Model comparison
GLM-4.6 vs Muse Spark
Muse Spark is the stronger model overall, scoring 50.3 to 40.9 on the Noometry Index.
Last verified . 20 shared benchmarks.
MetaSummary
- They share 20 benchmarks with published results for both. GLM-4.6 scores higher in 0 categories and Muse Spark in 8 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where Muse Spark leads 65.7 to 39.6.
- The biggest single-benchmark swing is SciCode: 38.4% for GLM-4.6 and 51.5% for Muse Spark.
- GLM-4.6 has downloadable open weights; the other is API-only.
Side by side
| GLM-4.6 | Muse Spark | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 40.9 | 50.3 |
| Released | 2025-09-30 | 2026-04-08 |
| Weights | Open | Proprietary |
| Context window | 205K | — |
| Max output | 131K | — |
| Input $ / M tokens | $0.60 | — |
| Output $ / M tokens | $2.20 | — |
| Results tracked | 29 | 27 |
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Category by category
Coding Muse Spark leads
GLM-4.6: 39.9 (#137), Muse Spark: 45.6 (#65)
| Benchmark | GLM-4.6 | Muse Spark |
|---|---|---|
| SciCode | 38.4% | 51.5% |
| LMArena Coding | 1449 | 1482 |
| SWE-bench Verified (bash only) | 55.4% | — |
| LMArena WebDev | 1339 | — |
| ALE-Bench | 340.82 | — |
Agentic & Tool Use Not comparable
GLM-4.6: 32.1 (#60), Muse Spark: —
| Benchmark | GLM-4.6 | Muse Spark |
|---|---|---|
| Terminal-Bench | 24.5% | — |
| Berkeley Function Calling Leaderboard | 72.4% | — |
Reasoning Muse Spark leads
GLM-4.6: 23.1 (#168), Muse Spark: 34.9 (#61)
| Benchmark | GLM-4.6 | Muse Spark |
|---|---|---|
| CritPt | 1.1% | 11.3% |
| LMArena Hard Prompts | 1440 | 1475 |
| Kagi LLM Benchmark | 47.4% | — |
| Epoch Capabilities Index | — | 152.09 |
Math Muse Spark leads
GLM-4.6: 36.4 (#115), Muse Spark: 46.8 (#57)
| Benchmark | GLM-4.6 | Muse Spark |
|---|---|---|
| LMArena Math | 1431 | 1455 |
| FrontierMath (Feb 2025 set) | 3.8% | 39% |
| FrontierMath Tier 4 (v1) | 2.1% | 14.6% |
| OTIS Mock AIME 2024-2025 | — | 88.9% |
| ProofBench | — | 17% |
Knowledge Muse Spark leads
GLM-4.6: 39.6 (#118), Muse Spark: 65.7 (#12)
| Benchmark | GLM-4.6 | Muse Spark |
|---|---|---|
| LMArena Expert | 1432 | 1458 |
| GPQA Diamond | — | 89.8% |
| Humanity's Last Exam | — | 40.6% |
| Vectara Hallucination Rate | 9.5% | — |
Multimodal Not comparable
GLM-4.6: —, Muse Spark: 42.7 (#23)
| Benchmark | GLM-4.6 | Muse Spark |
|---|---|---|
| LMArena Vision | — | 1306 |
| LMArena Document | — | 1444 |
Multilingual Muse Spark leads
GLM-4.6: 53.6 (#62), Muse Spark: 56.3 (#23)
| Benchmark | GLM-4.6 | Muse Spark |
|---|---|---|
| LMArena Non-English | 1426 | 1464 |
| LMArena Chinese | 1500 | 1507 |
| LMArena French | 1459 | 1497 |
| LMArena German | 1447 | 1497 |
| LMArena Korean | 1401 | 1457 |
| LMArena Russian | 1418 | 1467 |
| LMArena Spanish | 1436 | 1471 |
| LMArena Japanese | 1394 | — |
Instruction Following Muse Spark leads
GLM-4.6: 74.5 (#93), Muse Spark: 76.1 (#47)
| Benchmark | GLM-4.6 | Muse Spark |
|---|---|---|
| LMArena Instruction Following | 1410 | 1443 |
Long Context Too close to call
GLM-4.6: 43.4 (#91), Muse Spark: 44.4 (#65)
| Benchmark | GLM-4.6 | Muse Spark |
|---|---|---|
| LMArena Longer Query | 1423 | 1451 |
Writing & Preference Muse Spark leads
GLM-4.6: 61.3 (#86), Muse Spark: 66.2 (#37)
| Benchmark | GLM-4.6 | Muse Spark |
|---|---|---|
| LMArena Text | 1440 | 1474 |
| LMArena Creative Writing | 1411 | 1460 |
| LMArena Multi-Turn | 1427 | 1477 |
| EQ-Bench Creative Writing | 1411 | — |
Frequently asked questions
Is GLM-4.6 better than Muse Spark?
Muse Spark is the stronger model overall, scoring 50.3 to 40.9 on the Noometry Index.
Is GLM-4.6 or Muse Spark better for coding?
Muse Spark scores higher on coding benchmarks: 45.6 versus 39.9 in the Noometry coding category.
How many benchmarks do GLM-4.6 and Muse Spark share?
20 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Muse Spark has 27.