Model comparison
GLM-4.6 vs Muse Spark
Head-to-head evidence from 14 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-4.6 #85 (Supported); Muse Spark #13 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-4.6 and Muse Spark share 14 comparable benchmark results. 1 of 8 categories are comparable. 0 results are unique to GLM-4.6; 25 to Muse Spark.
Updated July 23, 2026- Shared results
- 14
- GLM-4.6 only
- 0
- Muse Spark only
- 25
- Comparable categories
- 1 / 8
Pick Muse Spark if you want the stronger benchmark profile. GLM-4.6 only becomes the better choice if its workflow or ecosystem matters more than the raw scoreboard.
Confidence note. This is a partial-evidence comparison with 14 shared benchmark results across 6 evidence categories; 1 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 55.12. 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 mathematics, where it averages 32.9 against 3.4. The single biggest benchmark swing on the page is FrontierMath v2 (Tiers 1-3), 3.819% to 39.000%.
Muse Spark gives you the larger context window at 262K, compared with 200K for GLM-4.6.
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-4.6 | Δ | Muse Spark |
|---|---|---|---|
| Math | GLM-4.63.4 | Margin→ 29.5 | Muse Spark32.9 |
| Agentic | GLM-4.6Not measured | MarginNo overlap | Muse Spark59.0 |
| Coding | GLM-4.6Not measured | MarginNo overlap | Muse Spark67.8 |
| Reasoning | GLM-4.6Not measured | MarginNo overlap | Muse Spark42.5 |
| Knowledge | GLM-4.6Not measured | MarginNo overlap | Muse Spark50.4 |
| Multimodal | GLM-4.6Not measured | MarginNo overlap | Muse Spark82.5 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 3.819%B 39.000%Winner: Muse SparkΔ 35.2FrontierMath v2 (Tiers 1-3): GLM-4.6 scored 3.819%; Muse Spark scored 39.000%. Muse Spark wins this benchmark. - Source ↗
FrontierMath v2 (Tier 4)
MathA 2.128%B 14.600%Winner: Muse SparkΔ 12.5FrontierMath v2 (Tier 4): GLM-4.6 scored 2.128%; Muse Spark scored 14.600%. Muse Spark wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-4.6 | Muse Spark | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-4.6Not available | Muse SparkNot available | A complete price comparison is not available. |
| Generation speedtokens per second | GLM-4.6Not available | Muse SparkNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-4.6Not available | Muse SparkNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-4.6200K | Muse Spark262K | Muse Spark lists the larger context window. |
Benchmark Deep Dive
Agentic8 benchmarks
| Benchmark | GLM-4.6 | Muse Spark | Result |
|---|---|---|---|
| τ²-bench resultsSource | 76.9% | 91.5% | Muse Spark leads |
| Terminal-Bench 2.0Source | — | 59% | Not comparable |
| DeepSearchQASource | — | 74.8% | Not comparable |
| CyberGymSource | — | 43.5% | Not comparable |
| Claw-EvalSource | — | 63.8% | Not comparable |
| AA Agentic IndexSource | — | 28.7% | Not comparable |
| GDPval-AASource | — | 32.2% | Not comparable |
| GDPval-AASource | — | 1144 | Not comparable |
Coding6 benchmarks
Reasoning3 benchmarks
Knowledge11 benchmarks
| Benchmark | GLM-4.6 | Muse Spark | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 23.0% | 43.1% | Muse Spark leads |
| AA-GPQA DiamondSource | 63.2% | 88.4% | Muse Spark leads |
| AA-HLESource | 5.2% | 39.9% | Muse Spark leads |
| AA-Omniscience IndexSource | -31.6% | 4.1% | Muse Spark leads |
| AA-Omniscience AccuracySource | 20.8% | 44.6% | Muse Spark leads |
| AA-Omniscience Hallucination RateSource | 66.1% | 73.2% | GLM-4.6 leads |
| GPQA-DSource | — | 89.5% | Not comparable |
| HLESource | — | 50.4% | Not comparable |
| HLE w/o toolsSource | — | 42.8% | Not comparable |
| HealthBench HardSource | — | 42.8% | Not comparable |
| MedXpertQA (Text)Source | — | 52.6% | Not comparable |
MathMuse Spark wins2 benchmarks
Multimodal8 benchmarks
| Benchmark | GLM-4.6 | Muse Spark | Result |
|---|---|---|---|
| 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 |
Inst. Following1 benchmarks
| Benchmark | GLM-4.6 | Muse Spark | Result |
|---|---|---|---|
| AA-IFBenchSource | 36.7% | 75.9% | Muse Spark leads |
Frequently Asked Questions (2)
Which is better, GLM-4.6 or Muse Spark?
Muse Spark is ahead on BenchLM's BenchAlign leaderboard, 71.04 to 55.12. The biggest single separator in this matchup is FrontierMath v2 (Tiers 1-3), where the scores are 3.819% and 39.000%.
Which is better for math, GLM-4.6 or Muse Spark?
Muse Spark has the edge for math in this comparison, averaging 32.9 versus 3.4. Inside this category, FrontierMath v2 (Tiers 1-3) is the benchmark that creates the most daylight between them.
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