Model comparison
Exaone 4.0 32B vs GLM-5
Head-to-head evidence from 12 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Exaone 4.0 32B #170 (Estimated); GLM-5 #28 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Exaone 4.0 32B and GLM-5 share 12 comparable benchmark results. 1 of 8 categories are comparable. 1 result is unique to Exaone 4.0 32B; 37 to GLM-5.
Updated July 18, 2026- Shared results
- 12
- Exaone 4.0 32B only
- 1
- GLM-5 only
- 37
- Comparable categories
- 1 / 8
Pick GLM-5 if you want the stronger benchmark profile. Exaone 4.0 32B only becomes the better choice if knowledge is the priority or you want the stronger reasoning-first profile.
Confidence note. This is a partial-evidence comparison with 12 shared benchmark results across 5 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
GLM-5 is clearly ahead on the BenchAlign aggregate, 66.06 to 40.44. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
Exaone 4.0 32B 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. GLM-5 gives you the larger context window at 200K, compared with 128K for Exaone 4.0 32B.
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 | Exaone 4.0 32B | Δ | GLM-5 |
|---|---|---|---|
| Knowledge | Exaone 4.0 32B81.8 | Margin← 15.4 | GLM-566.4 |
| Agentic | Exaone 4.0 32BNot measured | MarginNo overlap | GLM-556.2 |
| Coding | Exaone 4.0 32BNot measured | MarginNo overlap | GLM-566.3 |
| Reasoning | Exaone 4.0 32BNot measured | MarginNo overlap | GLM-560.8 |
| Math | Exaone 4.0 32BNot measured | MarginNo overlap | GLM-556.3 |
| Multilingual | Exaone 4.0 32BNot measured | MarginNo overlap | GLM-583.1 |
| Inst. Following | Exaone 4.0 32BNot measured | MarginNo overlap | GLM-592.6 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
MMLU-Pro
KnowledgeA 81.8%B 85.7%Winner: GLM-5Δ 3.9MMLU-Pro: Exaone 4.0 32B scored 81.8%; GLM-5 scored 85.7%. GLM-5 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Exaone 4.0 32B | GLM-5 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Exaone 4.0 32BNot available | GLM-5$1 input / $3.2 output | A complete price comparison is not available. |
| Generation speedtokens per second | Exaone 4.0 32BNot available | GLM-574 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Exaone 4.0 32BNot available | GLM-51.64 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Exaone 4.0 32B128K | GLM-5200K | GLM-5 lists the larger context window. |
Benchmark Deep Dive
Agentic13 benchmarks
| Benchmark | Exaone 4.0 32B | GLM-5 | Result |
|---|---|---|---|
| τ²-bench resultsSource | 4.1% | 98.2% | GLM-5 leads |
| Terminal-Bench 2.0Source | — | 56.2% | Not comparable |
| Claw-EvalSource | — | 57.7% | Not comparable |
| QwenClawBenchSource | — | 54.1% | Not comparable |
| τ³-bench resultsSource | — | 65.6% | Not comparable |
| DeepPlanningSource | — | 14.6% | Not comparable |
| ToolathlonSource | — | 38% | Not comparable |
| MCP AtlasSource | — | 31.1% | Not comparable |
| MCP-TasksSource | — | 60.8% | Not comparable |
| WideResearchSource | — | 69.8% | Not comparable |
| CyberGymSource | — | 43.2% | Not comparable |
| APEX-Agents-AASource | — | 14.5% | Not comparable |
| Gert LabsSource | — | 50.99% | Not comparable |
Coding7 benchmarks
| Benchmark | Exaone 4.0 32B | GLM-5 | Result |
|---|---|---|---|
| AA-SciCodeSource | 25.2% | 46.2% | GLM-5 leads |
| SWE-bench VerifiedSource | — | 77.8% | Not comparable |
| SWE-bench Verified*Source | — | 72.8% | Not comparable |
| SWE-bench ProSource | — | 55.1% | Not comparable |
| SWE MultilingualSource | — | 73.3% | Not comparable |
| SWE-RebenchSource | — | 62.8% | Not comparable |
| React Native EvalsSource | — | 74.8% | Not comparable |
Reasoning4 benchmarks
KnowledgeExaone 4.0 32B wins12 benchmarks
| Benchmark | Exaone 4.0 32B | GLM-5 | Result |
|---|---|---|---|
| MMLU-ProSource | 81.8% | 85.7% | GLM-5 leads |
| Artificial Analysis Intelligence IndexSource | 6.0% | 39.5% | GLM-5 leads |
| AA-GPQA DiamondSource | 62.8% | 82.0% | GLM-5 leads |
| AA-HLESource | 4.9% | 27.2% | GLM-5 leads |
| AA-Omniscience IndexSource | -62.3% | 2.0% | GLM-5 leads |
| AA-Omniscience AccuracySource | 10.4% | 26.9% | GLM-5 leads |
| AA-Omniscience Hallucination RateSource | 81.0% | 34.0% | GLM-5 leads |
| GPQASource | — | 86% | Not comparable |
| GPQA-DSource | — | 86.0% | Not comparable |
| SuperGPQASource | — | 66.8% | Not comparable |
| MMLU-Pro (Arcee)Source | — | 85.8% | Not comparable |
| HLESource | — | 50.4% | Not comparable |
Math9 benchmarks
| Benchmark | Exaone 4.0 32B | GLM-5 | Result |
|---|---|---|---|
| AIME 2025Source | 85.3% | — | Not comparable |
| 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% | Not comparable |
| FrontierMath v2 (Tier 4)Source | — | 2.100% | Not comparable |
Multilingual2 benchmarks
Multimodal1 benchmarks
| Benchmark | Exaone 4.0 32B | GLM-5 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | — | 1280 | Not comparable |
Frequently Asked Questions (2)
Which is better, Exaone 4.0 32B or GLM-5?
GLM-5 is ahead on BenchLM's BenchAlign leaderboard, 66.06 to 40.44. The biggest single separator in this matchup is MMLU-Pro, where the scores are 81.8% and 85.7%.
Which is better for knowledge tasks, Exaone 4.0 32B or GLM-5?
Exaone 4.0 32B has the edge for knowledge tasks in this comparison, averaging 81.8 versus 66.4. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
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