Model comparison
GLM-4.7 vs Muse Spark 1.2
Muse Spark 1.2 is the stronger model overall, scoring 50.3 to 42.0 on the Noometry Index. GLM-4.7 costs 2.0× less per token, which makes it the better buy when Muse Spark 1.2's lead doesn't matter for your workload.
Last verified . 22 shared benchmarks.
MetaSummary
- They share 22 benchmarks with published results for both. GLM-4.7 scores higher in 0 categories and Muse Spark 1.2 in 9 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Muse Spark 1.2 leads 51.3 to 24.3.
- The biggest single-benchmark swing is ProofBench: 6% for GLM-4.7 and 43% for Muse Spark 1.2.
- GLM-4.7 is cheaper at $0.60 / $2.20 per million input/output tokens, against $1.25 / $4.25 for Muse Spark 1.2.
- Muse Spark 1.2 accepts more context: 1.05M tokens versus 205K.
- GLM-4.7 has downloadable open weights; the other is API-only.
Side by side
| GLM-4.7 | Muse Spark 1.2 | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 42.0 | 50.3 |
| Released | 2025-12-22 | 2026-08-05 |
| Weights | Open | Proprietary |
| Context window | 205K | 1.05M |
| Max output | 131K | 131K |
| Input $ / M tokens | $0.60 | $1.25 |
| Output $ / M tokens | $2.20 | $4.25 |
| Results tracked | 36 | 31 |
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Category by category
Coding Muse Spark 1.2 leads
GLM-4.7: 44.0 (#79), Muse Spark 1.2: 49.2 (#51)
| Benchmark | GLM-4.7 | Muse Spark 1.2 |
|---|---|---|
| LMArena WebDev | 1435 | 1533 |
| SciCode | 45.1% | 56.4% |
| LMArena Coding | 1454 | 1495 |
| DeepSWE | — | 54.9% |
| FrontierSWE | — | 12% |
| WeirdML | — | 60.3% |
| ALE-Bench | 399.48 | — |
Agentic & Tool Use Muse Spark 1.2 leads
GLM-4.7: 26.5 (#103), Muse Spark 1.2: 29.4 (#87)
| Benchmark | GLM-4.7 | Muse Spark 1.2 |
|---|---|---|
| Terminal-Bench | 33.4% | — |
| APEX-Agents | — | 36.4% |
| GDP.pdf | — | 16% |
| Vending-Bench 2 | 2,377 | — |
Reasoning Muse Spark 1.2 leads
GLM-4.7: 24.3 (#164), Muse Spark 1.2: 51.3 (#34)
| Benchmark | GLM-4.7 | Muse Spark 1.2 |
|---|---|---|
| SimpleBench | 47.7% | 74.5% |
| CritPt | 1.7% | 17.7% |
| LMArena Hard Prompts | 1443 | 1486 |
| Epoch Capabilities Index | 143.51 | 154.87 |
| NYT Connections (extended) | — | 79.2% |
| Chess Puzzles | 6% | — |
| DTBench | — | 94.7% |
| LMCA | — | 48.4% |
Math Muse Spark 1.2 leads
GLM-4.7: 38.6 (#135), Muse Spark 1.2: 46.4 (#70)
| Benchmark | GLM-4.7 | Muse Spark 1.2 |
|---|---|---|
| ProofBench | 6% | 43% |
| LMArena Math | 1423 | 1471 |
| OTIS Mock AIME 2024-2025 | 83.3% | — |
| FrontierMath (Feb 2025 set) | 2.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Muse Spark 1.2 leads
GLM-4.7: 47.0 (#80), Muse Spark 1.2: 54.1 (#53)
| Benchmark | GLM-4.7 | Muse Spark 1.2 |
|---|---|---|
| SimpleQA Verified | 32.2% | 60.3% |
| LMArena Expert | 1424 | 1480 |
| GPQA Diamond | 83.3% | — |
| Vectara Hallucination Rate | 11.7% | — |
Multimodal Not comparable
GLM-4.7: —, Muse Spark 1.2: 43.4 (#25)
| Benchmark | GLM-4.7 | Muse Spark 1.2 |
|---|---|---|
| LMArena Vision | — | 1305 |
Multilingual Muse Spark 1.2 leads
GLM-4.7: 52.8 (#79), Muse Spark 1.2: 57.1 (#11)
| Benchmark | GLM-4.7 | Muse Spark 1.2 |
|---|---|---|
| LMArena Non-English | 1417 | 1478 |
| LMArena Chinese | 1495 | 1511 |
| LMArena French | 1432 | 1513 |
| LMArena Russian | 1423 | 1487 |
| LMArena Spanish | 1434 | 1498 |
| LMArena German | 1424 | — |
| LMArena Japanese | 1439 | — |
| LMArena Korean | 1399 | — |
Instruction Following Muse Spark 1.2 leads
GLM-4.7: 74.4 (#95), Muse Spark 1.2: 76.7 (#36)
| Benchmark | GLM-4.7 | Muse Spark 1.2 |
|---|---|---|
| LMArena Instruction Following | 1411 | 1461 |
Long Context Muse Spark 1.2 leads
GLM-4.7: 42.8 (#116), Muse Spark 1.2: 45.2 (#48)
| Benchmark | GLM-4.7 | Muse Spark 1.2 |
|---|---|---|
| LMArena Longer Query | 1432 | 1475 |
| CL-bench | 15.9% | — |
| CL-bench Life | 10.9% | — |
Writing & Preference Muse Spark 1.2 leads
GLM-4.7: 60.9 (#93), Muse Spark 1.2: 72.3 (#14)
| Benchmark | GLM-4.7 | Muse Spark 1.2 |
|---|---|---|
| LMArena Text | 1435 | 1482 |
| LMArena Creative Writing | 1401 | 1449 |
| EQ-Bench Creative Writing | 1413 | 1840 |
| LMArena Multi-Turn | 1446 | 1494 |
Frequently asked questions
Is GLM-4.7 better than Muse Spark 1.2?
Muse Spark 1.2 is the stronger model overall, scoring 50.3 to 42.0 on the Noometry Index. GLM-4.7 costs 2.0× less per token, which makes it the better buy when Muse Spark 1.2's lead doesn't matter for your workload.
Which is cheaper, GLM-4.7 or Muse Spark 1.2?
GLM-4.7 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Muse Spark 1.2 lists at $1.25 and $4.25.
Is GLM-4.7 or Muse Spark 1.2 better for coding?
Muse Spark 1.2 scores higher on coding benchmarks: 49.2 versus 44.0 in the Noometry coding category.
Which has the bigger context window?
Muse Spark 1.2 does, with 1.05M tokens against 205K.
How many benchmarks do GLM-4.7 and Muse Spark 1.2 share?
22 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and Muse Spark 1.2 has 31.