Model comparison
GLM-5.3 vs Muse Spark
GLM-5.3 is the stronger model overall, scoring 54.8 to 50.6 on the Noometry Index.
Last verified . 22 shared benchmarks.
MetaSummary
- They share 22 benchmarks with published results for both. GLM-5.3 scores higher in 6 categories and Muse Spark in 2 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5.3 leads 62.3 to 47.8.
- The biggest single-benchmark swing is ProofBench: 49% for GLM-5.3 and 17% for Muse Spark.
- GLM-5.3 has downloadable open weights; the other is API-only.
Side by side
| GLM-5.3 | Muse Spark | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 54.8 | 50.6 |
| Released | 2026-08-14 | 2026-04-08 |
| Weights | Open | Proprietary |
| Context window | 1M | — |
| Max output | 131K | — |
| Input $ / M tokens | $1.40 | — |
| Output $ / M tokens | $4.40 | — |
| Results tracked | 42 | 27 |
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Category by category
Coding GLM-5.3 leads
GLM-5.3: 59.5 (#14), Muse Spark: 46.2 (#69)
| Benchmark | GLM-5.3 | Muse Spark |
|---|---|---|
| SciCode | 59% | 51.5% |
| LMArena Coding | 1496 | 1481 |
| DeepSWE | 69% | — |
| FrontierCode | 40.1% | — |
| CursorBench | 42.6% | — |
| LMArena WebDev | 1622 | — |
| FrontierSWE | 30.2% | — |
| WeirdML | 75.4% | — |
| ALE-Bench | 1,317 | — |
Agentic & Tool Use Not comparable
GLM-5.3: 36.4 (#38), Muse Spark: —
| Benchmark | GLM-5.3 | Muse Spark |
|---|---|---|
| APEX-Agents | 56.6% | — |
| Vending-Bench 2 | 8,164 | — |
Reasoning GLM-5.3 leads
GLM-5.3: 46.1 (#46), Muse Spark: 35.9 (#67)
| Benchmark | GLM-5.3 | Muse Spark |
|---|---|---|
| CritPt | 19.1% | 11.3% |
| LMArena Hard Prompts | 1489 | 1474 |
| Epoch Capabilities Index | 155.61 | 152.04 |
| NYT Connections (extended) | 74.2% | — |
| Chess Puzzles | 21% | — |
| Mystery Game Puzzles | 33% | — |
| DTBench | 87.7% | — |
| LMCA | 55.5% | — |
| Bench to the Future 3 | 0.15 | — |
Math GLM-5.3 leads
GLM-5.3: 62.3 (#33), Muse Spark: 47.8 (#66)
| Benchmark | GLM-5.3 | Muse Spark |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 91.1% | 88.9% |
| ProofBench | 49% | 17% |
| LMArena Math | 1489 | 1455 |
| FrontierMath (Tiers 1-3) | 68.8% | — |
| FrontierMath Tier 4 | 29.3% | — |
| FrontierMath (Feb 2025 set) | — | 39% |
| FrontierMath Tier 4 (v1) | — | 14.6% |
Knowledge Muse Spark leads
GLM-5.3: 58.3 (#37), Muse Spark: 65.7 (#13)
| Benchmark | GLM-5.3 | Muse Spark |
|---|---|---|
| GPQA Diamond | 90.9% | 89.8% |
| LMArena Expert | 1516 | 1457 |
| Humanity's Last Exam | — | 40.6% |
| SimpleQA Verified | 41% | — |
Multimodal Not comparable
GLM-5.3: —, Muse Spark: 43.4 (#24)
| Benchmark | GLM-5.3 | Muse Spark |
|---|---|---|
| LMArena Vision | — | 1306 |
| LMArena Document | — | 1444 |
Multilingual Too close to call
GLM-5.3: 55.7 (#28), Muse Spark: 56.1 (#24)
| Benchmark | GLM-5.3 | Muse Spark |
|---|---|---|
| LMArena Non-English | 1457 | 1464 |
| LMArena Chinese | 1528 | 1509 |
| LMArena French | 1499 | 1497 |
| LMArena German | 1499 | 1497 |
| LMArena Korean | 1472 | 1459 |
| LMArena Russian | 1463 | 1466 |
| LMArena Spanish | 1460 | 1472 |
| LMArena Japanese | 1453 | — |
Instruction Following GLM-5.3 leads
GLM-5.3: 77.5 (#23), Muse Spark: 75.9 (#51)
| Benchmark | GLM-5.3 | Muse Spark |
|---|---|---|
| LMArena Instruction Following | 1477 | 1442 |
Long Context GLM-5.3 leads
GLM-5.3: 45.4 (#41), Muse Spark: 44.4 (#69)
| Benchmark | GLM-5.3 | Muse Spark |
|---|---|---|
| LMArena Longer Query | 1482 | 1451 |
Writing & Preference GLM-5.3 leads
GLM-5.3: 75.7 (#6), Muse Spark: 66.0 (#39)
| Benchmark | GLM-5.3 | Muse Spark |
|---|---|---|
| LMArena Text | 1471 | 1474 |
| LMArena Creative Writing | 1457 | 1459 |
| LMArena Multi-Turn | 1472 | 1477 |
| EQ-Bench Creative Writing | 2075 | — |
Frequently asked questions
Is GLM-5.3 better than Muse Spark?
GLM-5.3 is the stronger model overall, scoring 54.8 to 50.6 on the Noometry Index.
Is GLM-5.3 or Muse Spark better for coding?
GLM-5.3 scores higher on coding benchmarks: 59.5 versus 46.2 in the Noometry coding category.
How many benchmarks do GLM-5.3 and Muse Spark share?
22 benchmarks have published results for both models. GLM-5.3 has 42 scored results on Noometry and Muse Spark has 27.