Model comparison
GLM-5 vs Muse Spark
Head-to-head evidence from 20 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-5 #28 (Supported); Muse Spark #13 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-5 and Muse Spark share 20 comparable benchmark results. 5 of 8 categories are comparable. 29 results are unique to GLM-5; 19 to Muse Spark.
Updated July 18, 2026- Shared results
- 20
- GLM-5 only
- 29
- Muse Spark only
- 19
- Comparable categories
- 5 / 8
Pick Muse Spark if you want the stronger benchmark profile. GLM-5 only becomes the better choice if mathematics is the priority or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 20 shared benchmark results across 6 evidence categories; 5 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Muse Spark is clearly ahead on the BenchAlign aggregate, 71.04 to 66.06. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Muse Spark's sharpest advantage is in agentic, where it averages 59 against 56.2. The single biggest benchmark swing on the page is FrontierMath v2 (Tiers 1-3), 16.434% to 39.000%. GLM-5 does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.
Muse Spark is the reasoning model in the pair, while GLM-5 is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. Muse Spark gives you the larger context window at 262K, compared with 200K for GLM-5.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | GLM-5 | Δ | Muse Spark |
|---|---|---|---|
| Math | GLM-556.3 | Margin← 23.4 | Muse Spark32.9 |
| Reasoning | GLM-560.8 | Margin← 18.3 | Muse Spark42.5 |
| Knowledge | GLM-566.4 | Margin← 16.0 | Muse Spark50.4 |
| Agentic | GLM-556.2 | Margin→ 2.8 | Muse Spark59.0 |
| Coding | GLM-566.3 | Margin→ 1.5 | Muse Spark67.8 |
| Multilingual | GLM-583.1 | MarginNo overlap | Muse SparkNot measured |
| Multimodal | GLM-5Not measured | MarginNo overlap | Muse Spark82.5 |
| Inst. Following | GLM-592.6 | MarginNo overlap | Muse SparkNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 16.434%B 39.000%Winner: Muse SparkΔ 22.6FrontierMath v2 (Tiers 1-3): GLM-5 scored 16.434%; Muse Spark scored 39.000%. Muse Spark wins this benchmark. - Source ↗
FrontierMath v2 (Tier 4)
MathA 2.100%B 14.600%Winner: Muse SparkΔ 12.5FrontierMath v2 (Tier 4): GLM-5 scored 2.100%; Muse Spark scored 14.600%. Muse Spark wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 56.2%B 59%Winner: Muse SparkΔ 2.8Terminal-Bench 2.0: GLM-5 scored 56.2%; Muse Spark scored 59%. Muse Spark wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 55.1%B 52.4%Winner: GLM-5Δ 2.7SWE-bench Pro: GLM-5 scored 55.1%; Muse Spark scored 52.4%. GLM-5 wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 77.8%B 77.4%Winner: GLM-5Δ 0.4SWE-bench Verified: GLM-5 scored 77.8%; Muse Spark scored 77.4%. GLM-5 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-5 | Muse Spark | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-5$1 input / $3.2 output | Muse SparkNot available | A complete price comparison is not available. |
| Generation speedtokens per second | GLM-574 tok/s | Muse SparkNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-51.64 s | Muse SparkNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-5200K | Muse Spark262K | Muse Spark lists the larger context window. |
Benchmark Deep Dive
AgenticMuse Spark wins17 benchmarks
| Benchmark | GLM-5 | Muse Spark | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 56.2% | 59% | Muse Spark leads |
| Claw-EvalSource | 57.7% | 63.8% | Muse Spark leads |
| QwenClawBenchSource | 54.1% | — | Not comparable |
| τ³-bench resultsSource | 65.6% | — | Not comparable |
| DeepPlanningSource | 14.6% | — | Not comparable |
| ToolathlonSource | 38% | — | Not comparable |
| MCP AtlasSource | 31.1% | — | Not comparable |
| MCP-TasksSource | 60.8% | — | Not comparable |
| WideResearchSource | 69.8% | — | Not comparable |
| τ²-bench resultsSource | 98.2% | 91.5% | GLM-5 leads |
| CyberGymSource | 43.2% | 43.5% | Muse Spark leads |
| APEX-Agents-AASource | 14.5% | — | Not comparable |
| Gert LabsSource | 50.99% | — | Not comparable |
| DeepSearchQASource | — | 74.8% | Not comparable |
| AA Agentic IndexSource | — | 28.7% | Not comparable |
| GDPval-AASource | — | 32.2% | Not comparable |
| GDPval-AASource | — | 1144 | Not comparable |
CodingMuse Spark wins10 benchmarks
| Benchmark | GLM-5 | Muse Spark | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 77.8% | 77.4% | GLM-5 leads |
| SWE-bench Verified*Source | 72.8% | — | Not comparable |
| SWE-bench ProSource | 55.1% | 52.4% | GLM-5 leads |
| SWE MultilingualSource | 73.3% | — | Not comparable |
| SWE-RebenchSource | 62.8% | — | Not comparable |
| React Native EvalsSource | 74.8% | — | Not comparable |
| AA-SciCodeSource | 46.2% | 51.5% | Muse Spark leads |
| LiveCodeBench ProSource | — | 80.0% | Not comparable |
| Vibe Code BenchSource | — | 19.67% | Not comparable |
| AA Coding IndexSource | — | 58.6% | Not comparable |
ReasoningGLM-5 wins5 benchmarks
KnowledgeGLM-5 wins15 benchmarks
| Benchmark | GLM-5 | Muse Spark | Result |
|---|---|---|---|
| GPQASource | 86% | — | Not comparable |
| GPQA-DSource | 86.0% | 89.5% | Muse Spark leads |
| SuperGPQASource | 66.8% | — | Not comparable |
| MMLU-ProSource | 85.7% | — | Not comparable |
| MMLU-Pro (Arcee)Source | 85.8% | — | Not comparable |
| HLESource | 50.4% | 50.4% | Tie |
| Artificial Analysis Intelligence IndexSource | 39.5% | 43.1% | Muse Spark leads |
| AA-GPQA DiamondSource | 82.0% | 88.4% | Muse Spark leads |
| AA-HLESource | 27.2% | 39.9% | Muse Spark leads |
| AA-Omniscience IndexSource | 2.0% | 4.1% | Muse Spark leads |
| AA-Omniscience AccuracySource | 26.9% | 44.6% | Muse Spark leads |
| AA-Omniscience Hallucination RateSource | 34.0% | 73.2% | GLM-5 leads |
| HLE w/o toolsSource | — | 42.8% | Not comparable |
| HealthBench HardSource | — | 42.8% | Not comparable |
| MedXpertQA (Text)Source | — | 52.6% | Not comparable |
MathGLM-5 wins8 benchmarks
| Benchmark | GLM-5 | Muse Spark | Result |
|---|---|---|---|
| AIME26Source | 95.8% | — | Not comparable |
| AIME25 (Arcee)Source | 93.3% | — | Not comparable |
| HMMT Feb 2025Source | 97.5% | — | Not comparable |
| HMMT Nov 2025Source | 96.9% | — | Not comparable |
| HMMT Feb 2026Source | 86.4% | — | Not comparable |
| MMAnswerBenchSource | 82.5% | — | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | 16.434% | 39.000% | Muse Spark leads |
| FrontierMath v2 (Tier 4)Source | 2.100% | 14.600% | Muse Spark leads |
Multilingual2 benchmarks
Multimodal9 benchmarks
| Benchmark | GLM-5 | Muse Spark | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1280 | — | Not comparable |
| CharXivSource | — | 86.4% | Not comparable |
| MMMU-ProSource | — | 80.4% | Not comparable |
| ERQASource | — | 64.7% | Not comparable |
| SimpleVQASource | — | 71.3% | Not comparable |
| ScreenSpot ProSource | — | 84.1% | Not comparable |
| ZeroBenchSource | — | 33.0% | Not comparable |
| MedXpertQA (MM)Source | — | 78.4% | Not comparable |
| AA-MMMU-ProSource | — | 80.5% | Not comparable |
Frequently Asked Questions (6)
Which is better, GLM-5 or Muse Spark?
Muse Spark is ahead on BenchLM's BenchAlign leaderboard, 71.04 to 66.06. The biggest single separator in this matchup is FrontierMath v2 (Tiers 1-3), where the scores are 16.434% and 39.000%.
Which is better for knowledge tasks, GLM-5 or Muse Spark?
GLM-5 has the edge for knowledge tasks in this comparison, averaging 66.4 versus 50.4. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for coding, GLM-5 or Muse Spark?
Muse Spark has the edge for coding in this comparison, averaging 67.8 versus 66.3. Inside this category, AA-SciCode is the benchmark that creates the most daylight between them.
Which is better for math, GLM-5 or Muse Spark?
GLM-5 has the edge for math in this comparison, averaging 56.3 versus 32.9. Inside this category, FrontierMath v2 (Tiers 1-3) is the benchmark that creates the most daylight between them.
Which is better for reasoning, GLM-5 or Muse Spark?
GLM-5 has the edge for reasoning in this comparison, averaging 60.8 versus 42.5. Inside this category, CritPt is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GLM-5 or Muse Spark?
Muse Spark has the edge for agentic tasks in this comparison, averaging 59 versus 56.2. Inside this category, τ²-bench results is the benchmark that creates the most daylight between them.
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