Model comparison
GLM-5.2 vs Muse Spark 1.2
GLM-5.2 and Muse Spark 1.2 score almost the same on the Noometry Index (51.1 vs 50.3), so choose on price, context window or the category you care about most.
Last verified . 28 shared benchmarks.
MetaSummary
- They share 28 benchmarks with published results for both. GLM-5.2 scores higher in 6 categories and Muse Spark 1.2 in 3 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5.2 leads 55.7 to 46.4.
- The biggest single-benchmark swing is SimpleQA Verified: 34.2% for GLM-5.2 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-5.2.
- Muse Spark 1.2 accepts more context: 1.05M tokens versus 1M.
- GLM-5.2 has downloadable open weights; the other is API-only.
Side by side
| GLM-5.2 | Muse Spark 1.2 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 51.1 | 50.3 |
| Released | 2026-06-13 | 2026-08-05 |
| Weights | Open | Proprietary |
| Context window | 1M | 1.05M |
| Max output | 131K | 131K |
| Input $ / M tokens | $1.40 | $1.25 |
| Output $ / M tokens | $4.40 | $4.25 |
| Results tracked | 51 | 31 |
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Category by category
Coding GLM-5.2 leads
GLM-5.2: 51.3 (#41), Muse Spark 1.2: 49.2 (#51)
| Benchmark | GLM-5.2 | Muse Spark 1.2 |
|---|---|---|
| DeepSWE | 43.8% | 54.9% |
| LMArena WebDev | 1603 | 1533 |
| SciCode | 50.5% | 56.4% |
| WeirdML | 70.1% | 60.3% |
| LMArena Coding | 1485 | 1495 |
| SWE-bench Verified | 78.7% | — |
| FrontierCode | 24.5% | — |
| FrontierSWE | — | 12% |
| ALE-Bench | 1,047 | — |
Agentic & Tool Use GLM-5.2 leads
GLM-5.2: 32.4 (#63), Muse Spark 1.2: 29.4 (#87)
| Benchmark | GLM-5.2 | Muse Spark 1.2 |
|---|---|---|
| APEX-Agents | 45.2% | 36.4% |
| τ²-bench Banking | 37.1% | — |
| PostTrainBench | 31.7% | — |
| GBAEval | 0% | — |
| GDP.pdf | — | 16% |
| Vending-Bench 2 | 8,314 | — |
Reasoning Muse Spark 1.2 leads
GLM-5.2: 42.3 (#52), Muse Spark 1.2: 51.3 (#34)
| Benchmark | GLM-5.2 | Muse Spark 1.2 |
|---|---|---|
| SimpleBench | 58.8% | 74.5% |
| NYT Connections (extended) | 74.3% | 79.2% |
| CritPt | 20.9% | 17.7% |
| LMArena Hard Prompts | 1480 | 1486 |
| DTBench | 93.6% | 94.7% |
| LMCA | 45.8% | 48.4% |
| Epoch Capabilities Index | 151.78 | 154.87 |
| ARC-AGI-2 | 22.8% | — |
| Kagi LLM Benchmark | 62.6% | — |
| ARC-AGI-1 | 77% | — |
| Chess Puzzles | 21% | — |
| EBR-Bench | 9.5% | — |
| Mystery Game Puzzles | 19% | — |
| Surface Evolver Bench | 55.6% | — |
Math GLM-5.2 leads
GLM-5.2: 55.7 (#43), Muse Spark 1.2: 46.4 (#70)
| Benchmark | GLM-5.2 | Muse Spark 1.2 |
|---|---|---|
| ProofBench | 35% | 43% |
| LMArena Math | 1482 | 1471 |
| FrontierMath (Tiers 1-3) | 59.2% | — |
| FrontierMath Tier 4 | 29.3% | — |
| MathArena Final-Answer Competitions | 67.6% | — |
| OTIS Mock AIME 2024-2025 | 86.4% | — |
Knowledge GLM-5.2 leads
GLM-5.2: 57.1 (#40), Muse Spark 1.2: 54.1 (#53)
| Benchmark | GLM-5.2 | Muse Spark 1.2 |
|---|---|---|
| SimpleQA Verified | 34.2% | 60.3% |
| LMArena Expert | 1486 | 1480 |
| GPQA Diamond | 91.9% | — |
Multimodal Not comparable
GLM-5.2: —, Muse Spark 1.2: 43.4 (#25)
| Benchmark | GLM-5.2 | Muse Spark 1.2 |
|---|---|---|
| LMArena Vision | — | 1305 |
Multilingual Muse Spark 1.2 leads
GLM-5.2: 55.8 (#26), Muse Spark 1.2: 57.1 (#11)
| Benchmark | GLM-5.2 | Muse Spark 1.2 |
|---|---|---|
| LMArena Non-English | 1459 | 1478 |
| LMArena Chinese | 1519 | 1511 |
| LMArena French | 1479 | 1513 |
| LMArena Russian | 1466 | 1487 |
| LMArena Spanish | 1477 | 1498 |
| LMArena German | 1468 | — |
| LMArena Japanese | 1451 | — |
| LMArena Korean | 1445 | — |
Instruction Following Too close to call
GLM-5.2: 76.9 (#34), Muse Spark 1.2: 76.7 (#36)
| Benchmark | GLM-5.2 | Muse Spark 1.2 |
|---|---|---|
| LMArena Instruction Following | 1465 | 1461 |
Long Context Too close to call
GLM-5.2: 45.3 (#43), Muse Spark 1.2: 45.2 (#48)
| Benchmark | GLM-5.2 | Muse Spark 1.2 |
|---|---|---|
| LMArena Longer Query | 1479 | 1475 |
Writing & Preference Muse Spark 1.2 leads
GLM-5.2: 70.4 (#21), Muse Spark 1.2: 72.3 (#14)
| Benchmark | GLM-5.2 | Muse Spark 1.2 |
|---|---|---|
| LMArena Text | 1470 | 1482 |
| LMArena Creative Writing | 1462 | 1449 |
| EQ-Bench Creative Writing | 1757 | 1840 |
| LMArena Multi-Turn | 1469 | 1494 |
| EQ-Bench 4 | 1222 | — |
Frequently asked questions
Is GLM-5.2 better than Muse Spark 1.2?
GLM-5.2 and Muse Spark 1.2 score almost the same on the Noometry Index (51.1 vs 50.3), so choose on price, context window or the category you care about most.
Which is cheaper, GLM-5.2 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-5.2 lists at $1.40 and $4.40.
Is GLM-5.2 or Muse Spark 1.2 better for coding?
GLM-5.2 scores higher on coding benchmarks: 51.3 versus 49.2 in the Noometry coding category.
Which has the bigger context window?
Muse Spark 1.2 does, with 1.05M tokens against 1M.
How many benchmarks do GLM-5.2 and Muse Spark 1.2 share?
28 benchmarks have published results for both models. GLM-5.2 has 51 scored results on Noometry and Muse Spark 1.2 has 31.