# DeepSeek V3.2 vs GLM-5

> Side-by-side benchmark comparison for DeepSeek V3.2 and GLM-5 across agentic, coding, multimodal, knowledge, reasoning, multilingual, and math tasks.

- Canonical page: https://benchlm.ai/compare/deepseek-v3-2-vs-glm-5
- Last updated: October 17, 2026

- Shared sourced benchmarks: 4
- HTML indexing: indexable
- Ranking lane: BenchAlign v5.8

## Quick Verdict

Pick GLM-5 if you want the stronger benchmark profile. DeepSeek V3.2 only makes more sense when its price, context window, or workload-specific category wins matter more than the overall score.

## Summary

- GLM-5 leads overall 54.84 to 50.2.
- The clearest category separation is in instruction following, where the averages are 58.2 for DeepSeek V3.2 and 88.6 for GLM-5.
- The biggest single benchmark swing is Gert Labs in Agentic, with scores of 29.57% and 50.99%.
- DeepSeek V3.2 is the cheaper option on output tokens, which matters if you expect large responses or heavy interactive use.
- GLM-5 also has the larger context window at 200K.

## Model Snapshot

| Property | DeepSeek V3.2 | GLM-5 |
|----------|----------|----------|
| Creator | DeepSeek | Z.AI |
| Type | Open Weight | Open Weight |
| Reasoning | Non-Reasoning | Non-Reasoning |
| Context | 128K | 200K |
| Overall Score | 50.2 | 54.84 |
| Benchmarks Covered | 5 | 38 |
| Pricing (input/output) | $0.28 / $0.42 | $1.00 / $3.20 |

## Category Breakdown

### Agentic

- Winner: Not comparable
- DeepSeek V3.2 public-lane score: Coming soon
- GLM-5 public-lane score: 41.5 (Estimated · #63/128)

| Benchmark | DeepSeek V3.2 | GLM-5 | Winner |
|-----------|-----------|-----------|--------|
| Claw-Eval | 40.2% | 57.7% | GLM-5 |
| VITA-Bench | 18.5% | Coming soon | Coming soon |
| Gert Labs | 29.57% | 50.99% | GLM-5 |
| Terminal-Bench 2.0 | Coming soon | 56.2% | Coming soon |
| BrowseComp | Coming soon | 62% | Coming soon |
| HLE w/ tools | Coming soon | 50.4% | Coming soon |
| QwenClawBench | Coming soon | 54.1% | Coming soon |
| τ³-bench results | Coming soon | 65.6% | Coming soon |
| DeepPlanning | Coming soon | 14.6% | Coming soon |
| Toolathlon | Coming soon | 38% | Coming soon |
| MCP Atlas | Coming soon | 31.1% | Coming soon |
| MCP-Tasks | Coming soon | 60.8% | Coming soon |
| WideResearch | Coming soon | 69.8% | Coming soon |
| CyberGym | Coming soon | 43.2% | Coming soon |

### Coding

- Winner: Directional only
- DeepSeek V3.2 public-lane score: 28.5 (Estimated · #99/150)
- GLM-5 public-lane score: 38 (Estimated · #70/150)

| Benchmark | DeepSeek V3.2 | GLM-5 | Winner |
|-----------|-----------|-----------|--------|
| SWE-Rebench | 60.9% | 62.8% | GLM-5 |
| React Native Evals | 71.5% | 74.8% | GLM-5 |
| SWE-bench Verified | Coming soon | 77.8% | Coming soon |
| SWE-bench Verified* | Coming soon | 72.8% | Coming soon |
| SWE-bench Pro | Coming soon | 55.1% | Coming soon |
| SWE Multilingual | Coming soon | 73.3% | Coming soon |
| NL2Repo | Coming soon | 35.9% | Coming soon |
| Terminal-Bench 2.0 | Coming soon | 56.2% | Coming soon |

### Reasoning

- Winner: Not comparable
- DeepSeek V3.2 public-lane score: 57.2 (Unranked · 2 rankable rows)
- GLM-5 public-lane score: 70.9 (Unranked · 4 rankable rows)

| Benchmark | DeepSeek V3.2 | GLM-5 | Winner |
|-----------|-----------|-----------|--------|
| LongBench v2 | Coming soon | 60.8% | Coming soon |
| AI-Needle | Coming soon | 63.3% | Coming soon |

### Knowledge

- Winner: Directional only
- DeepSeek V3.2 public-lane score: 42.2 (Estimated · #109/184)
- GLM-5 public-lane score: 50.4 (Estimated · #79/184)

| Benchmark | DeepSeek V3.2 | GLM-5 | Winner |
|-----------|-----------|-----------|--------|
| GPQA | Coming soon | 86% | Coming soon |
| GPQA-D | Coming soon | 86.0% | Coming soon |
| SuperGPQA | Coming soon | 66.8% | Coming soon |
| MMLU-Pro | Coming soon | 85.7% | Coming soon |
| MMLU-Pro (Arcee) | Coming soon | 85.8% | Coming soon |
| HLE | Coming soon | 30.5% | Coming soon |

### Multilingual

- Winner: Not comparable
- DeepSeek V3.2 public-lane score: Coming soon
- GLM-5 public-lane score: 89.5 (#6/17)

| Benchmark | DeepSeek V3.2 | GLM-5 | Winner |
|-----------|-----------|-----------|--------|
| MMLU-ProX | Coming soon | 83.1% | Coming soon |
| NOVA-63 | Coming soon | 55.1% | Coming soon |

### Instruction Following

- Winner: Directional only
- DeepSeek V3.2 public-lane score: 58.2 (#82/148)
- GLM-5 public-lane score: 88.6 (#35/148)

| Benchmark | DeepSeek V3.2 | GLM-5 | Winner |
|-----------|-----------|-----------|--------|
| IFEval | Coming soon | 92.6% | Coming soon |

### Mathematics

- Winner: Not comparable
- DeepSeek V3.2 public-lane score: Coming soon
- GLM-5 public-lane score: 83 (Unranked · 6 rankable rows)

| Benchmark | DeepSeek V3.2 | GLM-5 | Winner |
|-----------|-----------|-----------|--------|
| AIME26 | Coming soon | 95.8% | Coming soon |
| AIME25 (Arcee) | Coming soon | 93.3% | Coming soon |
| HMMT Feb 2025 | Coming soon | 97.5% | Coming soon |
| HMMT Nov 2025 | Coming soon | 96.9% | Coming soon |
| HMMT Feb 2026 | Coming soon | 86.4% | Coming soon |
| MMAnswerBench | Coming soon | 82.5% | Coming soon |

## FAQ

### Which is better overall, DeepSeek V3.2 or GLM-5?

GLM-5 is ahead overall on BenchLM right now.

### Where is the biggest gap between DeepSeek V3.2 and GLM-5?

The widest category gap is in instruction following, where the averages are 58.2 for DeepSeek V3.2 and 88.6 for GLM-5.

### How many benchmarks does DeepSeek V3.2 cover on BenchLM?

DeepSeek V3.2 currently has 5 sourced benchmark scores on BenchLM.

### How many benchmarks does GLM-5 cover on BenchLM?

GLM-5 currently has 38 sourced benchmark scores on BenchLM.

## Related Comparisons

- [DeepSeek V3.2 vs DeepSeek V3.2 (Thinking)](/compare/deepseek-v3-2-vs-deepseek-v3-2-thinking)
- [GLM-5 vs DeepSeek V3.2 (Thinking)](/compare/deepseek-v3-2-thinking-vs-glm-5)
- [DeepSeek V3.2 vs GLM-5.3](/compare/deepseek-v3-2-vs-glm-5-3)
- [GLM-5 vs GLM-5.3](/compare/glm-5-vs-glm-5-3)

## Explore More

- [DeepSeek V3.2 profile](/models/deepseek-v3-2)
- [GLM-5 profile](/models/glm-5)
- [Compare Pricing](/llm-pricing)
- [Alternative Finder](/tools/alternative-finder)
- [LLM Selector](/tools/llm-selector)
- [Overall Rankings](/best/overall)