Muse Spark Open vs Perceptron Mk1.5
Perceptron Mk1.5 costs 2.8x less per output token than Muse Spark Open ($1.50 vs $4.25 per million). Updated October 22, 2026; no benchmark has tested both models yet.
- Coding
- 47.4
- Overall
- 44.9
- Output $/M
- $4.25
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.50
Muse Spark Open or Perceptron Mk1.5: which to pick
Only Muse Spark Open has a coding score, 47.4 on the Vibe Coding Index; Perceptron Mk1.5 has none, so the two cannot be ranked on coding.
Pick Perceptron Mk1.5 for output tokens 2.8x cheaper ($1.50 vs $4.25 per million).
No benchmark has tested both yet. Muse Spark Open has results on LiveBench coding, LMArena WebDev and Terminal-Bench 4 (Vals AI); Perceptron Mk1.5 has none yet. Compare them on price and context instead.
Which one for your work
Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Only Muse Spark Open has a coding score, so no call is made.
One side not measured
Web design
Design Arena: websites
No call
Only Muse Spark Open has a Design Arena: websites result, 1310.
Directional only
General
Vals Index
No call
Only Muse Spark Open has a Vals Index result, 48.6%.
Directional only
Long documents
Listed context window
Muse Spark Open
Muse Spark Open takes 1.05M tokens against 37K.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Perceptron Mk1.5
Muse Spark Open $0.0034, Perceptron Mk1.5 $0.0009 per turn.
List prices
At a glance
- Coding index
- Muse Spark Open 47.4 from 4 benchmarks, Perceptron Mk1.5 not benchmarked.
- Widest category
- None yet: no category has been tested on both models.
- Widest single gap
- None yet: no benchmark has tested both models.
- Output price
- Muse Spark Open $4.25 against Perceptron Mk1.5 $1.50 per million output tokens, 2.8x apart.
- Context window
- Muse Spark Open takes 1.05M tokens, Perceptron Mk1.5 37K.
Benchmark by benchmark
Every board either model has a result on, a category to a fold; bars are each result on a 0 to 100 scale. Only one model is measured on each, so no row names a leader.
CodingDirectional onlySix of these boards feed the Vibe Coding Index9 boards measured
| Benchmark | Muse Spark Open | Perceptron Mk1.5 | Leader |
|---|---|---|---|
| LiveBench coding | 73.6% | Not measured | Only Muse Spark Open measured |
| LMArena WebDev | 1528 | Not measured | Only Muse Spark Open measured |
| Terminal-Bench 4 (Vals AI) | 6.6% | Not measured | Only Muse Spark Open measured |
| Vibe Code Bench (Vals AI) | 76.2% | Not measured | Only Muse Spark Open measured |
| Code migration (Vals AI) | 21.2% | Not measured | Only Muse Spark Open measured |
| SciCode | 58.4% | Not measured | Only Muse Spark Open measured |
| ALE-Bench | 1590.1 | Not measured | Only Muse Spark Open measured |
| LMArena WebDev: React | 1529 | Not measured | Only Muse Spark Open measured |
| LMArena WebDev: HTML | 1495 | Not measured | Only Muse Spark Open measured |
| Neither model has a result on the other 30 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board measured
| Benchmark | Muse Spark Open | Perceptron Mk1.5 | Leader |
|---|---|---|---|
| Epoch Capabilities Index | 155.1 | Not measured | Only Muse Spark Open measured |
| Neither model has a result on the other 1 board here | |||
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index9 boards measured
| Benchmark | Muse Spark Open | Perceptron Mk1.5 | Leader |
|---|---|---|---|
| LiveBench research | 80.3% | Not measured | Only Muse Spark Open measured |
| LiveBench browser | 36.0% | Not measured | Only Muse Spark Open measured |
| LiveBench long agentic | 18.9% | Not measured | Only Muse Spark Open measured |
| Finance Agent (Vals AI) | 61.3% | Not measured | Only Muse Spark Open measured |
| Tax Agent Bench (Vals AI) | 26.3% | Not measured | Only Muse Spark Open measured |
| Legal Research Bench (Vals AI) | 38.5% | Not measured | Only Muse Spark Open measured |
| Harvey's Legal Agent Benchmark (Vals AI) | 25.0% | Not measured | Only Muse Spark Open measured |
| Excel Modeling Benchmark (Vals AI) | 53.7% | Not measured | Only Muse Spark Open measured |
| APEX-Agents | 33.4% | Not measured | Only Muse Spark Open measured |
| Neither model has a result on the other 32 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Muse Spark Open | Perceptron Mk1.5 | Leader |
|---|---|---|---|
| LiveBench reasoning | 73.7% | Not measured | Only Muse Spark Open measured |
| GPQA Diamond (Artificial Analysis run) | 89.0% | Not measured | Only Muse Spark Open measured |
| Humanity's Last Exam (Artificial Analysis run) | 43.9% | Not measured | Only Muse Spark Open measured |
| Neither model has a result on the other 19 boards here | |||
Web designDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Muse Spark Open | Perceptron Mk1.5 | Leader |
|---|---|---|---|
| Design Arena: websites | 1310 | Not measured | Only Muse Spark Open measured |
| Design Arena: game dev | 1282 | Not measured | Only Muse Spark Open measured |
| LiveBench design | 60.3% | Not measured | Only Muse Spark Open measured |
| Neither model has a result on the other 6 boards here | |||
GeneralDirectional onlyPublic boards, shown as published, kept out of the index3 boards measured
| Benchmark | Muse Spark Open | Perceptron Mk1.5 | Leader |
|---|---|---|---|
| Vals Index | 48.6% | Not measured | Only Muse Spark Open measured |
| LiveBench data analysis | 60.2% | Not measured | Only Muse Spark Open measured |
| Long context reasoning (AA-LCR) | 78.3% | Not measured | Only Muse Spark Open measured |
| Neither model has a result on the other 43 boards here | |||
What each workload costs
Three fixed token mixes at each model's listed price, so per-token rates become a bill.
Chat turn
1K input + 500 output tokens
Perceptron Mk1.5 costs less
Repository review
50K input + 3K output tokens
Perceptron Mk1.5 costs less
Agent loop
200K input + 10K output tokens
Perceptron Mk1.5 costs less
Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.
Specification differences
The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.
| Specification | Meta Muse Spark Open | Perceptron Mk1.5 |
|---|---|---|
| Maker | Meta | Perceptron |
| Weights | Open weights | No public weights listed |
| Released | October 15, 2026 | September 25, 2026 |
| Context window | 1.05M | 37K |
| Input $/Mtok | $1.25 | $0.15 |
| Output $/Mtok | $4.25 | $1.50 |
| Coding index | 47.4 | Not benchmarked |
| Independent measurements behind it | 4 | 0 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Muse Spark Open better than Perceptron Mk1.5 for coding?
Only Muse Spark Open has a coding score, 47.4 on the Vibe Coding Index; Perceptron Mk1.5 has none, so the two cannot be ranked on coding. Pick Perceptron Mk1.5 for output tokens 2.8x cheaper ($1.50 vs $4.25 per million).
Which is cheaper, Muse Spark Open or Perceptron Mk1.5?
Muse Spark Open costs $1.25 per million input tokens and $4.25 per million output tokens; Perceptron Mk1.5 costs $0.15 and $1.50. Cost per solved task is known for neither of them.
Which has the bigger context window, Muse Spark Open or Perceptron Mk1.5?
Muse Spark Open, with 1.05M tokens against 37K.
Has any benchmark tested both Muse Spark Open and Perceptron Mk1.5?
No benchmark has tested both yet. Muse Spark Open has results on LiveBench coding, LMArena WebDev and Terminal-Bench 4 (Vals AI); Perceptron Mk1.5 has none yet. Compare them on price and context instead. Data as of October 22, 2026.