Muse Spark Open vs Beam 1.0 501B A23B
Updated October 21, 2026. 5 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.
Decision reading
Pick Muse Spark Open for coding: it scores 62.1 on the Vibe Coding Index against 33.8 for Beam 1.0 501B A23B.
Pick Beam 1.0 501B A23B when output tokens cost 4.3x less.
- Shared results
- 5
- Muse Spark Open only
- 21
- Beam 1.0 501B A23B only
- 23
- Like-for-like categories
- 2 of 9
Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.
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, four public coding benchmarks
Muse Spark Open
Muse Spark Open scores 62.1 against 33.8.
2 and 1 benchmarks behind the scores
Web design
Design Arena: websites
Muse Spark Open
Muse Spark Open leads, 1311 against 1253.
Same board, both measured
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Beam 1.0 501B A23B
Muse Spark Open $0.0034, Beam 1.0 501B A23B $0.0008 per turn.
List prices
At a glance
- Coding index
- Muse Spark Open 62.1 from 2 benchmarks, Beam 1.0 501B A23B 33.8 from 1 benchmark.
- Widest category
- Coding, 12.4 points apart on average over 3 shared benchmarks.
- Widest single gap
- LMArena WebDev: React: Muse Spark Open 1529 against Beam 1.0 501B A23B 1443, 14.5 points apart on a 0 to 100 scale.
- Output price
- Muse Spark Open $4.25 against Beam 1.0 501B A23B $1.00 per million output tokens, 4.3x apart.
- Context window
- Both take 1.05M tokens.
Benchmark by benchmark
First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.
| Category | Muse Spark Open | Bars | Beam 1.0 501B A23B | Ties |
|---|---|---|---|---|
| Coding | 3 | 0 | ||
| Web design | 2 | 0 | ||
| All shared boards | 5 | 0 |
CodingLike-for-likeFour of these boards feed the Vibe Coding Index30
| Benchmark | Muse Spark Open | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| LiveBench coding | 73.6% | Not measured | Only Muse Spark Open measured |
| LMArena WebDev | 1528 | 1437 | Muse Spark Open |
| 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 Text: coding | Not measured | 1473 | Only Beam 1.0 501B A23B measured |
| LMArena Text: software and IT | Not measured | 1461 | Only Beam 1.0 501B A23B measured |
| LMArena WebDev: React | 1529 | 1443 | Muse Spark Open |
| LMArena WebDev: HTML | 1495 | 1436 | Muse Spark Open |
| Neither model has a result on the other 27 boards here | |||
IntelligenceDirectional onlyPublic boards, shown as published, kept out of the index1 board, none shared
| Benchmark | Muse Spark Open | Beam 1.0 501B A23B | 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 index8 boards, none shared
| Benchmark | Muse Spark Open | Beam 1.0 501B A23B | 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 |
| 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 31 boards here | |||
ReasoningDirectional onlyPublic boards, shown as published, kept out of the index6 boards, none shared
| Benchmark | Muse Spark Open | Beam 1.0 501B A23B | 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 |
| LMArena Text: hard prompts | Not measured | 1442 | Only Beam 1.0 501B A23B measured |
| LMArena Text: expert | Not measured | 1447 | Only Beam 1.0 501B A23B measured |
| LMArena Text: hard prompts in English | Not measured | 1451 | Only Beam 1.0 501B A23B measured |
| Neither model has a result on the other 15 boards here | |||
MathDirectional onlyPublic boards, shown as published, kept out of the index2 boards, none shared
| Benchmark | Muse Spark Open | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| LMArena Text: math | Not measured | 1459 | Only Beam 1.0 501B A23B measured |
| LMArena Text: mathematical work | Not measured | 1475 | Only Beam 1.0 501B A23B measured |
| Neither model has a result on the other 11 boards here | |||
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
| Benchmark | Muse Spark Open | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| LMArena Text: science | Not measured | 1430 | Only Beam 1.0 501B A23B measured |
| LMArena Text: medicine and healthcare | Not measured | 1376 | Only Beam 1.0 501B A23B measured |
| LMArena Text: legal and government | Not measured | 1433 | Only Beam 1.0 501B A23B measured |
| LMArena Text: business and finance | Not measured | 1430 | Only Beam 1.0 501B A23B measured |
| Neither model has a result on the other 13 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | Muse Spark Open | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| Design Arena: websites | 1311 | 1253 | Muse Spark Open |
| Design Arena: game dev | 1290 | 1222 | Muse Spark Open |
| 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 index14 boards, none shared
| Benchmark | Muse Spark Open | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| 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 |
| LMArena Text | Not measured | 1425 | Only Beam 1.0 501B A23B measured |
| LMArena Text: instruction following | Not measured | 1430 | Only Beam 1.0 501B A23B measured |
| LMArena Text: creative writing | Not measured | 1390 | Only Beam 1.0 501B A23B measured |
| LMArena Text: English | Not measured | 1436 | Only Beam 1.0 501B A23B measured |
| LMArena Text: non-English | Not measured | 1413 | Only Beam 1.0 501B A23B measured |
| LMArena Text: Chinese | Not measured | 1424 | Only Beam 1.0 501B A23B measured |
| LMArena Text: French | Not measured | 1461 | Only Beam 1.0 501B A23B measured |
| LMArena Text: Russian | Not measured | 1412 | Only Beam 1.0 501B A23B measured |
| LMArena Text: multi-turn | Not measured | 1414 | Only Beam 1.0 501B A23B measured |
| LMArena Text: longer queries | Not measured | 1429 | Only Beam 1.0 501B A23B measured |
| LMArena Text: writing and language | Not measured | 1400 | Only Beam 1.0 501B A23B measured |
| LMArena Text: entertainment and media | Not measured | 1399 | Only Beam 1.0 501B A23B measured |
| Neither model has a result on the other 32 boards here | |||
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
| Benchmark | Muse Spark Open | Beam 1.0 501B A23B | Leader |
|---|---|---|---|
| Neither model has a result on 5 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
Beam 1.0 501B A23B costs less
Repository review
50K input + 3K output tokens
Beam 1.0 501B A23B costs less
Agent loop
200K input + 10K output tokens
Beam 1.0 501B A23B 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 | Reflection Beam 1.0 501B A23B |
|---|---|---|
| Maker | Meta | Reflection |
| Weights | Open weights | Open weights |
| Released | October 15, 2026 | October 16, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $1.25 | $0.30 |
| Output $/Mtok | $4.25 | $1.00 |
| Coding index | 62.1 | 33.8 |
| Independent measurements behind it | 2 | 1 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is Muse Spark Open better than Beam 1.0 501B A23B for coding?
Pick Muse Spark Open for coding: it scores 62.1 on the Vibe Coding Index against 33.8 for Beam 1.0 501B A23B. Pick Beam 1.0 501B A23B when output tokens cost 4.3x less.
Which is cheaper, Muse Spark Open or Beam 1.0 501B A23B?
Muse Spark Open costs $1.25 per million input tokens and $4.25 per million output tokens; Beam 1.0 501B A23B costs $0.30 and $1.00. Cost per solved task is known for neither of them.
Which has the bigger context window, Muse Spark Open or Beam 1.0 501B A23B?
Neither: both take 1.05M tokens.
How many benchmarks is the Muse Spark Open vs Beam 1.0 501B A23B comparison based on?
5 benchmarks have a result for both models as of October 21, 2026. Muse Spark Open's coding index rests on 2 independent benchmarks and Beam 1.0 501B A23B's on 1. Where only one model has a result, the page says so instead of naming a winner.