Muse Spark 1.3 vs Claude Opus 5
Meta's coding model is a quarter of Opus 5's input price and, on Meta's own table, narrowly ahead on coding. Read the data terms before you switch.
Updated September 4, 2026 · Independent comparison — Muse Spark 1.3, Claude Opus 5 are separate products.
Muse Spark 1.3
Meta's coding model, co-trained with Muse Code
Muse Spark 1.3 is Meta's coding model, released 2026-09-02 and co-trained with the Muse Code harness — Meta's claim is that running it inside Muse Code uses fewer tokens and turns than driving it from a third-party harness. It carries a 1M-token context window with text, image and video input, and reasoning effort levels from none through ultra. Weights are closed. Pricing is the headline: $1.25 per million input tokens and $4.25 per million output on the standard endpoint, with a Contributor endpoint at roughly $0.10 / $0.20 where Meta trains on your data. One practical caveat: 1.3 emits roughly three times the tokens of 1.2, so the per-token saving is smaller in practice than the sticker suggests.
Claude Opus 5
Anthropic's default for complex agentic coding
Claude Opus 5 is Anthropic's default for complex agentic coding and enterprise work, released 2026-07-24 as a step-change over Opus 4.8. It carries a 1M-token context window, up to 128K output (up to 300K on the Batch API beta), thinking on by default, and the full effort ladder through max. At $5 / $25 per million tokens (cache read $0.50, batch 50% off) it supports zero-data-retention and a research-preview fast mode at up to 2.5x output speed. It runs on the Claude API, Bedrock, Vertex and Microsoft Foundry, plus Claude Code on Pro and Max — a deployment surface Muse Spark has no equivalent for.
Bottom line
On Meta's own published table Muse Spark 1.3 wins the coding rows — 88.8 against 86.7 on Terminal-Bench 2.1, 75.4 against 74.0 on DeepSWE v1.1 — and wins long context outright, while conceding tool use and computer use to Claude Opus 5. Those margins are narrow, vendor-run, and not yet independently verified. The margin that is not narrow is price: $1.25 / $4.25 per million tokens against $5 / $25, roughly a quarter of the input cost and a sixth of the output, with a Contributor endpoint an order of magnitude cheaper still if you let Meta train on your data. Opus 5 answers with things a benchmark does not measure — Bedrock, Vertex and Foundry deployment, zero-data-retention, a 300K-output batch mode, and a production track record. And note the accounting trap on Meta's side: 1.3 emits roughly three times the tokens of 1.2, so the real saving is smaller than the rate card implies.
Pricing (per 1M tokens)
| Feature | Muse Spark 1.3 | Claude Opus 5 |
|---|---|---|
| Input | $1.25 | $5.00 |
| Output | $4.25 | $25.00 |
| Cached input read | $0.15 | $0.50 |
| Discounted tier | Contributor endpoint: ~$0.10 in / ~$0.20 out — Meta trains on your data | Batch API at 50% off — no training rights given up |
| Effective cost caveat | 1.3 emits roughly 3x the tokens of 1.2 | None published |
Context & limits
| Feature | Muse Spark 1.3 | Claude Opus 5 |
|---|---|---|
| Context window | 1M tokens | 1M tokens |
| Max output tokens | 128K | 128K (up to 300K on Batch API beta) |
| Image input | ✓ | ✓ |
| Video input | ✓ | ✗ |
| Reasoning effort control | none through ultra, default high | Thinking on by default; effort low through max |
Meta-published benchmark table
| Feature | Muse Spark 1.3 | Claude Opus 5 |
|---|---|---|
| Terminal-Bench 2.1 | 88.8 | 86.7 |
| DeepSWE v1.1 (agentic coding) | 75.4 | 74.0 |
| JobBench (tool use) | 64.9 | 65.7 |
| OSWorld 2.0 (computer use) | 66.9 | 68.3 |
| MRCR 512K-1M (long context) | 98.1 | Not in Meta's table |
| Independently verified head-to-head | None published yet | None published yet |
Access & deployment
| Feature | Muse Spark 1.3 | Claude Opus 5 |
|---|---|---|
| Open weights | ✗ | ✗ |
| Where you can run it | Muse Code, or the Meta Model API directly | Claude API, Bedrock, Vertex, Microsoft Foundry; Claude Code on Pro and Max; OpenCode Zen |
| Cloud marketplace availability | ✗ | AWS, Google Cloud and Azure |
| Co-trained with its own agent harness | Yes — with Muse Code | ✗ |
| Zero-data-retention option | Not published | ✓ |
| Fast or premium-speed mode | Not published | Fast mode: up to 2.5x output speed |
Best fit
| Feature | Muse Spark 1.3 | Claude Opus 5 |
|---|---|---|
| Strongest at | Long-horizon terminal coding and very long context, at a quarter of the input price | Complex agentic work, tool use and computer use, on enterprise infrastructure |
| Weakest at | Tool use and computer use, on Meta's own numbers; no enterprise deployment path | Cost — 4x the input and roughly 6x the output price |
The Verdict
Choose Muse Spark 1.3 if...
- ✓Token cost is the binding constraint on your workload
- ✓You are running long-horizon terminal coding tasks inside Muse Code
- ✓You need very long context, where Meta reports its widest margin
- ✓You want video as well as image input
- ✓You are comfortable that the cheapest tier pays for itself with training rights
Choose Claude Opus 5 if...
- ✓You need Bedrock, Vertex or Microsoft Foundry deployment
- ✓You need a zero-data-retention guarantee
- ✓Tool use and computer use matter more than raw coding score
- ✓You want up to 300K output on the Batch API for very long generations
- ✓You want a fast mode for up to 2.5x output speed when latency matters
- ✓You would rather run a model with a year of production track record
Frequently Asked Questions
Is Muse Spark 1.3 better than Claude Opus 5?
At coding, on Meta's own table, narrowly — 88.8 vs 86.7 on Terminal-Bench 2.1 and 75.4 vs 74.0 on DeepSWE v1.1, plus a clear lead on long-context retrieval. Opus 5 leads on JobBench tool use (65.7 vs 64.9) and OSWorld 2.0 computer use (68.3 vs 66.9). Every one of those figures is vendor-published on a model days old; there is no independently verified head-to-head yet, so treat them as a starting hypothesis rather than a result.
How much cheaper is Muse Spark 1.3?
Roughly 4x cheaper on input ($1.25 vs $5.00 per million tokens) and roughly 6x on output ($4.25 vs $25.00). The Contributor endpoint drops that to about $0.10 / $0.20, but Meta trains on your inputs and outputs at that price. Offset the headline saving against the fact that 1.3 emits roughly three times the tokens of 1.2.
Does Meta train on data sent to Muse Spark?
Not on the standard endpoint. The Contributor endpoint is where the order-of-magnitude discount lives, and that discount is explicitly paid for with training rights over your inputs and outputs. Check which endpoint your key bills against before sending proprietary code.
Where can I run each model?
Muse Spark 1.3 runs through Muse Code or directly on the Meta Model API — there is no cloud-marketplace path. Claude Opus 5 runs on the Claude API, AWS Bedrock, Google Vertex and Microsoft Foundry, inside Claude Code on Pro and Max, and through OpenCode Zen. For anyone with a procurement process, that difference usually decides it.
Does Muse Spark 1.3 have open weights?
No. Muse Spark 1.3 is closed-weights, as is Claude Opus 5. Meta has open-sourced other models in the Muse family, but Spark 1.3 is not among them.
Does Muse Spark work outside Muse Code?
Yes, via the Meta Model API, which is OpenAI SDK-compatible. But Meta co-trained the model with the Muse Code harness and reports that running it inside Muse Code uses fewer tokens and turns than a third-party harness, so a like-for-like comparison run through another agent may understate it.
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