Model comparison
GLM-4.6 vs Llama 4 Maverick
Head-to-head evidence from 12 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); Llama 4 Maverick #191 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-4.6 and Llama 4 Maverick share 12 comparable benchmark results. 1 of 8 categories are comparable. 2 results are unique to GLM-4.6; 6 to Llama 4 Maverick.
Updated July 23, 2026- Shared results
- 12
- GLM-4.6 only
- 2
- Llama 4 Maverick only
- 6
- Comparable categories
- 1 / 8
Pick GLM-4.6 if you want the stronger benchmark profile. Llama 4 Maverick only becomes the better choice if you need the larger 1M context window or you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 12 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
GLM-4.6 is clearly ahead on the BenchAlign aggregate, 55.12 to 23.49. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-4.6's sharpest advantage is in mathematics, where it averages 3.4 against 0.7. The single biggest benchmark swing on the page is FrontierMath v2 (Tiers 1-3), 3.819% to 0.690%.
GLM-4.6 is the reasoning model in the pair, while Llama 4 Maverick 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. Llama 4 Maverick gives you the larger context window at 1M, 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 | Llama 4 Maverick |
|---|---|---|---|
| Math | GLM-4.63.4 | Margin← 2.7 | Llama 4 Maverick0.7 |
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 0.690%Winner: GLM-4.6Δ 3.1FrontierMath v2 (Tiers 1-3): GLM-4.6 scored 3.819%; Llama 4 Maverick scored 0.690%. GLM-4.6 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-4.6 | Llama 4 Maverick | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-4.6Not available | Llama 4 Maverick$0 input / $0 output | A complete price comparison is not available. |
| Generation speedtokens per second | GLM-4.6Not available | Llama 4 Maverick121 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-4.6Not available | Llama 4 Maverick0.95 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-4.6200K | Llama 4 Maverick1M | Llama 4 Maverick lists the larger context window. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding3 benchmarks
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | GLM-4.6 | Llama 4 Maverick | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 23.0% | 14.3% | GLM-4.6 leads |
| AA-GPQA DiamondSource | 63.2% | 67.1% | Llama 4 Maverick leads |
| AA-HLESource | 5.2% | 4.8% | GLM-4.6 leads |
| AA-Omniscience IndexSource | -31.6% | -41.8% | GLM-4.6 leads |
| AA-Omniscience AccuracySource | 20.8% | 24.3% | Llama 4 Maverick leads |
| AA-Omniscience Hallucination RateSource | 66.1% | 87.3% | GLM-4.6 leads |
MathGLM-4.6 wins2 benchmarks
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | GLM-4.6 | Llama 4 Maverick | Result |
|---|---|---|---|
| AA-IFBenchSource | 36.7% | 43.0% | Llama 4 Maverick leads |
Frequently Asked Questions (2)
Which is better, GLM-4.6 or Llama 4 Maverick?
GLM-4.6 is ahead on BenchLM's BenchAlign leaderboard, 55.12 to 23.49. The biggest single separator in this matchup is FrontierMath v2 (Tiers 1-3), where the scores are 3.819% and 0.690%.
Which is better for math, GLM-4.6 or Llama 4 Maverick?
GLM-4.6 has the edge for math in this comparison, averaging 3.4 versus 0.7. Inside this category, FrontierMath v2 (Tiers 1-3) is the benchmark that creates the most daylight between them.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
Related Comparisons
Explore More
Choose a model with this week’s evidence
Join 2,000+ readers for ranking moves, pricing changes, and the claims that still need proof.
One email each week. Unsubscribe anytime.