Model comparison
GLM-4.7 vs GPT-5.5 Pro
Head-to-head evidence from 5 shared benchmark results across 4 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-4.7 #42 (Supported); GPT-5.5 Pro #38 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-4.7 and GPT-5.5 Pro share 5 comparable benchmark results. 3 of 8 categories are comparable. 25 results are unique to GLM-4.7; 2 to GPT-5.5 Pro.
Updated July 22, 2026- Shared results
- 5
- GLM-4.7 only
- 25
- GPT-5.5 Pro only
- 2
- Comparable categories
- 3 / 8
Pick GPT-5.5 Pro if you want the stronger benchmark profile. GLM-4.7 only becomes the better choice if you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 5 shared benchmark results across 4 evidence categories; 3 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-5.5 Pro has the cleaner BenchAlign overall profile here, landing at 63.69 versus 61.16. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
GPT-5.5 Pro's sharpest advantage is in mathematics, where it averages 48.1 against 1.8. The single biggest benchmark swing on the page is FrontierMath v2 (Tiers 1-3), 2.439% to 51.000%.
GPT-5.5 Pro is also the more expensive model on tokens at $30.00 input / $180.00 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. GPT-5.5 Pro 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 | GPT-5.5 Pro |
|---|---|---|---|
| Math | GLM-4.71.8 | Margin→ 46.3 | GPT-5.5 Pro48.1 |
| Agentic | GLM-4.745.7 | Margin→ 44.4 | GPT-5.5 Pro90.1 |
| Knowledge | GLM-4.751.8 | Margin→ 5.4 | GPT-5.5 Pro57.2 |
| Coding | GLM-4.775.4 | MarginNo overlap | GPT-5.5 ProNot 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 51.000%Winner: GPT-5.5 ProΔ 48.6FrontierMath v2 (Tiers 1-3): GLM-4.7 scored 2.439%; GPT-5.5 Pro scored 51.000%. GPT-5.5 Pro wins this benchmark. - Source ↗
FrontierMath v2 (Tier 4)
MathA 0.000%B 39.600%Winner: GPT-5.5 ProΔ 39.6FrontierMath v2 (Tier 4): GLM-4.7 scored 0.000%; GPT-5.5 Pro scored 39.600%. GPT-5.5 Pro wins this benchmark. - Source ↗
BrowseComp
AgenticA 52%B 90.1%Winner: GPT-5.5 ProΔ 38.1BrowseComp: GLM-4.7 scored 52%; GPT-5.5 Pro scored 90.1%. GPT-5.5 Pro wins this benchmark. - Source ↗
HLE
KnowledgeA 24.8%B 57.2%Winner: GPT-5.5 ProΔ 32.4HLE: GLM-4.7 scored 24.8%; GPT-5.5 Pro scored 57.2%. GPT-5.5 Pro wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-4.7 | GPT-5.5 Pro | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-4.7$0 input / $0 output | GPT-5.5 Pro$30 input / $180 output | GLM-4.7 has the lower combined listed price. |
| Generation speedtokens per second | GLM-4.782 tok/s | GPT-5.5 ProNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-4.71.10 s | GPT-5.5 ProNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-4.7200K | GPT-5.5 Pro1M | GPT-5.5 Pro lists the larger context window. |
Benchmark Deep Dive
AgenticGPT-5.5 Pro wins8 benchmarks
| Benchmark | GLM-4.7 | GPT-5.5 Pro | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 41% | — | Not comparable |
| BrowseCompSource | 52% | 90.1% | GPT-5.5 Pro leads |
| 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 |
Coding6 benchmarks
Reasoning2 benchmarks
KnowledgeGPT-5.5 Pro wins10 benchmarks
| Benchmark | GLM-4.7 | GPT-5.5 Pro | Result |
|---|---|---|---|
| GPQASource | 85.7% | — | Not comparable |
| MMLU-ProSource | 84.3% | — | Not comparable |
| HLESource | 24.8% | 57.2% | GPT-5.5 Pro leads |
| 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 |
| HLE w/o toolsSource | — | 43.1% | Not comparable |
MathGPT-5.5 Pro wins4 benchmarks
Multimodal1 benchmarks
| Benchmark | GLM-4.7 | GPT-5.5 Pro | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1255 | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GLM-4.7 | GPT-5.5 Pro | Result |
|---|---|---|---|
| AA-IFBenchSource | 67.9% | — | Not comparable |
Frequently Asked Questions (4)
Which is better, GLM-4.7 or GPT-5.5 Pro?
GPT-5.5 Pro is ahead on BenchLM's BenchAlign leaderboard, 63.69 to 61.16. The biggest single separator in this matchup is FrontierMath v2 (Tiers 1-3), where the scores are 2.439% and 51.000%.
Which is better for knowledge tasks, GLM-4.7 or GPT-5.5 Pro?
GPT-5.5 Pro has the edge for knowledge tasks in this comparison, averaging 57.2 versus 51.8. Inside this category, HLE is the benchmark that creates the most daylight between them.
Which is better for math, GLM-4.7 or GPT-5.5 Pro?
GPT-5.5 Pro has the edge for math in this comparison, averaging 48.1 versus 1.8. Inside this category, FrontierMath v2 (Tiers 1-3) is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, GLM-4.7 or GPT-5.5 Pro?
GPT-5.5 Pro has the edge for agentic tasks in this comparison, averaging 90.1 versus 45.7. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
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