MetaMuse Spark Open 816B A42B
Muse Spark Open 816B A42B is a Meta open-weights reasoning model, released 15 Oct 2026. Its best configuration (xhigh reasoning effort) ranks #152 of 775 on the BenchLeader Index at 58.6 ±6.0, in the upper half. The ± is the point: 281 other configurations score within that range, so they and this one cannot be told apart on quality alone — price and speed are what separate them. It scores highest in coding (66) and lowest in maths (60). At $2.00 per million tokens blended it is pricier than most ranked models. It has been measured at 2 reasoning-effort settings; this summary describes the best-scoring one, and the tabs above switch between them. Last measured 15 Oct 2026.
- Blended price
- $2.00/M
- $1.25 in · $4.25 out
- Output speed
- –
- First answer
- –
- Context
- 1.0M
- Full answer
- –
- Cost per run
- –
- Released
- 15 Oct 2026
- Overall index59
- Reasoning64
- Coding66
- Maths60
- Knowledge62
Reasoning-effort configurations
The same model behaves differently depending on how much it is allowed to think. Each row is one setting, scored only on the benchmarks that were run at that setting. “Not stated” collects results from publishers that did not say which setting they used; for a reasoning model that is usually its thinking mode, but we do not assume it. Pick a setting here or at the top of the page to see its price, speed and category scores.
| Effort | Index | Rank | Speed | First answer | Chat reply cost | Categories |
|---|---|---|---|---|---|---|
| xhighbest | 58.6 | #152 | – | – | $0.0018 | Coding 66 · Knowledge 62 · Maths 60 · Reasoning 64 |
| not stated | – | – | – | – | $0.0018 | Agents & tools 32 |
How its index has moved
17 Oct 2026 to 20 Oct 2026The index is recomputed from scratch every day, so a line moves when a new benchmark result lands, when a publisher revises a score, or when the models it is normalised against change. Early movement usually means the score is still settling.
Benchmark results
See all LLM benchmarks. One column per reasoning effort. Rank is among every configuration of every model on that benchmark. Hover a score for the run it came from.
Reasoning
| Benchmark | xhigh | Source |
|---|---|---|
| GPQA Diamond | 88.6%#57 | Epoch AI Benchmarking Hub |
Coding
| Benchmark | xhigh | Source |
|---|---|---|
| SciCode | 58.5%#23 | SciCode |
| ALE-Benchnot in index | 1590.1#18 | Epoch AI Benchmarking Hub |
Agents & tools
| Benchmark | not stated | Source |
|---|---|---|
| APEX-Agents | 33.4%#47 | Mercor |
Maths
| Benchmark | xhigh | Source |
|---|---|---|
| FrontierMath Tiers 1–3 | 69.8%#28 | Epoch AI Benchmarking Hub |
| FrontierMath Tier 4 | 31.7%#35 | Epoch AI Benchmarking Hub |
| OTIS Mock AIME | 98.1%#27 | Epoch AI Benchmarking Hub |
Knowledge
| Benchmark | xhigh | Source |
|---|---|---|
| SimpleQA Verified | 56.6%#19 | Epoch AI Benchmarking Hub |
What a task costs
Estimates from list price, output speed and time to first answer for the best configuration. “With caching” assumes three-quarters of the input is served from the prompt cache at $0.150 per 1M. Reasoning tokens are not modelled.
| Workload | Tokens in / out | Cost | With caching | Time |
|---|---|---|---|---|
| Chat reply | 400 / 300 | $0.0018 | $0.0014 | – |
| Summarize a 30-page report | 12,000 / 600 | $0.018 | $0.0077 | – |
| Code edit | 6,000 / 1,500 | $0.014 | $0.0089 | – |
| Agentic coding session | 60,000 / 4,000 | $0.092 | $0.043 | – |
| Structured extraction | 2,000 / 200 | $0.0034 | $0.0017 | – |
See also
Data as of 21 Oct 2026. Compare these configurations.
Cite as: BenchLeader, “Muse Spark Open 816B A42B: benchmarks, pricing, speed and rank”, https://www.benchleader.com/models/muse-spark-open-816b-a42b, data as of 21 Oct 2026.