Model comparison
Claude 4.1 Opus vs GLM-4.7
Head-to-head evidence from 3 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude 4.1 Opus #142 (Supported); GLM-4.7 #42 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude 4.1 Opus and GLM-4.7 share 3 comparable benchmark results. 1 of 8 categories are comparable. 1 result is unique to Claude 4.1 Opus; 27 to GLM-4.7.
Updated July 22, 2026- Shared results
- 3
- Claude 4.1 Opus only
- 1
- GLM-4.7 only
- 27
- Comparable categories
- 1 / 8
Pick GLM-4.7 if you want the stronger benchmark profile. Claude 4.1 Opus only becomes the better choice if you would rather avoid the extra latency and token burn of a reasoning model.
Confidence note. This is a partial-evidence comparison with 3 shared benchmark results across 3 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 45.88. 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 coding, where it averages 75.4 against 74.5. The single biggest benchmark swing on the page is SWE-bench Verified, 74.5% to 73.8%.
Claude 4.1 Opus is also the more expensive model on tokens at $15.00 input / $75.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for GLM-4.7. That is roughly Infinityx on output cost alone. GLM-4.7 is the reasoning model in the pair, while Claude 4.1 Opus 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.
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 | Claude 4.1 Opus | Δ | GLM-4.7 |
|---|---|---|---|
| Coding | Claude 4.1 Opus74.5 | Margin→ 0.9 | GLM-4.775.4 |
| Agentic | Claude 4.1 OpusNot measured | MarginNo overlap | GLM-4.745.7 |
| Knowledge | Claude 4.1 OpusNot measured | MarginNo overlap | GLM-4.751.8 |
| Math | Claude 4.1 OpusNot measured | MarginNo overlap | GLM-4.71.8 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
SWE-bench Verified
CodingA 74.5%B 73.8%Winner: Claude 4.1 OpusΔ 0.7SWE-bench Verified: Claude 4.1 Opus scored 74.5%; GLM-4.7 scored 73.8%. Claude 4.1 Opus wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude 4.1 Opus | GLM-4.7 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude 4.1 Opus$15 input / $75 output | GLM-4.7$0 input / $0 output | GLM-4.7 has the lower combined listed price. |
| Generation speedtokens per second | Claude 4.1 Opus29 tok/s | GLM-4.782 tok/s | GLM-4.7 has the higher measured throughput. |
| First-answer latencyseconds to first token | Claude 4.1 Opus1.66 s | GLM-4.71.10 s | GLM-4.7 reaches the first token sooner. |
| Context windowmaximum listed tokens | Claude 4.1 Opus200K | GLM-4.7200K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic9 benchmarks
| Benchmark | Claude 4.1 Opus | GLM-4.7 | Result |
|---|---|---|---|
| JobBenchSource | 21.9% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 41% | Not comparable |
| BrowseCompSource | — | 52% | Not comparable |
| VITA-BenchSource | — | 15.5% | 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 |
CodingGLM-4.7 wins6 benchmarks
Reasoning2 benchmarks
Knowledge9 benchmarks
| Benchmark | Claude 4.1 Opus | GLM-4.7 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 28.2% | 33.7% | GLM-4.7 leads |
| GPQASource | — | 85.7% | Not comparable |
| MMLU-ProSource | — | 84.3% | Not comparable |
| HLESource | — | 24.8% | 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 | Claude 4.1 Opus | GLM-4.7 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1207 | 1255 | GLM-4.7 leads |
Inst. Following1 benchmarks
| Benchmark | Claude 4.1 Opus | GLM-4.7 | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 67.9% | Not comparable |
Frequently Asked Questions (2)
Which is better, Claude 4.1 Opus or GLM-4.7?
GLM-4.7 is ahead on BenchLM's BenchAlign leaderboard, 61.16 to 45.88. The biggest single separator in this matchup is SWE-bench Verified, where the scores are 74.5% and 73.8%.
Which is better for coding, Claude 4.1 Opus or GLM-4.7?
GLM-4.7 has the edge for coding in this comparison, averaging 75.4 versus 74.5. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
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