GLM-5.2 vs Muse Spark 1.3
GLM-5.2 
Muse Spark 1.3 Verdict
- Muse Spark 1.3 (max) leads on quality: 69.3 vs 63.9.
- GLM-5.2 (max) is stronger in instruction following.
- Muse Spark 1.3 (max) is stronger in agents & tools, coding, composite, human preference, knowledge, long context, maths, reasoning, multimodal.
- They cost about the same ($2.00 per 1M blended).
- Muse Spark 1.3 (max) streams 3.1× faster (223 vs 71 tokens per second).
| Metric | GLM-5.2 (max) | Muse Spark 1.3 (max) |
|---|---|---|
| BenchLeader Index | 63.9 | 69.3 |
| Agents & tools score | 63.8 | 71.1 |
| Coding score | 63.8 | 66.6 |
| Composite score | 72.1 | 90.1 |
| Human preference score | 67.2 | 69.8 |
| Instruction following score | 71.6 | – |
| Knowledge score | 55.5 | 76.1 |
| Long context score | 65.6 | 68.0 |
| Maths score | 59.0 | 69.2 |
| Reasoning score | 72.9 | 83.1 |
| Multimodal score | – | 67.4 |
| Blended price $/M | $2.15 | $2.00 |
| Output speed | 71 tok/s | 223 tok/s |
| Time to first answer | 31.6 s | 34.8 s |
| Context window | 1M | 1.0M |
| GPQA Diamond | 91.9% | – |
| FrontierMath Tiers 1–3 | 59.2% | – |
| FrontierMath Tier 4 | 29.3% | – |
| OTIS Mock AIME | 86.4% | – |
| SWE-bench Verified (Epoch) | 78.7% | – |
| SimpleQA Verified | 34.2% | – |
| SciCode | 50.5% | – |
| WeirdML | 70.1% | – |
| ProofBench | 35.0% | – |
| LMArena Text | 1472 | 1493 |
| LMArena Hard Prompts | 1493 | 1516 |
| LMArena Coding | 1510 | 1537 |
| LMArena WebDev | 1592 | 1652 |
| LMArena Vision | – | 1315 |
| LMArena Agent | 4.4 | 4.2 |
| AA Intelligence Index | 34.0 | 48.2 |
| IFBench | 73.3% | – |
| AA-LCR | 78.3% | 83.0% |
| AA-Omniscience | 4.4 | 25 |
| Terminal-Bench Hard | 50.8% | – |
| GPQA Diamond (AA) | 89.5% | 93.5% |
| Humanity's Last Exam (AA) | 41.1% | 48.7% |
| SciCode (AA) | 51.2% | 58.8% |
| τ²-Bench Telecom (AA) | 99.1% | – |
| IOI | – | 56.6% |
| Terminal-Bench 2.1 (Vals) | 67.8% | 79.0% |
| SWE-bench (Vals) | 82.8% | – |
| Vals Index | – | 64.5 |
| CritPt | 20.9% | 24.9% |
| GDPval (AA) | 45.3% | 60.2% |
| τ²-Bench Banking (AA) | 34.6% | 50.5% |
| ITBench SRE (AA) | 42.7% | – |
| APEX-Agents (AA) | 33.7% | – |
| Code Migration | 37.9% | 47.4% |
| Excel Modeling Benchmark | – | 67.4% |
| Finance Agent v2 | – | 60.0% |
| Harvey's Legal Agent Benchmark | 7.1% | 23.8% |
| Legal Research Bench | 31.3% | 55.3% |
| MysteryMechanism | – | 36.0% |
| ProgramBench | 0.5% | – |
| SkillsBench | 45.1% | – |
| SREBench | 0.0% | – |
| Terminal-Bench 4.0 (Vals) | – | 27.8% |
| Terminal-Bench Science | – | 14.3% |
| Vibe Code Bench 1-100 | – | 20.5% |
| Vibe Code Bench v1.1 | 64.0% | 85.9% |
| LMArena Maths | 1480 | 1496 |
| LMArena Creative Writing | 1451 | 1453 |
| LMArena Instruction Following | 1466 | 1483 |
| LMArena Multi-turn | 1469 | 1493 |
| LMArena Longer Queries | 1483 | 1506 |
| LMArena Document | – | 1468 |
| Chess Puzzles | 21.0% | – |
| EBR-bench | 9.5% | – |
| PostTrainBench | 31.7% | – |
| DeepSWE | 43.8% | – |
| LMCA | 45.8% | – |
| DTBench | 93.6% | – |
| CursorBench | 55.0% | – |
| ALE-Bench | 1010.2 | – |
Data as of 2026-09-19. Best configuration of each model; every score links to its source on the model pages.
GLM-5.2 vs Muse Spark 1.3: questions
- Is GLM-5.2 better than Muse Spark 1.3?
- Muse Spark 1.3 (max) leads on quality: 69.3 vs 63.9. The BenchLeader Index combines every independent quality benchmark; Muse Spark 1.3 (max) is ahead overall as of 2026-09-19, but check the category scores for your use.
- Is GLM-5.2 better than Muse Spark 1.3 for coding?
- Muse Spark 1.3 scores higher in coding (67 vs 64 on the category index, where 50 is average).
- Is GLM-5.2 better than Muse Spark 1.3 for agentic tasks?
- Muse Spark 1.3 scores higher in agentic tasks (71 vs 64 on the category index, where 50 is average).
- Which is cheaper, GLM-5.2 or Muse Spark 1.3?
- Muse Spark 1.3 is cheaper: $2.00 against $2.15 per million tokens, blended at three input tokens per output token.
- Which is faster, GLM-5.2 or Muse Spark 1.3?
- Muse Spark 1.3 streams faster: 223 against 71 output tokens per second.
- Which has the larger context window?
- Muse Spark 1.3 accepts more context: 1.0M against 1M tokens.