# DeepSeek-V2.5 (Sep 2024) vs GLM-4.7-Flash

> GLM-4.7-Flash is the stronger model overall, scoring 38.4 to 37.0 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v2-5-vs-glm-4-7-flash
- Last updated: 2026-10-10
- Shared benchmarks: 16

## Summary

- They share 16 benchmarks with published results for both. DeepSeek-V2.5 (Sep 2024) scores higher in 2 categories and GLM-4.7-Flash in 6 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in coding, where GLM-4.7-Flash leads 40.0 to 31.3.

## Snapshot

| | DeepSeek-V2.5 (Sep 2024) | GLM-4.7-Flash |
|---|---|---|
| Provider | DeepSeek | Z.ai (Zhipu) |
| Noometry Index | 37.0 | 38.4 |
| Rank | 197 | 175 |
| Context | — | 200K |
| Input $/M | — | $0.06 |
| Output $/M | — | $0.40 |
| Weights | Open | Open |

## Coding

- DeepSeek-V2.5 (Sep 2024): 31.3 (#274)
- GLM-4.7-Flash: 40.0 (#133)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | GLM-4.7-Flash |
|---|---|---|
| LMArena Coding | 1310 | 1383 |
| Aider Polyglot | 17.8% | — |
| BigCodeBench Instruct | 48.6% | — |
| BigCodeBench Complete | 53.2% | — |
| HumanEval+ | 83.5% | — |
| MBPP+ | 74.1% | — |

## Reasoning

- DeepSeek-V2.5 (Sep 2024): 24.5 (#145)
- GLM-4.7-Flash: 20.2 (#224)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | GLM-4.7-Flash |
|---|---|---|
| LMArena Hard Prompts | 1289 | 1356 |
| Chess Puzzles | — | 0% |

## Math

- DeepSeek-V2.5 (Sep 2024): 33.3 (#177)
- GLM-4.7-Flash: 34.4 (#159)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | GLM-4.7-Flash |
|---|---|---|
| LMArena Math | 1289 | 1354 |
| OTIS Mock AIME 2024-2025 | — | 58.3% |

## Knowledge

- DeepSeek-V2.5 (Sep 2024): 34.2 (#190)
- GLM-4.7-Flash: 35.4 (#177)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | GLM-4.7-Flash |
|---|---|---|
| LMArena Expert | 1266 | 1357 |
| GPQA Diamond | — | 60.5% |
| Vectara Hallucination Rate | — | 9.3% |

## Multilingual

- DeepSeek-V2.5 (Sep 2024): 42.7 (#188)
- GLM-4.7-Flash: 46.8 (#152)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | GLM-4.7-Flash |
|---|---|---|
| LMArena Non-English | 1273 | 1331 |
| LMArena Chinese | 1317 | 1403 |
| LMArena French | 1288 | 1332 |
| LMArena German | 1258 | 1336 |
| LMArena Korean | 1209 | 1284 |
| LMArena Russian | 1289 | 1333 |
| LMArena Spanish | 1248 | 1351 |
| LMArena Japanese | 1228 | — |

## Instruction Following

- DeepSeek-V2.5 (Sep 2024): 67.7 (#189)
- GLM-4.7-Flash: 70.3 (#162)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | GLM-4.7-Flash |
|---|---|---|
| LMArena Instruction Following | 1280 | 1327 |

## Long Context

- DeepSeek-V2.5 (Sep 2024): 39.5 (#169)
- GLM-4.7-Flash: 40.9 (#143)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | GLM-4.7-Flash |
|---|---|---|
| LMArena Longer Query | 1301 | 1345 |

## Writing & Preference

- DeepSeek-V2.5 (Sep 2024): 50.0 (#182)
- GLM-4.7-Flash: 47.7 (#206)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | GLM-4.7-Flash |
|---|---|---|
| LMArena Text | 1294 | 1351 |
| LMArena Creative Writing | 1285 | 1297 |
| LMArena Multi-Turn | 1297 | 1342 |
| EQ-Bench Creative Writing | — | 1125 |

## FAQ

### Is DeepSeek-V2.5 (Sep 2024) better than GLM-4.7-Flash?

GLM-4.7-Flash is the stronger model overall, scoring 38.4 to 37.0 on the Noometry Index.

### Is DeepSeek-V2.5 (Sep 2024) or GLM-4.7-Flash better for coding?

GLM-4.7-Flash scores higher on coding benchmarks: 40.0 versus 31.3 in the Noometry coding category.

### How many benchmarks do DeepSeek-V2.5 (Sep 2024) and GLM-4.7-Flash share?

16 benchmarks have published results for both models. DeepSeek-V2.5 (Sep 2024) has 22 scored results on Noometry and GLM-4.7-Flash has 21.