Model comparison
Claude Opus 4.7 vs GLM-5.2
Head-to-head evidence from 13 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Claude Opus 4.7 #12 (Supported); GLM-5.2 #37 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Opus 4.7 and GLM-5.2 share 13 comparable benchmark results. 1 of 8 categories are comparable. 8 results are unique to Claude Opus 4.7; 30 to GLM-5.2.
Updated July 23, 2026- Shared results
- 13
- Claude Opus 4.7 only
- 8
- GLM-5.2 only
- 30
- Comparable categories
- 1 / 8
Pick Claude Opus 4.7 if you want the stronger benchmark profile. GLM-5.2 only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 13 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
Claude Opus 4.7 is clearly ahead on the BenchAlign aggregate, 71.94 to 63.96. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Claude Opus 4.7 is also the more expensive model on tokens at $5.00 input / $25.00 output per 1M tokens, versus $1.40 input / $4.40 output per 1M tokens for GLM-5.2. That is roughly 5.7x on output cost alone. GLM-5.2 is the reasoning model in the pair, while Claude Opus 4.7 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 Opus 4.7 | Δ | GLM-5.2 |
|---|---|---|---|
| Math | Claude Opus 4.738.6 | Margin→ 57.3 | GLM-5.295.9 |
| Agentic | Claude Opus 4.7Not measured | MarginNo overlap | GLM-5.281.0 |
| Coding | Claude Opus 4.7Not measured | MarginNo overlap | GLM-5.262.1 |
| Knowledge | Claude Opus 4.7Not measured | MarginNo overlap | GLM-5.259.6 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Opus 4.7 | GLM-5.2 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.7$5 input / $25 output | GLM-5.2$1.4 input / $4.4 output | GLM-5.2 has the lower combined listed price. |
| Generation speedtokens per second | Claude Opus 4.7Not available | GLM-5.2Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Opus 4.7Not available | GLM-5.2Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Opus 4.71M | GLM-5.21M | Listed context windows are equal. |
Benchmark Deep Dive
Agentic19 benchmarks
| Benchmark | Claude Opus 4.7 | GLM-5.2 | Result |
|---|---|---|---|
| τ²-bench resultsSource | 74% | 99.1% | GLM-5.2 leads |
| Gert LabsSource | 65.59% | — | Not comparable |
| ResearchClawBenchSource | 20.7% | 20.7% | Tie |
| OSWorld 2.0Source | 13.9% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 81% | Not comparable |
| MCP AtlasSource | — | 76.8% | Not comparable |
| ToolathlonSource | — | 48.2% | Not comparable |
| AA Agentic IndexSource | — | 43.1% | Not comparable |
| GDPval-AASource | — | 50.7% | Not comparable |
| GDPval-AASource | — | 1514 | Not comparable |
| APEX-Agents-AASource | — | 33.7% | Not comparable |
| AA BriefcaseSource | — | 1260 | Not comparable |
| AA AutomationBenchSource | — | 27.8% | Not comparable |
| AA EnterpriseOps-GymSource | — | 42.7% | Not comparable |
| AA Harvey LABSource | — | 91.0% | Not comparable |
| AA ITBenchSource | — | 42.7% | Not comparable |
| AA Tau3 BankingSource | — | 26.8% | Not comparable |
| terminalBenchHardSource | — | 50.8% | Not comparable |
| aaTerminalBench21Source | — | 77.9% | Not comparable |
Coding10 benchmarks
| Benchmark | Claude Opus 4.7 | GLM-5.2 | Result |
|---|---|---|---|
| Vibe Code BenchSource | 71.00% | — | Not comparable |
| React Native EvalsSource | 82.8% | — | Not comparable |
| AA-SciCodeSource | 50.1% | 50.5% | GLM-5.2 leads |
| FrontierCode 1.1 MainSource | 38.5% | — | Not comparable |
| SWE-bench ProSource | — | 62.1% | Not comparable |
| NL2RepoSource | — | 48.9% | Not comparable |
| Terminal-Bench 2.0Source | — | 81.0% | Not comparable |
| ProgramBenchSource | — | 63.7% | Not comparable |
| cursorBench32Source | — | 55.0% | Not comparable |
| AA Coding IndexSource | — | 68.8% | Not comparable |
Reasoning2 benchmarks
Knowledge11 benchmarks
| Benchmark | Claude Opus 4.7 | GLM-5.2 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 42.7% | 51.1% | GLM-5.2 leads |
| AA-GPQA DiamondSource | 88.5% | 89.5% | GLM-5.2 leads |
| AA-HLESource | 31.2% | 40.1% | GLM-5.2 leads |
| AA-Omniscience IndexSource | 14.2% | 4.0% | Claude Opus 4.7 leads |
| AA-Omniscience AccuracySource | 43.5% | 25.1% | Claude Opus 4.7 leads |
| AA-Omniscience Hallucination RateSource | 51.9% | 28.1% | GLM-5.2 leads |
| GPQASource | — | 91.2% | Not comparable |
| GPQA-DSource | — | 91.2% | Not comparable |
| HLESource | — | 54.7% | Not comparable |
| HLE w/o toolsSource | — | 40.5% | Not comparable |
| AA Openness IndexSource | — | 44.4% | Not comparable |
MathGLM-5.2 wins6 benchmarks
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | Claude Opus 4.7 | GLM-5.2 | Result |
|---|---|---|---|
| AA-IFBenchSource | 43.6% | 73.3% | GLM-5.2 leads |
Frequently Asked Questions (2)
Which is better, Claude Opus 4.7 or GLM-5.2?
Claude Opus 4.7 is ahead on BenchLM's BenchAlign leaderboard, 71.94 to 63.96.
Which is better for math, Claude Opus 4.7 or GLM-5.2?
GLM-5.2 has the edge for math in this comparison, averaging 95.9 versus 38.6. Claude Opus 4.7 stays close enough that the answer can still flip depending on your workload.
Related Comparisons
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.