Muse Wonder vs Claude Opus 5.5: Same Price, Different Jobs

Muse Wonder and Claude Opus 5.5 have identical first-party API pricing: $4 per million input tokens, $20 per million output tokens, and $0.20 per million cached input tokens. Both expose a 1M-token context window. That removes price from the initial comparison and leaves a simpler question: which model does the work better? On Artificial Analysis’ independent index, Opus 5.5 scores 58 versus Wonder’s 52. On Meta’s agentic benchmarks, Wonder Full leads some long-running coding and legal tasks, while the API-available Wonder also beats Opus on SWE-Marathon. Artificial Analysis measured Wonder at $4.52 per index task versus $5.98 for Opus.

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This comparison covers specifications, benchmarks, per-task cost, tooling, data terms, and practical model selection. For a standalone introduction to Meta’s model, see the Muse Wonder explainer.

Specs

	Muse Wonder	Claude Opus 5.5
Model ID	muse-wonder-1.0	claude-opus-5-5
Input / output / cached per 1M	$4 / $20 / $0.20	$4 / $20 / $0.20 cache read
Context	1M tokens	1M tokens
Inputs	Text, image, video, audio	Text, image, PDF
API formats	Responses, Chat Completions, Messages	Messages, plus an OpenAI-compatible endpoint
Reasoning control	effort from minimal to max; always reasons	effort levels; extended thinking
First-party rate limits	3,000 RPM and 4M TPM per team	Tiered by spend
Larger sibling	Muse Wonder Full, available only in Muse Code	None
Weights	Closed	Closed

Two distinctions matter before benchmarks. Wonder accepts video and audio natively; Opus does not. Opus is Anthropic’s strongest model, while Wonder is the smaller of Meta’s two models. When Meta publishes charts showing a win over Opus, check whether the result belongs to Wonder or Wonder Full.

Benchmarks: Meta’s table

Meta’s model card reports the following results at maximum effort for the API-available Muse Wonder and Claude Opus 5.5:

Benchmark	Muse Wonder	Claude Opus 5.5	Winner
Artificial Analysis Intelligence Index	52	58	Opus 5.5
Harvey LAB-AA, legal	10.0	4.2	Wonder
AutomationBench-AA	39.1	41.2	Opus 5.5
JobBench	70.5	75.4	Opus 5.5
DeepSWE 1.1	78.8	74.2	Wonder
SWE-Marathon	53.1	46.3	Wonder
Terminal-Bench 4.0-AA	52.0	59.6	Opus 5.5
HealthBench Pro	60.5	65.6	Opus 5.5

Opus wins five of eight rows on Meta’s own table. Wonder wins both software-engineering benchmarks and the legal benchmark. Its 6.8-point SWE-Marathon lead is the most relevant signal for long-running coding agents that need to continue through many steps and blockers.

Benchmarks: the independent view

Artificial Analysis tested both models at maximum effort:

Measure	Muse Wonder	Claude Opus 5.5
Intelligence Index v4.3	52	58
AA-Omniscience, knowledge	25	46
Hallucination rate	27%	Not in the same table
GDPval-AA, Elo	n/a; Wonder Full scored 1857	1866
Coding Agents Index	63	66 with Claude Code
Output tokens per index task	~54,000	Not stated
Cost per index task	$4.52	$5.98

The knowledge gap is the largest difference in either direction: Opus scores 46 versus Wonder’s 25 on AA-Omniscience. Retrieval-heavy applications should therefore treat grounding as mandatory for Wonder, while Opus may need less retrieval support for some factual workflows. On coding agents, Claude Code with Opus scores 66 versus 63 for Wonder; Wonder Full reaches 68, but it has no API.

Cost per task, not per token

The rate cards are identical, but actual bills differ. Artificial Analysis measured Wonder at $4.52 per index task and Opus at $5.98. Wonder’s profile is cache-heavy: only $1.08 of its $4.52 came from output tokens, while $3.43 came from input, mostly cache writes and reads. Opus spent proportionally more on output.

Use the workload, not the token price, to decide:

• Long agentic loops with a stable prefix: Wonder’s cache-heavy profile can be advantageous because cached input costs $0.20 per million tokens.
• Short prompts with long generated answers: Output volume dominates, so the effective gap narrows.
• Any production workload: Inspect usage on every response and calculate cost from your own traffic.

A simple cost calculation for either model is:

cost = (input_tokens × 4 / 1_000_000)
     + (output_tokens × 20 / 1_000_000)
     + (cached_input_tokens × 0.20 / 1_000_000)

The Opus 5.5 caching math and Muse Wonder pricing posts walk through detailed examples.

Tooling and ecosystem

Claude Opus 5.5 has the broader ecosystem: Claude Code, the Agent SDK, Managed Agents, Amazon Bedrock, Google Cloud, Microsoft Foundry, and substantial third-party integration support. Its 18-hour task API design is particularly relevant for long-horizon agents.

Muse Wonder launched on October 12, 2026, so its ecosystem is still new. It supports Meta’s API with three request formats, Muse Code, Vercel AI Gateway, and Cloudflare Workers AI. Meta’s documentation explains how to point Claude Code and Codex at api.meta.ai, making it straightforward to test existing agent harnesses against Wonder. However, Meta does not yet offer an equivalent of Managed Agents. Its zero-data-retention mode also disables server-side state, background requests, file uploads, and web search.

Muse Code also had a launch-week quota-drain bug, which Meta fixed the same day. Treat the ecosystem as promising but early.

Safety and data

Both vendors recommend human confirmation before consequential agent actions. Meta trained Wonder to check in before important actions and avoid sharing private information without permission. Its full safety report was still pending, and Meta could not rule out high-risk chemical and biological capabilities without safeguards.

Anthropic publishes system cards at launch. Its reported 85% prompt-injection resistance figure is covered in more detail in the Opus 5.5 prompt injection analysis.

Data handling also differs. Meta’s API Standard mode does not train on customer traffic, but Muse Code subscriptions default to Contributor mode, which does. Anthropic does not train on API traffic by default.

Which model should get which job?

Job	Better pick	Why
Long-running coding agents with many steps and blockers	Try Wonder	SWE-Marathon: 53.1 versus 46.3; cache-heavy cost profile
Legal document agents	Try Wonder	Harvey LAB: 10.0 versus 4.2
Factual Q&A and research assistants	Opus 5.5	AA-Omniscience: 46 versus 25
Terminal and DevOps agents	Opus 5.5	Terminal-Bench: 59.6 versus 52.0
Health and professional advice	Opus 5.5	HealthBench Pro: 65.6 versus 60.5
Video or audio input	Wonder	Opus does not accept them
Workloads requiring Bedrock, Google Cloud, or Foundry	Opus 5.5	Wonder is available first-party, through Vercel, and through Cloudflare
Interactive coding with the strongest available model	Opus through the API, or Wonder Full through Muse Code	Wonder Full is subscription-only

The practical conclusion is straightforward: Opus 5.5 is the stronger general model and the safer default. Wonder is worth testing for long agentic tool-using workloads, legal document tasks, and applications that need native video or audio input.

Run the comparison in Apidog

Because Wonder supports OpenAI-style and Anthropic-style interfaces and Opus supports Anthropic Messages plus an OpenAI-compatible endpoint, one [Apidog](https://apid - Meta: base_url = https://api.meta.ai/v1

• Anthropic: use Anthropic’s Messages base URL
  1. Store each API key as a secret environment variable.
  2. Build one Responses request for Wonder use the response usage fields directly:

const usage = pm.response.json().usage;

const inputCost = (usage.input_tokens ?? 0) * 4 / 1_000_000;
const outputCost = (usage.output_tokens ?? 0) * 20 / 1_000_000;
const cacheCost = (usage.cached_input_tokens ?? 0) * 0.20 / 1_000_000;

pm.collectionVariables.set("run_cost_usd", inputCost + outputCost + cacheCost);

Adjust the usage field names if a provider returns cache details in a nested object. Ten representative tasks from your own workload will provide more useful evidence than either vendor’s benchmark table. Download Apidog to run the models side by side.

Frequently asked questions

Is### Are Muse Wonder and Claude Opus 5.5 the same price?

Yes, on list price: $4 per million input tokens, $20 per million output tokens, and $0.20 per million cached input tokens. Per index task, Artificial Analysis measured Wonder at $4.52 and Opus at $5.98.

Which model is better for Claude Code?

Claude Code was built for Claude. It can also target Wonder through Meta’s Messages endpoint. In the Coding Agents Index, Claude Code with Opus scores 66 versus 63 for Wonder. Wonder Full closes the gap, but it has no API and is available only through Muse Code.

Does Muse Wonder Full change the recommendation?

It changes the benchmark picture: Wonder Full scores 56 on the index and leads most agentic rows. Operationally, it only matters if you can work inside Muse Code because Full cannot be deployed through the API.

Next step

Select your longest representative agent task, run it through both models at your intended effort level, and compare intervention frequency, output quality, completion rate, and usage. Since list price is identical, let task performance and actual token consumption decide.