# Deepseek Coder v2 vs GLM-4.5V

> GLM-4.5V is the stronger model overall, scoring 39.8 to 35.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-coder-v2-vs-glm-4-5v
- Last updated: 2026-10-10
- Shared benchmarks: 13

## Summary

- They share 13 benchmarks with published results for both. Deepseek Coder v2 scores higher in 0 categories and GLM-4.5V in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-4.5V leads 52.5 to 38.2.

## Snapshot

| | Deepseek Coder v2 | GLM-4.5V |
|---|---|---|
| Provider | DeepSeek | Z.ai (Zhipu) |
| Noometry Index | 35.9 | 39.8 |
| Rank | 220 | 158 |
| Context | — | 64K |
| Input $/M | — | $0.60 |
| Output $/M | — | $1.80 |
| Weights | Open | Open |

## Coding

- Deepseek Coder v2: 38.1 (#183)
- GLM-4.5V: 39.5 (#155)

| Benchmark | Deepseek Coder v2 | GLM-4.5V |
|---|---|---|
| LMArena Coding | 1251 | 1347 |
| BigCodeBench Instruct | 48.2% | — |
| BigCodeBench Complete | 59.7% | — |
| HumanEval+ | 82.3% | — |
| MBPP+ | 75.1% | — |

## Reasoning

- Deepseek Coder v2: 23.6 (#176)
- GLM-4.5V: 27.4 (#119)

| Benchmark | Deepseek Coder v2 | GLM-4.5V |
|---|---|---|
| LMArena Hard Prompts | 1207 | 1334 |
| Kagi LLM Benchmark | — | 59.8% |
| WinoGrande | 83.7% | — |

## Math

- Deepseek Coder v2: 34.9 (#190)
- GLM-4.5V: 37.4 (#159)

| Benchmark | Deepseek Coder v2 | GLM-4.5V |
|---|---|---|
| LMArena Math | 1241 | 1354 |
| GSM8K | 94.5% | — |

## Knowledge

- Deepseek Coder v2: 32.3 (#212)
- GLM-4.5V: 37.5 (#156)

| Benchmark | Deepseek Coder v2 | GLM-4.5V |
|---|---|---|
| LMArena Expert | 1181 | 1353 |
| ARC (AI2) Challenge | 64.3% | — |

## Multimodal

- Deepseek Coder v2: —
- GLM-4.5V: 34.3 (#92)

| Benchmark | Deepseek Coder v2 | GLM-4.5V |
|---|---|---|
| LMArena Vision | — | 1154 |

## Multilingual

- Deepseek Coder v2: 36.3 (#240)
- GLM-4.5V: 44.6 (#177)

| Benchmark | Deepseek Coder v2 | GLM-4.5V |
|---|---|---|
| LMArena Non-English | 1182 | 1303 |
| LMArena Chinese | 1201 | 1337 |
| LMArena Russian | 1188 | 1298 |
| LMArena Spanish | 1153 | 1336 |
| LMArena French | 1185 | — |
| LMArena German | 1164 | — |
| LMArena Japanese | 1126 | — |
| LMArena Korean | 1104 | — |

## Instruction Following

- Deepseek Coder v2: 61.7 (#242)
- GLM-4.5V: 69.2 (#175)

| Benchmark | Deepseek Coder v2 | GLM-4.5V |
|---|---|---|
| LMArena Instruction Following | 1180 | 1311 |

## Long Context

- Deepseek Coder v2: 37.0 (#224)
- GLM-4.5V: 39.6 (#171)

| Benchmark | Deepseek Coder v2 | GLM-4.5V |
|---|---|---|
| LMArena Longer Query | 1219 | 1304 |

## Writing & Preference

- Deepseek Coder v2: 38.2 (#253)
- GLM-4.5V: 52.5 (#170)

| Benchmark | Deepseek Coder v2 | GLM-4.5V |
|---|---|---|
| LMArena Text | 1191 | 1333 |
| LMArena Creative Writing | 1120 | 1295 |
| LMArena Multi-Turn | 1177 | 1332 |

## FAQ

### Is Deepseek Coder v2 better than GLM-4.5V?

GLM-4.5V is the stronger model overall, scoring 39.8 to 35.9 on the Noometry Index.

### Is Deepseek Coder v2 or GLM-4.5V better for coding?

GLM-4.5V scores higher on coding benchmarks: 39.5 versus 38.1 in the Noometry coding category.

### How many benchmarks do Deepseek Coder v2 and GLM-4.5V share?

13 benchmarks have published results for both models. Deepseek Coder v2 has 24 scored results on Noometry and GLM-4.5V has 15.