Model comparison
GLM-4.7 vs GPT-5.4
Head-to-head evidence from 23 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-4.7 #42 (Supported); GPT-5.4 #8 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-4.7 and GPT-5.4 share 23 comparable benchmark results. 4 of 8 categories are comparable. 7 results are unique to GLM-4.7; 29 to GPT-5.4.
Updated July 20, 2026- Shared results
- 23
- GLM-4.7 only
- 7
- GPT-5.4 only
- 29
- Comparable categories
- 4 / 8
Pick GPT-5.4 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 23 shared benchmark results across 7 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-5.4 is clearly ahead on the BenchAlign aggregate, 74.24 to 61.16. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-5.4's sharpest advantage is in mathematics, where it averages 42.5 against 1.8. The single biggest benchmark swing on the page is FrontierMath v2 (Tiers 1-3), 2.439% to 47.600%. 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-5.4 is also the more expensive model on tokens at $2.50 input / $15.00 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-5.4 gives you the larger context window at 1.05M, 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-5.4 |
|---|---|---|---|
| Math | GLM-4.71.8 | Margin→ 40.7 | GPT-5.442.5 |
| Agentic | GLM-4.745.7 | Margin→ 31.5 | GPT-5.477.2 |
| Coding | GLM-4.775.4 | Margin← 17.7 | GPT-5.457.7 |
| Knowledge | GLM-4.751.8 | Margin→ 5.8 | GPT-5.457.6 |
| Multimodal | GLM-4.7Not measured | MarginNo overlap | GPT-5.473.2 |
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 47.600%Winner: GPT-5.4Δ 45.2FrontierMath v2 (Tiers 1-3): GLM-4.7 scored 2.439%; GPT-5.4 scored 47.600%. GPT-5.4 wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 41%B 75.1%Winner: GPT-5.4Δ 34.1Terminal-Bench 2.0: GLM-4.7 scored 41%; GPT-5.4 scored 75.1%. GPT-5.4 wins this benchmark. - Source ↗
BrowseComp
AgenticA 52%B 82.7%Winner: GPT-5.4Δ 30.7BrowseComp: GLM-4.7 scored 52%; GPT-5.4 scored 82.7%. GPT-5.4 wins this benchmark. - Source ↗
HLE
KnowledgeA 24.8%B 52.1%Winner: GPT-5.4Δ 27.3HLE: GLM-4.7 scored 24.8%; GPT-5.4 scored 52.1%. GPT-5.4 wins this benchmark. - Source ↗
FrontierMath v2 (Tier 4)
MathA 0.000%B 27.100%Winner: GPT-5.4Δ 27.1FrontierMath v2 (Tier 4): GLM-4.7 scored 0.000%; GPT-5.4 scored 27.100%. GPT-5.4 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-5.4 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-4.7$0 input / $0 output | GPT-5.4$2.5 input / $15 output | GLM-4.7 has the lower combined listed price. |
| Generation speedtokens per second | GLM-4.782 tok/s | GPT-5.474 tok/s | GLM-4.7 has the higher measured throughput. |
| First-answer latencyseconds to first token | GLM-4.71.10 s | GPT-5.4151.79 s | GLM-4.7 reaches the first token sooner. |
| Context windowmaximum listed tokens | GLM-4.7200K | GPT-5.41.05M | GPT-5.4 lists the larger context window. |
Benchmark Deep Dive
AgenticGPT-5.4 wins18 benchmarks
| Benchmark | GLM-4.7 | GPT-5.4 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 41% | 75.1% | GPT-5.4 leads |
| BrowseCompSource | 52% | 82.7% | GPT-5.4 leads |
| VITA-BenchSource | 15.5% | — | Not comparable |
| AA Agentic IndexSource | 25.4% | 41.1% | GPT-5.4 leads |
| τ²-bench resultsSource | 95.9% | 87.1% | GLM-4.7 leads |
| Gert LabsSource | 39.95% | 64.89% | GPT-5.4 leads |
| GDPval-AASource | 33.3% | 44.7% | GPT-5.4 leads |
| GDPval-AASource | 1165 | 1395 | GPT-5.4 leads |
| CyberGymSource | — | 79.0% | Not comparable |
| OSWorld-VerifiedSource | — | 75% | Not comparable |
| MCP AtlasSource | — | 70.6% | Not comparable |
| ToolathlonSource | — | 54.6% | Not comparable |
| Claw-EvalSource | — | 60.3% | Not comparable |
| DeepSearchQASource | — | 73.6% | Not comparable |
| APEX-Agents-AASource | — | 33.3% | Not comparable |
| ResearchClawBenchSource | — | 15.3% | Not comparable |
| JobBenchSource | — | 38.9% | Not comparable |
| ExploitGymSource | — | 6.0% | Not comparable |
CodingGLM-4.7 wins10 benchmarks
| Benchmark | GLM-4.7 | GPT-5.4 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 73.8% | — | Not comparable |
| LiveCodeBenchSource | 84.9% | — | Not comparable |
| SWE-RebenchSource | 58.7% | — | Not comparable |
| AA Coding IndexSource | 45.3% | 71.0% | GPT-5.4 leads |
| AA-SciCodeSource | 45.1% | 56.6% | GPT-5.4 leads |
| AA LiveCodeBenchSource | 89.4% | — | Not comparable |
| LiveCodeBench ProSource | — | 87.5% | Not comparable |
| SWE-bench ProSource | — | 57.7% | Not comparable |
| React Native EvalsSource | — | 85.3% | Not comparable |
| Vibe Code BenchSource | — | 67.42% | Not comparable |
Reasoning2 benchmarks
KnowledgeGPT-5.4 wins14 benchmarks
| Benchmark | GLM-4.7 | GPT-5.4 | Result |
|---|---|---|---|
| GPQASource | 85.7% | 92.8% | GPT-5.4 leads |
| MMLU-ProSource | 84.3% | — | Not comparable |
| HLESource | 24.8% | 52.1% | GPT-5.4 leads |
| Artificial Analysis Intelligence IndexSource | 33.7% | 51.4% | GPT-5.4 leads |
| AA-GPQA DiamondSource | 85.9% | 92.0% | GPT-5.4 leads |
| AA-HLESource | 25.1% | 41.6% | GPT-5.4 leads |
| AA-Omniscience IndexSource | -34.6% | 5.7% | GPT-5.4 leads |
| AA-Omniscience AccuracySource | 29.3% | 50.0% | GPT-5.4 leads |
| AA-Omniscience Hallucination RateSource | 90.3% | 88.6% | GPT-5.4 leads |
| HLE w/o toolsSource | — | 39.8% | Not comparable |
| GPQA-DSource | — | 92.8% | Not comparable |
| HealthBench HardSource | — | 40.1% | Not comparable |
| MedXpertQA (Text)Source | — | 59.6% | Not comparable |
| HealthBench ProfessionalSource | — | 48.1% | Not comparable |
MathGPT-5.4 wins3 benchmarks
Multimodal11 benchmarks
| Benchmark | GLM-4.7 | GPT-5.4 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1258 | 1252 | GLM-4.7 leads |
| MMMU-ProSource | — | 81.2% | Not comparable |
| OfficeQA ProSource | — | 53.2% | Not comparable |
| MMMU-Pro w/ PythonSource | — | 82.1% | Not comparable |
| CharXivSource | — | 82.8% | Not comparable |
| ERQASource | — | 65.4% | Not comparable |
| SimpleVQASource | — | 61.1% | Not comparable |
| ScreenSpot ProSource | — | 85.4% | Not comparable |
| ZeroBenchSource | — | 41.0% | Not comparable |
| MedXpertQA (MM)Source | — | 77.1% | Not comparable |
| AA-MMMU-ProSource | — | 78.4% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GLM-4.7 | GPT-5.4 | Result |
|---|---|---|---|
| AA-IFBenchSource | 67.9% | 73.9% | GPT-5.4 leads |
Frequently Asked Questions (5)
Which is better, GLM-4.7 or GPT-5.4?
GPT-5.4 is ahead on BenchLM's BenchAlign leaderboard, 74.24 to 61.16. The biggest single separator in this matchup is FrontierMath v2 (Tiers 1-3), where the scores are 2.439% and 47.600%.
Which is better for knowledge tasks, GLM-4.7 or GPT-5.4?
GPT-5.4 has the edge for knowledge tasks in this comparison, averaging 57.6 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-5.4?
GLM-4.7 has the edge for coding in this comparison, averaging 75.4 versus 57.7. 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-5.4?
GPT-5.4 has the edge for math in this comparison, averaging 42.5 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-5.4?
GPT-5.4 has the edge for agentic tasks in this comparison, averaging 77.2 versus 45.7. Inside this category, GDPval-AA is the benchmark that creates the most daylight between them.
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