GLM 5.3 FlashX vs Muse Spark Open
GLM 5.3 FlashX costs 3.4x less per output token than Muse Spark Open ($1.25 vs $4.25 per million). Updated October 21, 2026; no benchmark has tested both models yet.
- Coding
- No data
- Overall
- No data
- Output $/M
- $1.25
- Coding
- 47.4
- Overall
- 44.9
- Output $/M
- $4.25
GLM 5.3 FlashX or Muse Spark Open: which to pick
Only Muse Spark Open has a coding score, 47.4 on the Vibe Coding Index; GLM 5.3 FlashX has none, so the two cannot be ranked on coding.
Pick GLM 5.3 FlashX for output tokens 3.4x cheaper ($1.25 vs $4.25 per million).
No benchmark has tested both yet. GLM 5.3 FlashX has none yet; Muse Spark Open on LiveBench coding, LMArena WebDev and Terminal-Bench 4 (Vals AI). 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, 1317.
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
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
GLM 5.3 FlashX
GLM 5.3 FlashX $0.0010, Muse Spark Open $0.0034 per turn.
List prices
At a glance
- Coding index
- GLM 5.3 FlashX not benchmarked, Muse Spark Open 47.4 from 4 benchmarks.
- 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
- GLM 5.3 FlashX $1.25 against Muse Spark Open $4.25 per million output tokens, 3.4x apart.
- Context window
- Both take 1.05M tokens.
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 | GLM 5.3 FlashX | Muse Spark Open | Leader |
|---|---|---|---|
| LiveBench coding | Not measured | 73.6% | Only Muse Spark Open measured |
| LMArena WebDev | Not measured | 1528 | Only Muse Spark Open measured |
| Terminal-Bench 4 (Vals AI) | Not measured | 6.6% | Only Muse Spark Open measured |
| Vibe Code Bench (Vals AI) | Not measured | 76.2% | Only Muse Spark Open measured |
| Code migration (Vals AI) | Not measured | 21.2% | Only Muse Spark Open measured |
| SciCode | Not measured | 58.4% | Only Muse Spark Open measured |
| ALE-Bench | Not measured | 1590.1 | Only Muse Spark Open measured |
| LMArena WebDev: React | Not measured | 1529 | Only Muse Spark Open measured |
| LMArena WebDev: HTML | Not measured | 1495 | 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 | GLM 5.3 FlashX | Muse Spark Open | Leader |
|---|---|---|---|
| Epoch Capabilities Index | Not measured | 155.1 | 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 | GLM 5.3 FlashX | Muse Spark Open | Leader |
|---|---|---|---|
| LiveBench research | Not measured | 80.3% | Only Muse Spark Open measured |
| LiveBench browser | Not measured | 36.0% | Only Muse Spark Open measured |
| LiveBench long agentic | Not measured | 18.9% | Only Muse Spark Open measured |
| Finance Agent (Vals AI) | Not measured | 61.3% | Only Muse Spark Open measured |
| Tax Agent Bench (Vals AI) | Not measured | 26.3% | Only Muse Spark Open measured |
| Legal Research Bench (Vals AI) | Not measured | 38.5% | Only Muse Spark Open measured |
| Harvey's Legal Agent Benchmark (Vals AI) | Not measured | 25.0% | Only Muse Spark Open measured |
| Excel Modeling Benchmark (Vals AI) | Not measured | 53.7% | Only Muse Spark Open measured |
| APEX-Agents | Not measured | 33.4% | 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 | GLM 5.3 FlashX | Muse Spark Open | Leader |
|---|---|---|---|
| LiveBench reasoning | Not measured | 73.7% | Only Muse Spark Open measured |
| GPQA Diamond (Artificial Analysis run) | Not measured | 89.0% | Only Muse Spark Open measured |
| Humanity's Last Exam (Artificial Analysis run) | Not measured | 43.9% | 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 | GLM 5.3 FlashX | Muse Spark Open | Leader |
|---|---|---|---|
| Design Arena: websites | Not measured | 1317 | Only Muse Spark Open measured |
| Design Arena: game dev | Not measured | 1294 | Only Muse Spark Open measured |
| LiveBench design | Not measured | 60.3% | 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 | GLM 5.3 FlashX | Muse Spark Open | Leader |
|---|---|---|---|
| Vals Index | Not measured | 48.6% | Only Muse Spark Open measured |
| LiveBench data analysis | Not measured | 60.2% | Only Muse Spark Open measured |
| Long context reasoning (AA-LCR) | Not measured | 78.3% | 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
GLM 5.3 FlashX costs less
Repository review
50K input + 3K output tokens
GLM 5.3 FlashX costs less
Agent loop
200K input + 10K output tokens
GLM 5.3 FlashX 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 | Z.ai GLM 5.3 FlashX | Meta Muse Spark Open |
|---|---|---|
| Maker | Z.ai | Meta |
| Weights | No public weights listed | Open weights |
| Released | September 18, 2026 | October 15, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $0.37 | $1.25 |
| Output $/Mtok | $1.25 | $4.25 |
| Coding index | Not benchmarked | 47.4 |
| Independent measurements behind it | 0 | 4 |
| Cost per solved task | Not computable | Not computable |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5.3 FlashX better than Muse Spark Open for coding?
Only Muse Spark Open has a coding score, 47.4 on the Vibe Coding Index; GLM 5.3 FlashX has none, so the two cannot be ranked on coding. Pick GLM 5.3 FlashX for output tokens 3.4x cheaper ($1.25 vs $4.25 per million).
Which is cheaper, GLM 5.3 FlashX or Muse Spark Open?
GLM 5.3 FlashX costs $0.37 per million input tokens and $1.25 per million output tokens; Muse Spark Open costs $1.25 and $4.25. Cost per solved task is known for neither of them.
Which has the bigger context window, GLM 5.3 FlashX or Muse Spark Open?
Neither: both take 1.05M tokens.
Has any benchmark tested both GLM 5.3 FlashX and Muse Spark Open?
No benchmark has tested both yet. GLM 5.3 FlashX has none yet; Muse Spark Open on LiveBench coding, LMArena WebDev and Terminal-Bench 4 (Vals AI). Compare them on price and context instead. Data as of October 21, 2026.