Model comparison
DeepSeek V4 Pro (High) vs GLM-5
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: DeepSeek V4 Pro (High) #81 (Estimated); GLM-5 #28 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. DeepSeek V4 Pro (High) and GLM-5 share 23 comparable benchmark results. 4 of 8 categories are comparable. 15 results are unique to DeepSeek V4 Pro (High); 26 to GLM-5.
Updated July 23, 2026- Shared results
- 23
- DeepSeek V4 Pro (High) only
- 15
- GLM-5 only
- 26
- Comparable categories
- 4 / 8
Pick GLM-5 if you want the stronger benchmark profile. DeepSeek V4 Pro (High) 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 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
GLM-5 is clearly ahead on the BenchAlign aggregate, 66.06 to 55.47. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GLM-5's sharpest advantage is in knowledge, where it averages 66.4 against 57. The single biggest benchmark swing on the page is HLE, 34.5% to 50.4%. DeepSeek V4 Pro (High) does hit back in mathematics, so the answer changes if that is the part of the workload you care about most.
GLM-5 is also the more expensive model on tokens at $1.00 input / $3.20 output per 1M tokens, versus $0.43 input / $0.87 output per 1M tokens for DeepSeek V4 Pro (High). That is roughly 3.7x on output cost alone. DeepSeek V4 Pro (High) 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. DeepSeek V4 Pro (High) gives you the larger context window at 1M, 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 | DeepSeek V4 Pro (High) | Δ | GLM-5 |
|---|---|---|---|
| Math | DeepSeek V4 Pro (High)94.0 | Margin← 37.7 | GLM-556.3 |
| Agentic | DeepSeek V4 Pro (High)70.6 | Margin← 14.4 | GLM-556.2 |
| Knowledge | DeepSeek V4 Pro (High)57.0 | Margin→ 9.4 | GLM-566.4 |
| Coding | DeepSeek V4 Pro (High)69.8 | Margin← 3.5 | GLM-566.3 |
| Reasoning | DeepSeek V4 Pro (High)Not measured | MarginNo overlap | GLM-560.8 |
| Multilingual | DeepSeek V4 Pro (High)Not measured | MarginNo overlap | GLM-583.1 |
| Inst. Following | DeepSeek V4 Pro (High)Not measured | MarginNo overlap | GLM-592.6 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
HLE
KnowledgeA 34.5%B 50.4%Winner: GLM-5Δ 15.9HLE: DeepSeek V4 Pro (High) scored 34.5%; GLM-5 scored 50.4%. GLM-5 wins this benchmark. - Source ↗
HMMT Feb 2026
MathA 94.0%B 86.4%Winner: DeepSeek V4 Pro (High)Δ 7.6HMMT Feb 2026: DeepSeek V4 Pro (High) scored 94.0%; GLM-5 scored 86.4%. DeepSeek V4 Pro (High) wins this benchmark. - Source ↗
Terminal-Bench 2.0
AgenticA 63.3%B 56.2%Winner: DeepSeek V4 Pro (High)Δ 7.1Terminal-Bench 2.0: DeepSeek V4 Pro (High) scored 63.3%; GLM-5 scored 56.2%. DeepSeek V4 Pro (High) wins this benchmark. - Source ↗
GPQA
KnowledgeA 89.1%B 86%Winner: DeepSeek V4 Pro (High)Δ 3.1GPQA: DeepSeek V4 Pro (High) scored 89.1%; GLM-5 scored 86%. DeepSeek V4 Pro (High) wins this benchmark. - Source ↗
SWE-bench Verified
CodingA 79.4%B 77.8%Winner: DeepSeek V4 Pro (High)Δ 1.6SWE-bench Verified: DeepSeek V4 Pro (High) scored 79.4%; GLM-5 scored 77.8%. DeepSeek V4 Pro (High) wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | DeepSeek V4 Pro (High) | GLM-5 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | DeepSeek V4 Pro (High)$0.435 input / $0.87 output | GLM-5$1 input / $3.2 output | DeepSeek V4 Pro (High) has the lower combined listed price. |
| Generation speedtokens per second | DeepSeek V4 Pro (High)Not available | GLM-574 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | DeepSeek V4 Pro (High)Not available | GLM-51.64 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | DeepSeek V4 Pro (High)1M | GLM-5200K | DeepSeek V4 Pro (High) lists the larger context window. |
Benchmark Deep Dive
AgenticDeepSeek V4 Pro (High) wins18 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | GLM-5 | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 63.3% | 56.2% | DeepSeek V4 Pro (High) leads |
| BrowseCompSource | 80.4% | — | Not comparable |
| HLE w/ toolsSource | 44.7% | — | Not comparable |
| MCP AtlasSource | 74.2% | 31.1% | DeepSeek V4 Pro (High) leads |
| ToolathlonSource | 49% | 38% | DeepSeek V4 Pro (High) leads |
| τ²-bench resultsSource | 94.2% | 98.2% | GLM-5 leads |
| GDPval-AASource | 39.9% | — | Not comparable |
| GDPval-AASource | 1299 | — | Not comparable |
| AA Agentic IndexSource | 34.4% | — | 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 |
| 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 |
CodingDeepSeek V4 Pro (High) wins10 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | GLM-5 | Result |
|---|---|---|---|
| CodeforcesSource | 2919.0 | — | Not comparable |
| SWE-bench VerifiedSource | 79.4% | 77.8% | DeepSeek V4 Pro (High) leads |
| SWE-bench ProSource | 54.4% | 55.1% | GLM-5 leads |
| SWE MultilingualSource | 74.1% | 73.3% | DeepSeek V4 Pro (High) leads |
| Terminal-Bench 2.0Source | 63.3% | — | Not comparable |
| AA-SciCodeSource | 46.4% | 46.2% | DeepSeek V4 Pro (High) leads |
| AA Coding IndexSource | 58.7% | — | Not comparable |
| SWE-bench Verified*Source | — | 72.8% | Not comparable |
| SWE-RebenchSource | — | 62.8% | Not comparable |
| React Native EvalsSource | — | 74.8% | Not comparable |
Reasoning6 benchmarks
KnowledgeGLM-5 wins14 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | GLM-5 | Result |
|---|---|---|---|
| MMLU-ProSource | 87.1% | 85.7% | DeepSeek V4 Pro (High) leads |
| SimpleQASource | 46.2% | — | Not comparable |
| Chinese-SimpleQASource | 77.7% | — | Not comparable |
| GPQASource | 89.1% | 86% | DeepSeek V4 Pro (High) leads |
| GPQA-DSource | 89.1% | 86.0% | DeepSeek V4 Pro (High) leads |
| HLESource | 34.5% | 50.4% | GLM-5 leads |
| Artificial Analysis Intelligence IndexSource | 43.1% | 39.5% | DeepSeek V4 Pro (High) leads |
| AA-GPQA DiamondSource | 90.5% | 82.0% | DeepSeek V4 Pro (High) leads |
| AA-HLESource | 33.5% | 27.2% | DeepSeek V4 Pro (High) leads |
| AA-Omniscience IndexSource | -9.7% | 2.0% | GLM-5 leads |
| AA-Omniscience AccuracySource | 41.8% | 26.9% | DeepSeek V4 Pro (High) leads |
| AA-Omniscience Hallucination RateSource | 88.6% | 34.0% | GLM-5 leads |
| SuperGPQASource | — | 66.8% | Not comparable |
| MMLU-Pro (Arcee)Source | — | 85.8% | Not comparable |
MathDeepSeek V4 Pro (High) wins11 benchmarks
| Benchmark | DeepSeek V4 Pro (High) | GLM-5 | Result |
|---|---|---|---|
| HMMT Feb 2026Source | 94.0% | 86.4% | DeepSeek V4 Pro (High) leads |
| IMOAnswerBenchSource | 88.0% | — | Not comparable |
| ApexSource | 27.4% | — | Not comparable |
| Apex ShortlistSource | 85.5% | — | 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 |
| 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 | DeepSeek V4 Pro (High) | GLM-5 | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 1264 | 1278 | GLM-5 leads |
Frequently Asked Questions (5)
Which is better, DeepSeek V4 Pro (High) or GLM-5?
GLM-5 is ahead on BenchLM's BenchAlign leaderboard, 66.06 to 55.47. The biggest single separator in this matchup is HLE, where the scores are 34.5% and 50.4%.
Which is better for knowledge tasks, DeepSeek V4 Pro (High) or GLM-5?
GLM-5 has the edge for knowledge tasks in this comparison, averaging 66.4 versus 57. Inside this category, AA-Omniscience Hallucination Rate is the benchmark that creates the most daylight between them.
Which is better for coding, DeepSeek V4 Pro (High) or GLM-5?
DeepSeek V4 Pro (High) has the edge for coding in this comparison, averaging 69.8 versus 66.3. Inside this category, SWE-bench Verified is the benchmark that creates the most daylight between them.
Which is better for math, DeepSeek V4 Pro (High) or GLM-5?
DeepSeek V4 Pro (High) has the edge for math in this comparison, averaging 94 versus 56.3. Inside this category, HMMT Feb 2026 is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, DeepSeek V4 Pro (High) or GLM-5?
DeepSeek V4 Pro (High) has the edge for agentic tasks in this comparison, averaging 70.6 versus 56.2. Inside this category, MCP Atlas is the benchmark that creates the most daylight between them.
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