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

> GLM-4.7 is the stronger model overall, scoring 42.0 to 37.6 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v2-5-vs-glm-4-7
- Last updated: 2026-10-11
- Shared benchmarks: 17

## Summary

- They share 17 benchmarks with published results for both. DeepSeek-V2.5 (Sep 2024) scores higher in 1 category and GLM-4.7 in 7 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in coding, where GLM-4.7 leads 44.0 to 31.7.

## Snapshot

| | DeepSeek-V2.5 (Sep 2024) | GLM-4.7 |
|---|---|---|
| Provider | DeepSeek | Z.ai (Zhipu) |
| Noometry Index | 37.6 | 42.0 |
| Rank | 200 | 124 |
| Context | — | 205K |
| Input $/M | — | $0.60 |
| Output $/M | — | $2.20 |
| Weights | Open | Open |

## Coding

- DeepSeek-V2.5 (Sep 2024): 31.7 (#281)
- GLM-4.7: 44.0 (#79)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | GLM-4.7 |
|---|---|---|
| LMArena Coding | 1309 | 1454 |
| Aider Polyglot | 17.8% | — |
| LMArena WebDev | — | 1435 |
| SciCode | — | 45.1% |
| BigCodeBench Instruct | 48.6% | — |
| BigCodeBench Complete | 53.2% | — |
| ALE-Bench | — | 399.48 |
| HumanEval+ | 83.5% | — |
| MBPP+ | 74.1% | — |

## Agentic & Tool Use

- DeepSeek-V2.5 (Sep 2024): —
- GLM-4.7: 26.5 (#103)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | GLM-4.7 |
|---|---|---|
| Terminal-Bench | — | 33.4% |
| Vending-Bench 2 | — | 2,377 |

## Reasoning

- DeepSeek-V2.5 (Sep 2024): 25.6 (#145)
- GLM-4.7: 24.3 (#164)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | GLM-4.7 |
|---|---|---|
| LMArena Hard Prompts | 1289 | 1443 |
| SimpleBench | — | 47.7% |
| CritPt | — | 1.7% |
| Chess Puzzles | — | 6% |
| Epoch Capabilities Index | — | 143.51 |

## Math

- DeepSeek-V2.5 (Sep 2024): 35.9 (#177)
- GLM-4.7: 38.6 (#135)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | GLM-4.7 |
|---|---|---|
| LMArena Math | 1288 | 1423 |
| OTIS Mock AIME 2024-2025 | — | 83.3% |
| ProofBench | — | 6% |
| FrontierMath (Feb 2025 set) | — | 2.4% |
| FrontierMath Tier 4 (v1) | — | 0% |

## Knowledge

- DeepSeek-V2.5 (Sep 2024): 34.8 (#193)
- GLM-4.7: 47.0 (#80)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | GLM-4.7 |
|---|---|---|
| LMArena Expert | 1266 | 1424 |
| GPQA Diamond | — | 83.3% |
| SimpleQA Verified | — | 32.2% |
| Vectara Hallucination Rate | — | 11.7% |

## Multilingual

- DeepSeek-V2.5 (Sep 2024): 42.5 (#193)
- GLM-4.7: 52.8 (#79)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | GLM-4.7 |
|---|---|---|
| LMArena Non-English | 1273 | 1417 |
| LMArena Chinese | 1318 | 1495 |
| LMArena French | 1289 | 1432 |
| LMArena German | 1258 | 1424 |
| LMArena Japanese | 1228 | 1439 |
| LMArena Korean | 1209 | 1399 |
| LMArena Russian | 1289 | 1423 |
| LMArena Spanish | 1248 | 1434 |

## Instruction Following

- DeepSeek-V2.5 (Sep 2024): 67.5 (#194)
- GLM-4.7: 74.4 (#95)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | GLM-4.7 |
|---|---|---|
| LMArena Instruction Following | 1280 | 1411 |

## Long Context

- DeepSeek-V2.5 (Sep 2024): 39.5 (#174)
- GLM-4.7: 42.8 (#116)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | GLM-4.7 |
|---|---|---|
| LMArena Longer Query | 1301 | 1432 |
| CL-bench | — | 15.9% |
| CL-bench Life | — | 10.9% |

## Writing & Preference

- DeepSeek-V2.5 (Sep 2024): 49.8 (#187)
- GLM-4.7: 60.9 (#93)

| Benchmark | DeepSeek-V2.5 (Sep 2024) | GLM-4.7 |
|---|---|---|
| LMArena Text | 1294 | 1435 |
| LMArena Creative Writing | 1285 | 1401 |
| LMArena Multi-Turn | 1297 | 1446 |
| EQ-Bench Creative Writing | — | 1413 |

## FAQ

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

GLM-4.7 is the stronger model overall, scoring 42.0 to 37.6 on the Noometry Index.

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

GLM-4.7 scores higher on coding benchmarks: 44.0 versus 31.7 in the Noometry coding category.

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

17 benchmarks have published results for both models. DeepSeek-V2.5 (Sep 2024) has 22 scored results on Noometry and GLM-4.7 has 36.