Model comparison
GLM-5 vs GPT-5.4
Head-to-head evidence from 26 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-5 #28 (Supported); GPT-5.4 #8 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GLM-5 and GPT-5.4 share 26 comparable benchmark results. 4 of 8 categories are comparable. 23 results are unique to GLM-5; 26 to GPT-5.4.
Updated July 20, 2026- Shared results
- 26
- GLM-5 only
- 23
- GPT-5.4 only
- 26
- Comparable categories
- 4 / 8
Pick GPT-5.4 if you want the stronger benchmark profile. GLM-5 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 26 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 66.06. 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 agentic, where it averages 77.2 against 56.2. The single biggest benchmark swing on the page is FrontierMath v2 (Tiers 1-3), 16.434% to 47.600%. GLM-5 does hit back in mathematics, 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 $1.00 input / $3.20 output per 1M tokens for GLM-5. That is roughly 4.7x on output cost alone. GPT-5.4 is the reasoning model in the pair, while GLM-5 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. GPT-5.4 gives you the larger context window at 1.05M, compared with 200K for GLM-5.
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-5 | Δ | GPT-5.4 |
|---|---|---|---|
| Agentic | GLM-556.2 | Margin→ 21.0 | GPT-5.477.2 |
| Math | GLM-556.3 | Margin← 13.8 | GPT-5.442.5 |
| Knowledge | GLM-566.4 | Margin← 8.8 | GPT-5.457.6 |
| Coding | GLM-566.3 | Margin← 8.6 | GPT-5.457.7 |
| Reasoning | GLM-560.8 | MarginNo overlap | GPT-5.4Not measured |
| Multilingual | GLM-583.1 | MarginNo overlap | GPT-5.4Not measured |
| Multimodal | GLM-5Not measured | MarginNo overlap | GPT-5.473.2 |
| Inst. Following | GLM-592.6 | MarginNo overlap | GPT-5.4Not measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 16.434%B 47.600%Winner: GPT-5.4Δ 31.2FrontierMath v2 (Tiers 1-3): GLM-5 scored 16.434%; GPT-5.4 scored 47.600%. GPT-5.4 wins this benchmark. - Source ↗
FrontierMath v2 (Tier 4)
MathA 2.100%B 27.100%Winner: GPT-5.4Δ 25FrontierMath v2 (Tier 4): GLM-5 scored 2.100%; GPT-5.4 scored 27.100%. GPT-5.4 wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 56.2%B 75.1%Winner: GPT-5.4Δ 18.9Terminal-Bench 2.0: GLM-5 scored 56.2%; GPT-5.4 scored 75.1%. GPT-5.4 wins this benchmark. - Source ↗
GPQA
KnowledgeA 86%B 92.8%Winner: GPT-5.4Δ 6.8GPQA: GLM-5 scored 86%; GPT-5.4 scored 92.8%. GPT-5.4 wins this benchmark. - Source ↗
SWE-bench Pro
CodingA 55.1%B 57.7%Winner: GPT-5.4Δ 2.6SWE-bench Pro: GLM-5 scored 55.1%; GPT-5.4 scored 57.7%. 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-5 | GPT-5.4 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-5$1 input / $3.2 output | GPT-5.4$2.5 input / $15 output | GLM-5 has the lower combined listed price. |
| Generation speedtokens per second | GLM-574 tok/s | GPT-5.474 tok/s | Measured throughput is equal. |
| First-answer latencyseconds to first token | GLM-51.64 s | GPT-5.4151.79 s | GLM-5 reaches the first token sooner. |
| Context windowmaximum listed tokens | GLM-5200K | GPT-5.41.05M | GPT-5.4 lists the larger context window. |
Benchmark Deep Dive
AgenticGPT-5.4 wins22 benchmarks
| Benchmark | GLM-5 | GPT-5.4 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 56.2% | 75.1% | GPT-5.4 leads |
| Claw-EvalSource | 57.7% | 60.3% | GPT-5.4 leads |
| QwenClawBenchSource | 54.1% | — | Not comparable |
| τ³-bench resultsSource | 65.6% | — | Not comparable |
| DeepPlanningSource | 14.6% | — | Not comparable |
| ToolathlonSource | 38% | 54.6% | GPT-5.4 leads |
| MCP AtlasSource | 31.1% | 70.6% | GPT-5.4 leads |
| MCP-TasksSource | 60.8% | — | Not comparable |
| WideResearchSource | 69.8% | — | Not comparable |
| τ²-bench resultsSource | 98.2% | 87.1% | GLM-5 leads |
| CyberGymSource | 43.2% | 79.0% | GPT-5.4 leads |
| APEX-Agents-AASource | 14.5% | 33.3% | GPT-5.4 leads |
| Gert LabsSource | 50.99% | 64.89% | GPT-5.4 leads |
| BrowseCompSource | — | 82.7% | Not comparable |
| OSWorld-VerifiedSource | — | 75% | Not comparable |
| DeepSearchQASource | — | 73.6% | Not comparable |
| AA Agentic IndexSource | — | 41.1% | Not comparable |
| GDPval-AASource | — | 44.7% | Not comparable |
| GDPval-AASource | — | 1395 | Not comparable |
| ResearchClawBenchSource | — | 15.3% | Not comparable |
| JobBenchSource | — | 38.9% | Not comparable |
| ExploitGymSource | — | 6.0% | Not comparable |
CodingGLM-5 wins10 benchmarks
| Benchmark | GLM-5 | GPT-5.4 | Result |
|---|---|---|---|
| SWE-bench VerifiedSource | 77.8% | — | Not comparable |
| SWE-bench Verified*Source | 72.8% | — | Not comparable |
| SWE-bench ProSource | 55.1% | 57.7% | GPT-5.4 leads |
| SWE MultilingualSource | 73.3% | — | Not comparable |
| SWE-RebenchSource | 62.8% | — | Not comparable |
| React Native EvalsSource | 74.8% | 85.3% | GPT-5.4 leads |
| AA-SciCodeSource | 46.2% | 56.6% | GPT-5.4 leads |
| LiveCodeBench ProSource | — | 87.5% | Not comparable |
| Vibe Code BenchSource | — | 67.42% | Not comparable |
| AA Coding IndexSource | — | 71.0% | Not comparable |
Reasoning4 benchmarks
KnowledgeGLM-5 wins16 benchmarks
| Benchmark | GLM-5 | GPT-5.4 | Result |
|---|---|---|---|
| GPQASource | 86% | 92.8% | GPT-5.4 leads |
| GPQA-DSource | 86.0% | 92.8% | GPT-5.4 leads |
| SuperGPQASource | 66.8% | — | Not comparable |
| MMLU-ProSource | 85.7% | — | Not comparable |
| MMLU-Pro (Arcee)Source | 85.8% | — | Not comparable |
| HLESource | 50.4% | 52.1% | GPT-5.4 leads |
| Artificial Analysis Intelligence IndexSource | 39.5% | 51.4% | GPT-5.4 leads |
| AA-GPQA DiamondSource | 82.0% | 92.0% | GPT-5.4 leads |
| AA-HLESource | 27.2% | 41.6% | GPT-5.4 leads |
| AA-Omniscience IndexSource | 2.0% | 5.7% | GPT-5.4 leads |
| AA-Omniscience AccuracySource | 26.9% | 50.0% | GPT-5.4 leads |
| AA-Omniscience Hallucination RateSource | 34.0% | 88.6% | GLM-5 leads |
| HLE w/o toolsSource | — | 39.8% | Not comparable |
| HealthBench HardSource | — | 40.1% | Not comparable |
| MedXpertQA (Text)Source | — | 59.6% | Not comparable |
| HealthBench ProfessionalSource | — | 48.1% | Not comparable |
MathGLM-5 wins8 benchmarks
| Benchmark | GLM-5 | GPT-5.4 | Result |
|---|---|---|---|
| AIME26Source | 95.8% | — | Not comparable |
| AIME25 (Arcee)Source | 93.3% | — | Not comparable |
| HMMT Feb 2025Source | 97.5% | — | Not comparable |
| HMMT Nov 2025Source | 96.9% | — | Not comparable |
| HMMT Feb 2026Source | 86.4% | — | Not comparable |
| MMAnswerBenchSource | 82.5% | — | Not comparable |
| FrontierMath v2 (Tiers 1-3)Source | 16.434% | 47.600% | GPT-5.4 leads |
| FrontierMath v2 (Tier 4)Source | 2.100% | 27.100% | GPT-5.4 leads |
Multilingual2 benchmarks
Multimodal11 benchmarks
| Benchmark | GLM-5 | GPT-5.4 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1280 | 1252 | GLM-5 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 |
Frequently Asked Questions (5)
Which is better, GLM-5 or GPT-5.4?
GPT-5.4 is ahead on BenchLM's BenchAlign leaderboard, 74.24 to 66.06. The biggest single separator in this matchup is FrontierMath v2 (Tiers 1-3), where the scores are 16.434% and 47.600%.
Which is better for knowledge tasks, GLM-5 or GPT-5.4?
GLM-5 has the edge for knowledge tasks in this comparison, averaging 66.4 versus 57.6. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for coding, GLM-5 or GPT-5.4?
GLM-5 has the edge for coding in this comparison, averaging 66.3 versus 57.7. Inside this category, React Native Evals is the benchmark that creates the most daylight between them.
Which is better for math, GLM-5 or GPT-5.4?
GLM-5 has the edge for math in this comparison, averaging 56.3 versus 42.5. 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-5 or GPT-5.4?
GPT-5.4 has the edge for agentic tasks in this comparison, averaging 77.2 versus 56.2. Inside this category, MCP Atlas is the benchmark that creates the most daylight between them.
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