Model comparison
GLM-4.7 vs GPT-5.6 Sol
Head-to-head evidence from 20 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-4.7 #42 (Supported); GPT-5.6 Sol #3 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-4.7 and GPT-5.6 Sol share 20 comparable benchmark results. 4 of 8 categories are comparable. 10 results are unique to GLM-4.7; 26 to GPT-5.6 Sol.
Updated July 23, 2026- Shared results
- 20
- GLM-4.7 only
- 10
- GPT-5.6 Sol only
- 26
- Comparable categories
- 4 / 8
Pick GPT-5.6 Sol if you want the stronger benchmark profile. GLM-4.7 only becomes the better choice if coding is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 20 shared benchmark results across 6 evidence categories; 4 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-5.6 Sol is clearly ahead on the BenchAlign aggregate, 81.96 to 61.16. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.6 Sol's sharpest advantage is in mathematics, where it averages 87.5 against 1.8. The single biggest benchmark swing on the page is FrontierMath v2 (Tiers 1-3), 2.439% to 89.000%. GLM-4.7 does hit back in coding, so the answer changes if that is the part of the workload you care about most.
GPT-5.6 Sol is also the more expensive model on tokens at $5.00 input / $30.00 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-5.6 Sol 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-5.6 Sol |
|---|---|---|---|
| Math | GLM-4.71.8 | Margin→ 85.7 | GPT-5.6 Sol87.5 |
| Agentic | GLM-4.745.7 | Margin→ 46.3 | GPT-5.6 Sol92.0 |
| Knowledge | GLM-4.751.8 | Margin→ 42.8 | GPT-5.6 Sol94.6 |
| Coding | GLM-4.775.4 | Margin← 10.8 | GPT-5.6 Sol64.6 |
| Multimodal | GLM-4.7Not measured | MarginNo overlap | GPT-5.6 Sol83.0 |
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 89.000%Winner: GPT-5.6 SolΔ 86.6FrontierMath v2 (Tiers 1-3): GLM-4.7 scored 2.439%; GPT-5.6 Sol scored 89.000%. GPT-5.6 Sol wins this benchmark. - Source ↗
FrontierMath v2 (Tier 4)
MathA 0.000%B 83.000%Winner: GPT-5.6 SolΔ 83FrontierMath v2 (Tier 4): GLM-4.7 scored 0.000%; GPT-5.6 Sol scored 83.000%. GPT-5.6 Sol wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 41%B 91.9%Winner: GPT-5.6 SolΔ 50.9Terminal-Bench 2.0: GLM-4.7 scored 41%; GPT-5.6 Sol scored 91.9%. GPT-5.6 Sol wins this benchmark. - Source ↗
BrowseComp
AgenticA 52%B 92.2%Winner: GPT-5.6 SolΔ 40.2BrowseComp: GLM-4.7 scored 52%; GPT-5.6 Sol scored 92.2%. GPT-5.6 Sol wins this benchmark. - Source ↗
GPQA
KnowledgeA 85.7%B 94.6%Winner: GPT-5.6 SolΔ 8.9GPQA: GLM-4.7 scored 85.7%; GPT-5.6 Sol scored 94.6%. GPT-5.6 Sol 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-5.6 Sol | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-4.7$0 input / $0 output | GPT-5.6 Sol$5 input / $30 output | GLM-4.7 has the lower combined listed price. |
| Generation speedtokens per second | GLM-4.782 tok/s | GPT-5.6 SolNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-4.71.10 s | GPT-5.6 SolNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-4.7200K | GPT-5.6 Sol1M | GPT-5.6 Sol lists the larger context window. |
Benchmark Deep Dive
AgenticGPT-5.6 Sol wins19 benchmarks
| Benchmark | GLM-4.7 | GPT-5.6 Sol | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 41% | 91.9% | GPT-5.6 Sol leads |
| BrowseCompSource | 52% | 92.2% | GPT-5.6 Sol leads |
| VITA-BenchSource | 15.5% | — | Not comparable |
| AA Agentic IndexSource | 25.4% | 54.0% | GPT-5.6 Sol leads |
| τ²-bench resultsSource | 95.9% | 85.1% | GLM-4.7 leads |
| Gert LabsSource | 39.95% | — | Not comparable |
| GDPval-AASource | 33.3% | 61.8% | GPT-5.6 Sol leads |
| GDPval-AASource | 1165 | 1736 | GPT-5.6 Sol leads |
| OSWorld 2.0Source | — | 62.6% | Not comparable |
| CyberGymSource | — | 84.5% | Not comparable |
| ExploitGymSource | — | 33.7% | Not comparable |
| ToolathlonSource | — | 58% | Not comparable |
| AA BriefcaseSource | — | 1501 | Not comparable |
| AA ITBenchSource | — | 56.2% | Not comparable |
| AA Tau3 BankingSource | — | 33.0% | Not comparable |
| AA AutomationBenchSource | — | 51.2% | Not comparable |
| AA Harvey LABSource | — | 87.2% | Not comparable |
| terminalBenchHardSource | — | 65.9% | Not comparable |
| aaTerminalBench21Source | — | 88% | Not comparable |
CodingGLM-4.7 wins12 benchmarks
| Benchmark | GLM-4.7 | GPT-5.6 Sol | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 73.8% | — | Not comparable |
| LiveCodeBenchSource | 84.9% | — | Not comparable |
| SWE-RebenchSource | 58.7% | — | Not comparable |
| AA Coding IndexSource | 45.3% | 77.4% | GPT-5.6 Sol leads |
| AA-SciCodeSource | 45.1% | 56.1% | GPT-5.6 Sol leads |
| AA LiveCodeBenchSource | 89.4% | — | Not comparable |
| SWE-bench ProSource | — | 64.6% | Not comparable |
| Terminal-Bench 2.0Source | — | 91.9% | Not comparable |
| deepSweSource | — | 72.7% | Not comparable |
| FrontierCode 1.1 ExtendedSource | — | 60.6% | Not comparable |
| cursorBench32Source | — | 67.2% | Not comparable |
| VulcanBench v3Source | — | 87.0% | Not comparable |
Reasoning4 benchmarks
KnowledgeGPT-5.6 Sol wins12 benchmarks
| Benchmark | GLM-4.7 | GPT-5.6 Sol | Result |
|---|---|---|---|
| GPQASource | 85.7% | 94.6% | GPT-5.6 Sol leads |
| MMLU-ProSource | 84.3% | — | Not comparable |
| HLESource | 24.8% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 33.7% | 58.9% | GPT-5.6 Sol leads |
| AA-GPQA DiamondSource | 85.9% | 94.1% | GPT-5.6 Sol leads |
| AA-HLESource | 25.1% | 47.2% | GPT-5.6 Sol leads |
| AA-Omniscience IndexSource | -34.6% | 21.7% | GPT-5.6 Sol leads |
| AA-Omniscience AccuracySource | 29.3% | 58.5% | GPT-5.6 Sol leads |
| AA-Omniscience Hallucination RateSource | 90.3% | 88.8% | GPT-5.6 Sol leads |
| GPQA-DSource | — | 94.6% | Not comparable |
| HealthBench ProfessionalSource | — | 60.5% | Not comparable |
| HealthBench HardSource | — | 33.1% | Not comparable |
MathGPT-5.6 Sol wins4 benchmarks
Multimodal4 benchmarks
Inst. Following1 benchmarks
| Benchmark | GLM-4.7 | GPT-5.6 Sol | Result |
|---|---|---|---|
| AA-IFBenchSource | 67.9% | 72.7% | GPT-5.6 Sol leads |
Frequently Asked Questions (5)
Which is better, GLM-4.7 or GPT-5.6 Sol?
GPT-5.6 Sol is ahead on BenchLM's BenchAlign leaderboard, 81.96 to 61.16. The biggest single separator in this matchup is FrontierMath v2 (Tiers 1-3), where the scores are 2.439% and 89.000%.
Which is better for knowledge tasks, GLM-4.7 or GPT-5.6 Sol?
GPT-5.6 Sol has the edge for knowledge tasks in this comparison, averaging 94.6 versus 51.8. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
Which is better for coding, GLM-4.7 or GPT-5.6 Sol?
GLM-4.7 has the edge for coding in this comparison, averaging 75.4 versus 64.6. Inside this category, AA Coding Index is the benchmark that creates the most daylight between them.
Which is better for math, GLM-4.7 or GPT-5.6 Sol?
GPT-5.6 Sol has the edge for math in this comparison, averaging 87.5 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-5.6 Sol?
GPT-5.6 Sol has the edge for agentic tasks in this comparison, averaging 92 versus 45.7. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
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