Model comparison
GLM-5.1 vs Muse Spark 1.2
Muse Spark 1.2 is the stronger model overall, scoring 49.8 to 47.6 on the Noometry Index.
Last verified . 22 shared benchmarks.
MetaSummary
- They share 22 benchmarks with published results for both. GLM-5.1 scores higher in 2 categories and Muse Spark 1.2 in 7 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Muse Spark 1.2 leads 50.4 to 38.2.
- The biggest single-benchmark swing is SimpleQA Verified: 34% for GLM-5.1 and 60.3% for Muse Spark 1.2.
- Muse Spark 1.2 is cheaper at $1.25 / $4.25 per million input/output tokens, against $1.40 / $4.40 for GLM-5.1.
- Muse Spark 1.2 accepts more context: 1.05M tokens versus 200K.
- GLM-5.1 has downloadable open weights; the other is API-only.
Side by side
| GLM-5.1 | Muse Spark 1.2 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 47.6 | 49.8 |
| Released | 2026-04-07 | 2026-08-05 |
| Weights | Open | Proprietary |
| Context window | 200K | 1.05M |
| Max output | 131K | 131K |
| Input $ / M tokens | $1.40 | $1.25 |
| Output $ / M tokens | $4.40 | $4.25 |
| Results tracked | 41 | 28 |
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Category by category
Coding Too close to call
GLM-5.1: 48.5 (#52), Muse Spark 1.2: 48.6 (#49)
| Benchmark | GLM-5.1 | Muse Spark 1.2 |
|---|---|---|
| LMArena WebDev | 1509 | 1532 |
| SciCode | 43.8% | 56.4% |
| WeirdML | 57.1% | 60.3% |
| LMArena Coding | 1486 | 1497 |
| SWE-bench Verified | 74.2% | — |
| DeepSWE | — | 54.9% |
| FrontierSWE | — | 12% |
| ALE-Bench | 887.1 | — |
Agentic & Tool Use Muse Spark 1.2 leads
GLM-5.1: 24.8 (#106), Muse Spark 1.2: 29.5 (#77)
| Benchmark | GLM-5.1 | Muse Spark 1.2 |
|---|---|---|
| APEX-Agents | 40.9% | 36.4% |
| ExploitBench | 18.1% | — |
| GBAEval | 0% | — |
| GDP.pdf | — | 16% |
| Vending-Bench 2 | 5,634 | — |
Reasoning Muse Spark 1.2 leads
GLM-5.1: 38.2 (#57), Muse Spark 1.2: 50.4 (#32)
| Benchmark | GLM-5.1 | Muse Spark 1.2 |
|---|---|---|
| SimpleBench | 55.1% | 74.5% |
| NYT Connections (extended) | 77.7% | 79.2% |
| CritPt | 4.6% | 17.7% |
| LMArena Hard Prompts | 1472 | 1490 |
| Epoch Capabilities Index | 149.86 | 155.18 |
| Chess Puzzles | 19% | — |
| Thematic Generalization | 69.8% | — |
| DTBench | — | 94.7% |
| LMCA | — | 48.4% |
Math GLM-5.1 leads
GLM-5.1: 49.0 (#48), Muse Spark 1.2: 43.8 (#68)
| Benchmark | GLM-5.1 | Muse Spark 1.2 |
|---|---|---|
| ProofBench | 22.2% | 43% |
| FrontierMath (Tiers 1-3) | 36.8% | — |
| MathArena Final-Answer Competitions | 67.1% | — |
| OTIS Mock AIME 2024-2025 | 93.3% | — |
| LMArena Math | 1472 | — |
| FrontierMath (Feb 2025 set) | 33.4% | — |
| FrontierMath Tier 4 (v1) | 12.5% | — |
Knowledge GLM-5.1 leads
GLM-5.1: 55.0 (#45), Muse Spark 1.2: 53.9 (#49)
| Benchmark | GLM-5.1 | Muse Spark 1.2 |
|---|---|---|
| SimpleQA Verified | 34% | 60.3% |
| LMArena Expert | 1477 | 1485 |
| GPQA Diamond | 89.9% | — |
Multimodal Not comparable
GLM-5.1: —, Muse Spark 1.2: 42.6 (#24)
| Benchmark | GLM-5.1 | Muse Spark 1.2 |
|---|---|---|
| LMArena Vision | — | 1304 |
Multilingual Muse Spark 1.2 leads
GLM-5.1: 55.2 (#34), Muse Spark 1.2: 57.4 (#10)
| Benchmark | GLM-5.1 | Muse Spark 1.2 |
|---|---|---|
| LMArena Non-English | 1448 | 1479 |
| LMArena Chinese | 1516 | 1519 |
| LMArena Russian | 1453 | 1494 |
| LMArena French | 1478 | — |
| LMArena German | 1466 | — |
| LMArena Japanese | 1436 | — |
| LMArena Korean | 1423 | — |
| LMArena Spanish | 1467 | — |
Instruction Following Too close to call
GLM-5.1: 76.5 (#41), Muse Spark 1.2: 77.1 (#30)
| Benchmark | GLM-5.1 | Muse Spark 1.2 |
|---|---|---|
| LMArena Instruction Following | 1451 | 1466 |
Long Context Too close to call
GLM-5.1: 44.9 (#51), Muse Spark 1.2: 45.4 (#35)
| Benchmark | GLM-5.1 | Muse Spark 1.2 |
|---|---|---|
| LMArena Longer Query | 1467 | 1483 |
Writing & Preference Muse Spark 1.2 leads
GLM-5.1: 67.2 (#29), Muse Spark 1.2: 72.6 (#14)
| Benchmark | GLM-5.1 | Muse Spark 1.2 |
|---|---|---|
| LMArena Text | 1462 | 1486 |
| LMArena Creative Writing | 1454 | 1444 |
| EQ-Bench Creative Writing | 1592 | 1840 |
| LMArena Multi-Turn | 1473 | 1504 |
Frequently asked questions
Is GLM-5.1 better than Muse Spark 1.2?
Muse Spark 1.2 is the stronger model overall, scoring 49.8 to 47.6 on the Noometry Index.
Which is cheaper, GLM-5.1 or Muse Spark 1.2?
Muse Spark 1.2 is cheaper. It lists at $1.25 per million input tokens and $4.25 per million output tokens; GLM-5.1 lists at $1.40 and $4.40.
Is GLM-5.1 or Muse Spark 1.2 better for coding?
They score almost the same on coding (48.5 vs 48.6); test both on your own repository before choosing.
Which has the bigger context window?
Muse Spark 1.2 does, with 1.05M tokens against 200K.
How many benchmarks do GLM-5.1 and Muse Spark 1.2 share?
22 benchmarks have published results for both models. GLM-5.1 has 41 scored results on Noometry and Muse Spark 1.2 has 28.