# DeepSeek-V3.1 vs GLM-4.5

> DeepSeek-V3.1 and GLM-4.5 score almost the same on the Noometry Index (42.8 vs 42.0), so choose on price, context window or the category you care about most.

- Canonical page: https://noometry.com/compare/deepseek-v3-1-vs-glm-4-5
- Last updated: 2026-10-11
- Shared benchmarks: 21

## Summary

- They share 21 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 2 categories and GLM-4.5 in 6 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where DeepSeek-V3.1 leads 43.7 to 35.9.
- The biggest single-benchmark swing is Fiction.LiveBench: 52.8% for DeepSeek-V3.1 and 58.3% for GLM-4.5.
- DeepSeek-V3.1 is cheaper at $0.25 / $0.95 per million input/output tokens, against $0.60 / $2.20 for GLM-4.5.
- DeepSeek-V3.1 accepts more context: 164K tokens versus 131K.

## Snapshot

| | DeepSeek-V3.1 | GLM-4.5 |
|---|---|---|
| Provider | DeepSeek | Z.ai (Zhipu) |
| Noometry Index | 42.8 | 42.0 |
| Rank | 108 | 122 |
| Context | 164K | 131K |
| Input $/M | $0.25 | $0.60 |
| Output $/M | $0.95 | $2.20 |
| Weights | Open | Open |

## Coding

- DeepSeek-V3.1: 40.3 (#144)
- GLM-4.5: 41.4 (#125)

| Benchmark | DeepSeek-V3.1 | GLM-4.5 |
|---|---|---|
| WeirdML | 38.4% | 40.6% |
| LMArena Coding | 1417 | 1434 |
| SWE-bench Verified (bash only) | — | 54.2% |
| ALE-Bench | — | 344.82 |
| AlgoTune | — | 1.52 |

## Reasoning

- DeepSeek-V3.1: 27.9 (#110)
- GLM-4.5: 28.6 (#100)

| Benchmark | DeepSeek-V3.1 | GLM-4.5 |
|---|---|---|
| Kagi LLM Benchmark | 53.2% | 57.9% |
| LMArena Hard Prompts | 1417 | 1429 |
| SimpleBench | 40% | — |
| DTBench | 82.7% | — |
| LMCA | 24.3% | — |
| Epoch Capabilities Index | 139.92 | — |
| ForecastBench | 58 | — |

## Math

- DeepSeek-V3.1: 38.9 (#122)
- GLM-4.5: 39.0 (#116)

| Benchmark | DeepSeek-V3.1 | GLM-4.5 |
|---|---|---|
| LMArena Math | 1420 | 1427 |

## Knowledge

- DeepSeek-V3.1: 43.7 (#90)
- GLM-4.5: 35.9 (#179)

| Benchmark | DeepSeek-V3.1 | GLM-4.5 |
|---|---|---|
| LMArena Expert | 1405 | 1433 |
| Humanity's Last Exam | — | 8.3% |
| Confabulations | — | 11.3% |
| Vectara Hallucination Rate | 5.5% | — |

## Multilingual

- DeepSeek-V3.1: 51.6 (#106)
- GLM-4.5: 52.8 (#77)

| Benchmark | DeepSeek-V3.1 | GLM-4.5 |
|---|---|---|
| LMArena Non-English | 1400 | 1417 |
| LMArena Chinese | 1469 | 1465 |
| LMArena French | 1447 | 1418 |
| LMArena German | 1411 | 1407 |
| LMArena Japanese | 1378 | 1415 |
| LMArena Korean | 1337 | 1380 |
| LMArena Russian | 1405 | 1414 |
| LMArena Spanish | 1431 | 1454 |

## Instruction Following

- DeepSeek-V3.1: 73.9 (#110)
- GLM-4.5: 74.1 (#104)

| Benchmark | DeepSeek-V3.1 | GLM-4.5 |
|---|---|---|
| LMArena Instruction Following | 1400 | 1404 |

## Long Context

- DeepSeek-V3.1: 36.3 (#232)
- GLM-4.5: 38.2 (#201)

| Benchmark | DeepSeek-V3.1 | GLM-4.5 |
|---|---|---|
| Fiction.LiveBench | 52.8% | 58.3% |
| LMArena Longer Query | 1422 | 1412 |

## Writing & Preference

- DeepSeek-V3.1: 60.3 (#98)
- GLM-4.5: 57.5 (#127)

| Benchmark | DeepSeek-V3.1 | GLM-4.5 |
|---|---|---|
| LMArena Text | 1420 | 1430 |
| LMArena Creative Writing | 1401 | 1395 |
| EQ-Bench Creative Writing | 1436 | 1343 |
| LMArena Multi-Turn | 1408 | 1415 |
| Short-Story Creative Writing | — | 73.4% |

## FAQ

### Is DeepSeek-V3.1 better than GLM-4.5?

DeepSeek-V3.1 and GLM-4.5 score almost the same on the Noometry Index (42.8 vs 42.0), so choose on price, context window or the category you care about most.

### Which is cheaper, DeepSeek-V3.1 or GLM-4.5?

DeepSeek-V3.1 is cheaper. It lists at $0.25 per million input tokens and $0.95 per million output tokens; GLM-4.5 lists at $0.60 and $2.20.

### Is DeepSeek-V3.1 or GLM-4.5 better for coding?

GLM-4.5 scores higher on coding benchmarks: 41.4 versus 40.3 in the Noometry coding category.

### Which has the bigger context window?

DeepSeek-V3.1 does, with 164K tokens against 131K.

### How many benchmarks do DeepSeek-V3.1 and GLM-4.5 share?

21 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and GLM-4.5 has 27.