Model comparison
Agents-A1 vs GLM-4.7
Head-to-head evidence from 3 shared benchmark results across 2 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: Agents-A1 unranked; GLM-4.7 #32
BenchAlign evidence: Agents-A1 not scored; GLM-4.7 supported. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Agents-A1 and GLM-4.7 share 3 comparable benchmark results. 2 of 8 categories are comparable. 3 results are unique to Agents-A1; 28 to GLM-4.7.
Updated July 16, 2026- Shared results
- 3
- Agents-A1 only
- 3
- GLM-4.7 only
- 28
- Comparable categories
- 2 / 8
Treat this as a split decision. Agents-A1 makes more sense if agentic is the priority or you need the larger 262K context window; GLM-4.7 is the better fit if knowledge is the priority.
Confidence note. This is a partial-evidence comparison with 3 shared benchmark results across 2 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Agents-A1 and GLM-4.7 finish on the same provisional overall score, so this is less about a single winner and more about where the edge shows up. The provisional headline says tie; the benchmark table is where the real choice happens.
Agents-A1 gives you the larger context window at 262K, 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 | Agents-A1 | Δ | GLM-4.7 |
|---|---|---|---|
| Agentic | Agents-A175.5 | Margin← 29.8 | GLM-4.745.7 |
| Knowledge | Agents-A147.6 | Margin→ 4.5 | GLM-4.752.1 |
| Coding | Agents-A1Not measured | MarginNo overlap | GLM-4.775.4 |
| Reasoning | Agents-A160.2 | MarginNo overlap | GLM-4.7Not measured |
| Math | Agents-A1Not measured | MarginNo overlap | GLM-4.71.8 |
| Inst. Following | Agents-A194.8 | MarginNo overlap | GLM-4.7Not measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Agents-A1 | GLM-4.7 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Agents-A1Not available | GLM-4.7$0 input / $0 output | A complete price comparison is not available. |
| Generation speedtokens per second | Agents-A1Not available | GLM-4.782 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Agents-A1Not available | GLM-4.71.10 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Agents-A1262K | GLM-4.7200K | Agents-A1 lists the larger context window. |
Benchmark Deep Dive
AgenticAgents-A1 wins9 benchmarks
| Benchmark | Agents-A1 | GLM-4.7 | Result |
|---|---|---|---|
| BrowseCompSource | 75.5% | 52% | Agents-A1 leads |
| HLE w/ toolsSource | 47.6% | — | Not comparable |
| VITA-BenchSource | 38.8% | 15.5% | Agents-A1 leads |
| Terminal-Bench 2.0Source | — | 41% | Not comparable |
| AA Agentic IndexSource | — | 25.4% | Not comparable |
| τ²-bench resultsSource | — | 95.9% | Not comparable |
| Gert LabsSource | — | 39.95% | Not comparable |
| GDPval-AASource | — | 33.3% | Not comparable |
| GDPval-AASource | — | 1165 | Not comparable |
Coding7 benchmarks
| Benchmark | Agents-A1 | GLM-4.7 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | — | 73.8% | Not comparable |
| LiveCodeBenchSource | — | 84.9% | Not comparable |
| SWE-RebenchSource | — | 58.7% | Not comparable |
| AA Coding IndexSource | — | 45.3% | Not comparable |
| Terminal-Bench HardSource | — | 31.8% | Not comparable |
| AA-SciCodeSource | — | 45.1% | Not comparable |
| AA LiveCodeBenchSource | — | 89.4% | Not comparable |
Reasoning3 benchmarks
KnowledgeGLM-4.7 wins9 benchmarks
| Benchmark | Agents-A1 | GLM-4.7 | Result |
|---|---|---|---|
| HLESource | 47.6% | 24.8% | Agents-A1 leads |
| GPQASource | — | 85.7% | Not comparable |
| MMLU-ProSource | — | 84.3% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 33.7% | Not comparable |
| AA-GPQA DiamondSource | — | 85.9% | Not comparable |
| AA-HLESource | — | 25.1% | Not comparable |
| AA-Omniscience IndexSource | — | -34.6% | Not comparable |
| AA-Omniscience AccuracySource | — | 29.3% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 90.3% | Not comparable |
Math3 benchmarks
Multimodal1 benchmarks
| Benchmark | Agents-A1 | GLM-4.7 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | — | 1260 | Not comparable |
Frequently Asked Questions (3)
Which is better, Agents-A1 or GLM-4.7?
Agents-A1 and GLM-4.7 are tied on the provisional overall score, so the right pick depends on which category matters most for your use case.
Which is better for knowledge tasks, Agents-A1 or GLM-4.7?
GLM-4.7 has the edge for knowledge tasks in this comparison, averaging 52.1 versus 47.6. Inside this category, HLE is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, Agents-A1 or GLM-4.7?
Agents-A1 has the edge for agentic tasks in this comparison, averaging 75.5 versus 45.7. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
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