# DeepSeek LLM 67B vs GLM-5.3

> GLM-5.3 is the stronger model overall, scoring 54.8 to 24.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-llm-67b-vs-glm-5-3
- Last updated: 2026-10-11
- Shared benchmarks: 14

## Summary

- They share 14 benchmarks with published results for both. DeepSeek LLM 67B scores higher in 0 categories and GLM-5.3 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5.3 leads 62.3 to 8.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 0.8% for DeepSeek LLM 67B and 91.1% for GLM-5.3.

## Snapshot

| | DeepSeek LLM 67B | GLM-5.3 |
|---|---|---|
| Provider | DeepSeek | Z.ai (Zhipu) |
| Noometry Index | 24.9 | 54.8 |
| Rank | 347 | 26 |
| Context | — | 1M |
| Input $/M | — | $1.40 |
| Output $/M | — | $4.40 |
| Weights | Open | Open |

## Coding

- DeepSeek LLM 67B: 31.9 (#278)
- GLM-5.3: 59.5 (#14)

| Benchmark | DeepSeek LLM 67B | GLM-5.3 |
|---|---|---|
| LMArena Coding | 1096 | 1496 |
| DeepSWE | — | 69% |
| FrontierCode | — | 40.1% |
| CursorBench | — | 42.6% |
| LMArena WebDev | — | 1622 |
| FrontierSWE | — | 30.2% |
| SciCode | — | 59% |
| WeirdML | — | 75.4% |
| ALE-Bench | — | 1,317 |

## Agentic & Tool Use

- DeepSeek LLM 67B: —
- GLM-5.3: 36.4 (#38)

| Benchmark | DeepSeek LLM 67B | GLM-5.3 |
|---|---|---|
| APEX-Agents | — | 56.6% |
| Vending-Bench 2 | — | 8,164 |

## Reasoning

- DeepSeek LLM 67B: 16.5 (#304)
- GLM-5.3: 46.1 (#46)

| Benchmark | DeepSeek LLM 67B | GLM-5.3 |
|---|---|---|
| Chess Puzzles | 0% | 21% |
| LMArena Hard Prompts | 1070 | 1489 |
| Epoch Capabilities Index | 110.5 | 155.61 |
| NYT Connections (extended) | — | 74.2% |
| CritPt | — | 19.1% |
| Mystery Game Puzzles | — | 33% |
| DTBench | — | 87.7% |
| LMCA | — | 55.5% |
| Bench to the Future 3 | — | 0.15 |

## Math

- DeepSeek LLM 67B: 8.7 (#324)
- GLM-5.3: 62.3 (#33)

| Benchmark | DeepSeek LLM 67B | GLM-5.3 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 0.8% | 91.1% |
| LMArena Math | 1108 | 1489 |
| FrontierMath (Tiers 1-3) | — | 68.8% |
| FrontierMath Tier 4 | — | 29.3% |
| ProofBench | — | 49% |
| MATH Level 5 | 6.4% | — |

## Knowledge

- DeepSeek LLM 67B: 7.0 (#313)
- GLM-5.3: 58.3 (#37)

| Benchmark | DeepSeek LLM 67B | GLM-5.3 |
|---|---|---|
| GPQA Diamond | 24.6% | 90.9% |
| SimpleQA Verified | — | 41% |
| LMArena Expert | — | 1516 |

## Multilingual

- DeepSeek LLM 67B: 29.4 (#267)
- GLM-5.3: 55.7 (#28)

| Benchmark | DeepSeek LLM 67B | GLM-5.3 |
|---|---|---|
| LMArena Non-English | 1073 | 1457 |
| LMArena Chinese | 1132 | 1528 |
| LMArena French | — | 1499 |
| LMArena German | — | 1499 |
| LMArena Japanese | — | 1453 |
| LMArena Korean | — | 1472 |
| LMArena Russian | — | 1463 |
| LMArena Spanish | — | 1460 |

## Instruction Following

- DeepSeek LLM 67B: 55.4 (#277)
- GLM-5.3: 77.5 (#23)

| Benchmark | DeepSeek LLM 67B | GLM-5.3 |
|---|---|---|
| LMArena Instruction Following | 1079 | 1477 |

## Long Context

- DeepSeek LLM 67B: 33.1 (#265)
- GLM-5.3: 45.4 (#41)

| Benchmark | DeepSeek LLM 67B | GLM-5.3 |
|---|---|---|
| LMArena Longer Query | 1092 | 1482 |

## Writing & Preference

- DeepSeek LLM 67B: 31.6 (#282)
- GLM-5.3: 75.7 (#6)

| Benchmark | DeepSeek LLM 67B | GLM-5.3 |
|---|---|---|
| LMArena Text | 1105 | 1471 |
| LMArena Creative Writing | 1067 | 1457 |
| LMArena Multi-Turn | 1082 | 1472 |
| EQ-Bench Creative Writing | — | 2075 |

## FAQ

### Is DeepSeek LLM 67B better than GLM-5.3?

GLM-5.3 is the stronger model overall, scoring 54.8 to 24.9 on the Noometry Index.

### Is DeepSeek LLM 67B or GLM-5.3 better for coding?

GLM-5.3 scores higher on coding benchmarks: 59.5 versus 31.9 in the Noometry coding category.

### How many benchmarks do DeepSeek LLM 67B and GLM-5.3 share?

14 benchmarks have published results for both models. DeepSeek LLM 67B has 15 scored results on Noometry and GLM-5.3 has 42.