no equivalent for Muse Spark 1.3.

A​nthropic is unusually explicit about the limits of its own table, noting that at this level of capability "benchmark margins have become a less reliable guide to real-world differences". That sentence is worth taking at face value in both directions: it undercuts the 10-point AA gap as much as it undercuts M​eta's DeepSWE placement claims.

Screenshot of the Artificial Analysis page for Claude Opus 5.5, labelled "Anthropic — Claude Opus 5.5 - max - Proprietary model - Released September 2026" and headed "Claude Opus 5.5 (Max, Default Fallback) Intelligence, Performance & Price Analysis". Visible figures: Intelligence Index 58 at rank 1 of 217; speed rank 5 of 186 at 95 tokens per second; $4.00 input and $20.00 output per million tokens; $5.98 per task; 260M output tokens against a median of 87M; and the summary sentence that the model supports text and image input and outputs text with a 1M token context window.

Vad du ger upp förutom poängen

• Indatamodaliteter — Muse Spark 1.3 tar emot text, bild och video. Claude Opus 5.5 tar emot text och bild. Om din pipeline matar skärminspelningar eller video direkt in i modellen är detta inte ett svårt val och indexgapet är irrelevant.

• Maximum output — O​pus 5.5 returns up to 128K tokens synchronously, and 300K through the Batches API behind a beta header. M​eta does not publish a max-output figure for Muse Spark 1.3 that we could verify. If you generate long artifacts in a single call, an unpublished ceiling is a risk you should test rather than assume.

• Cache economics — O​pus 5.5's cache read is $0.20 per million, a 95% discount off input. Muse Spark 1.3's is $0.15, an 88% discount. For a heavily cached agent loop this narrows or inverts the per-task arithmetic versus the headline rates, and it is the single easiest thing to get wrong when comparing these two on list price alone.

• Kontext — båda är 1M. Inget att separera.

• Release cadence — O​pus 5.5 is one model with one price and has not changed since September. Muse Spark has re-pointed three times in three months and then added a reasoning level on top. That is either healthy iteration or an integration hazard, depending on how much you like re-running evals.

Kör båda utan en andra integration

Both sides of this comparison are on OrcaRouter — Claude Opus 5.5 and the two Muse Spark checkpoints we serve, Muse Spark 1.2 and Muse Spark 1.1 — through one API across 200+ models, at each provider's list price with 0% markup passed through. Which is the practical answer to the question this article poses: the way to find out whether your workload really needs the extra ten index points is to route a slice of production traffic to Muse Spark 1.2 at $1.25 in / $4.25 out and compare it against the same prompts on O​pus 5.5, on the same key, with automatic failover so a bad run degrades to the other model rather than to an error page. No second contract, no second SDK, no migration.

Screenshot of the OrcaRouter model catalogue at orcarouter.ai/models, headed "Models / 210 models - 16 providers - one API key, one bill", with a filter sidebar (input modalities, context length, input price, API docs, status, access tier, series, supported parameters), modality tabs, a sort control, a "How to call any model" panel showing POST https://api.orcarouter.ai/v1/chat/completions with a model id and a messages payload, credit tiers from $50 to $1000, and model cards including OrcaCyber Zero 1.5, Claude Sonnet 5.5 and GPT-6.1 Sol.

Two honest caveats about our own coverage. Muse Spark 1.3 is not on our catalogue today, so the routing comparison above starts from 1.2, which is the checkpoint Artificial Analysis measures one point below Muse Spark Open and which now carries a deprecation notice pointing at 1.3. And this comparison rests on A​nthropic's and M​eta's published figures plus Artificial Analysis' independent listings; we have not re-run either model's benchmarks, and the vendor rows above should be read as claims.

Versionen värd att återvända till

If the question you brought here is "is the cheap one good enough", the honest answer today is that the cheap one is 48 to O​pus 5.5's 58, faster, less verbose and about 3.7x cheaper per completed task — and that A​nthropic's own caveat about benchmark margins is the strongest argument for testing rather than deciding. If your work involves video in, extremely long single outputs, or the last few points of hard reasoning, O​pus 5.5 is the model that shipped with those things documented. The thing to watch is not the next Muse Spark version number but whether Muse Spark 1.3 arrives on a router you already use, and at what price — the family's pricing has been stable at $1.25 / $4.25 across 1.1, 1.2 and 1.3, which is itself a signal that M​eta is competing on capability per dollar rather than on the dollar.

One development belongs outside this matchup rather than inside it, and it is the reason this family is being written about this week at all. On October 15, 2026 — thirteen days after Muse Spark 1.3 shipped and the day before this article — M​eta published the weights and licence for Muse Spark Open, the family's separate open-weight member, whose repository had been sitting gated and unannounced since September 15. The 816B-total / 42B-active architecture currently circulating is that release, not the closed 1.3 measured above. Artificial Analysis does list it, at an intelligence index of 39 against the 48 this article attributes to Muse Spark 1.3, and M​eta has not published the evaluation report behind its own scorecard for it. So the artefact is confirmed and the performance claim is not; do not read this comparison as covering it.

Vad siffrorna inte kan berätta för dig är huruvida något av det har gått fel i fält: de dokumenterade AI-incidenterna och agentfelen kring modeller i den här klassen samlas i OrcaRouter AI Incident Archive, där varje post har sina egna källor, allvarlighetsgrad, konfidensgrad och omtvistad flagga.

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