Model comparison
Claude Opus 4.7 vs GLM-5.1
Head-to-head evidence from 18 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Verified leaderboard positions: Claude Opus 4.7 unranked; GLM-5.1 #12
BenchAlign evidence: Claude Opus 4.7 supported; GLM-5.1 supported. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Opus 4.7 and GLM-5.1 share 18 comparable benchmark results. 1 of 8 categories are comparable. 4 results are unique to Claude Opus 4.7; 19 to GLM-5.1.
Updated July 15, 2026- Shared results
- 18
- Claude Opus 4.7 only
- 4
- GLM-5.1 only
- 19
- Comparable categories
- 1 / 8
Pick Claude Opus 4.7 if you want the stronger benchmark profile. GLM-5.1 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 18 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
Claude Opus 4.7 has the cleaner provisional overall profile here, landing at 69 versus 67. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
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-5.1. That is roughly 5.7x on output cost alone. GLM-5.1 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. Claude Opus 4.7 gives you the larger context window at 1M, compared with 203K for GLM-5.1.
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-5.1 |
|---|---|---|---|
| Math | Claude Opus 4.738.6 | Margin→ 23.4 | GLM-5.162.0 |
| Agentic | Claude Opus 4.7Not measured | MarginNo overlap | GLM-5.165.4 |
| Coding | Claude Opus 4.7Not measured | MarginNo overlap | GLM-5.161.3 |
| Knowledge | Claude Opus 4.7Not measured | MarginNo overlap | GLM-5.152.3 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
FrontierMath v2 (Tier 4)
MathA 22.917%B 12.500%Winner: Claude Opus 4.7Δ 10.4FrontierMath v2 (Tier 4): Claude Opus 4.7 scored 22.917%; GLM-5.1 scored 12.500%. Claude Opus 4.7 wins this benchmark. - Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 43.793%B 33.448%Winner: Claude Opus 4.7Δ 10.3FrontierMath v2 (Tiers 1-3): Claude Opus 4.7 scored 43.793%; GLM-5.1 scored 33.448%. Claude Opus 4.7 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Claude Opus 4.7 | GLM-5.1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.7$5 input / $25 output | GLM-5.1$1.4 input / $4.4 output | GLM-5.1 has the lower combined listed price. |
| Generation speedtokens per second | Claude Opus 4.7Not available | GLM-5.1Not available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Opus 4.7Not available | GLM-5.1Not available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Opus 4.71M | GLM-5.1203K | Claude Opus 4.7 lists the larger context window. |
Benchmark Deep Dive
Agentic13 benchmarks
| Benchmark | Claude Opus 4.7 | GLM-5.1 | Result |
|---|---|---|---|
| τ²-bench resultsSource | 74% | 97.7% | GLM-5.1 leads |
| Gert LabsSource | 65.59% | 60.11% | Claude Opus 4.7 leads |
| ResearchClawBenchSource | 20.7% | 18.2% | Claude Opus 4.7 leads |
| OSWorld 2.0Source | 13.9% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 63.5% | Not comparable |
| BrowseCompSource | — | 68% | Not comparable |
| τ³-bench resultsSource | — | 70.6% | Not comparable |
| MCP AtlasSource | — | 71.8% | Not comparable |
| CyberGymSource | — | 68.7% | Not comparable |
| Claw-EvalSource | — | 62.3% | Not comparable |
| AA Agentic IndexSource | — | 29.9% | Not comparable |
| GDPval-AASource | — | 37.8% | Not comparable |
| GDPval-AASource | — | 1257 | Not comparable |
Coding9 benchmarks
| Benchmark | Claude Opus 4.7 | GLM-5.1 | Result |
|---|---|---|---|
| Vibe Code BenchSource | 71.00% | 31.46% | Claude Opus 4.7 leads |
| React Native EvalsSource | 82.8% | — | Not comparable |
| Terminal-Bench HardSource | 54.5% | 43.2% | Claude Opus 4.7 leads |
| AA-SciCodeSource | 50.1% | 43.8% | Claude Opus 4.7 leads |
| FrontierCodeSource | 38.5% | — | Not comparable |
| SWE-bench ProSource | — | 58.4% | Not comparable |
| NL2RepoSource | — | 42.7% | Not comparable |
| SWE-RebenchSource | — | 62.7% | Not comparable |
| AA Coding IndexSource | — | 55.8% | Not comparable |
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | Claude Opus 4.7 | GLM-5.1 | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 42.7% | 40.2% | Claude Opus 4.7 leads |
| AA-GPQA DiamondSource | 88.5% | 86.8% | Claude Opus 4.7 leads |
| AA-HLESource | 31.2% | 28.0% | Claude Opus 4.7 leads |
| AA-Omniscience IndexSource | 14.2% | 1.9% | Claude Opus 4.7 leads |
| AA-Omniscience AccuracySource | 43.5% | 24.2% | Claude Opus 4.7 leads |
| AA-Omniscience Hallucination RateSource | 51.9% | 29.4% | GLM-5.1 leads |
| GPQA-DSource | — | 86.2% | Not comparable |
| HLESource | — | 52.3% | Not comparable |
MathGLM-5.1 wins6 benchmarks
| Benchmark | Claude Opus 4.7 | GLM-5.1 | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 43.793% | 33.448% | Claude Opus 4.7 leads |
| FrontierMath v2 (Tier 4)Source | 22.917% | 12.500% | Claude Opus 4.7 leads |
| AIME26Source | — | 95.3% | Not comparable |
| HMMT Nov 2025Source | — | 94.0% | Not comparable |
| HMMT Feb 2026Source | — | 82.6% | Not comparable |
| MMAnswerBenchSource | — | 83.8% | Not comparable |
Multimodal2 benchmarks
Inst. Following1 benchmarks
| Benchmark | Claude Opus 4.7 | GLM-5.1 | Result |
|---|---|---|---|
| AA-IFBenchSource | 43.6% | 76.3% | GLM-5.1 leads |
Frequently Asked Questions (2)
Which is better, Claude Opus 4.7 or GLM-5.1?
Claude Opus 4.7 is ahead on BenchLM's provisional leaderboard, 69 to 67. The biggest single separator in this matchup is FrontierMath v2 (Tier 4), where the scores are 22.917% and 12.500%.
Which is better for math, Claude Opus 4.7 or GLM-5.1?
GLM-5.1 has the edge for math in this comparison, averaging 62 versus 38.6. Inside this category, FrontierMath v2 (Tier 4) 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
The AI models change fast. We track them for you.
A weekly brief for engineers and researchers covering new models, ranking shifts, and pricing changes.
Free. No spam. Unsubscribe anytime.