Model comparison
GLM-4.7 vs Llama 4 Maverick
Head-to-head evidence from 17 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-4.7 #42 (Supported); Llama 4 Maverick #191 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-4.7 and Llama 4 Maverick share 17 comparable benchmark results. 1 of 8 categories are comparable. 13 results are unique to GLM-4.7; 1 to Llama 4 Maverick.
Updated July 20, 2026- Shared results
- 17
- GLM-4.7 only
- 13
- Llama 4 Maverick only
- 1
- Comparable categories
- 1 / 8
Pick GLM-4.7 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 17 shared benchmark results across 7 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-4.7 is clearly ahead on the BenchAlign aggregate, 61.16 to 23.49. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-4.7's sharpest advantage is in mathematics, where it averages 1.8 against 0.7. The single biggest benchmark swing on the page is FrontierMath v2 (Tiers 1-3), 2.439% to 0.690%.
GLM-4.7 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-4.7.
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-4.7 | Δ | Llama 4 Maverick |
|---|---|---|---|
| Math | GLM-4.71.8 | Margin← 1.1 | Llama 4 Maverick0.7 |
| Agentic | GLM-4.745.7 | MarginNo overlap | Llama 4 MaverickNot measured |
| Coding | GLM-4.775.4 | MarginNo overlap | Llama 4 MaverickNot measured |
| Knowledge | GLM-4.751.8 | MarginNo overlap | Llama 4 MaverickNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 2.439%B 0.690%Winner: GLM-4.7Δ 1.7FrontierMath v2 (Tiers 1-3): GLM-4.7 scored 2.439%; Llama 4 Maverick scored 0.690%. GLM-4.7 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-4.7 | Llama 4 Maverick | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-4.7$0 input / $0 output | Llama 4 Maverick$0 input / $0 output | Listed prices are equal. |
| Generation speedtokens per second | GLM-4.782 tok/s | Llama 4 Maverick121 tok/s | Llama 4 Maverick has the higher measured throughput. |
| First-answer latencyseconds to first token | GLM-4.71.10 s | Llama 4 Maverick0.95 s | Llama 4 Maverick reaches the first token sooner. |
| Context windowmaximum listed tokens | GLM-4.7200K | Llama 4 Maverick1M | Llama 4 Maverick lists the larger context window. |
Benchmark Deep Dive
Agentic8 benchmarks
| Benchmark | GLM-4.7 | Llama 4 Maverick | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 41% | — | Not comparable |
| BrowseCompSource | 52% | — | Not comparable |
| VITA-BenchSource | 15.5% | — | Not comparable |
| AA Agentic IndexSource | 25.4% | 1.3% | GLM-4.7 leads |
| τ²-bench resultsSource | 95.9% | 17.8% | GLM-4.7 leads |
| Gert LabsSource | 39.95% | — | Not comparable |
| GDPval-AASource | 33.3% | 0.0% | GLM-4.7 leads |
| GDPval-AASource | 1165 | -16 | GLM-4.7 leads |
Coding6 benchmarks
Reasoning2 benchmarks
Knowledge9 benchmarks
| Benchmark | GLM-4.7 | Llama 4 Maverick | Result |
|---|---|---|---|
| GPQASource | 85.7% | — | Not comparable |
| MMLU-ProSource | 84.3% | — | Not comparable |
| HLESource | 24.8% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 33.7% | 14.3% | GLM-4.7 leads |
| AA-GPQA DiamondSource | 85.9% | 67.1% | GLM-4.7 leads |
| AA-HLESource | 25.1% | 4.8% | GLM-4.7 leads |
| AA-Omniscience IndexSource | -34.6% | -41.8% | GLM-4.7 leads |
| AA-Omniscience AccuracySource | 29.3% | 24.3% | GLM-4.7 leads |
| AA-Omniscience Hallucination RateSource | 90.3% | 87.3% | Llama 4 Maverick leads |
MathGLM-4.7 wins3 benchmarks
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | GLM-4.7 | Llama 4 Maverick | Result |
|---|---|---|---|
| AA-IFBenchSource | 67.9% | 43.0% | GLM-4.7 leads |
Frequently Asked Questions (2)
Which is better, GLM-4.7 or Llama 4 Maverick?
GLM-4.7 is ahead on BenchLM's BenchAlign leaderboard, 61.16 to 23.49. The biggest single separator in this matchup is FrontierMath v2 (Tiers 1-3), where the scores are 2.439% and 0.690%.
Which is better for math, GLM-4.7 or Llama 4 Maverick?
GLM-4.7 has the edge for math in this comparison, averaging 1.8 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.
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