# GLM-4.6V vs Llama 3.1-405B

> GLM-4.6V is the stronger model overall, scoring 41.3 to 30.7 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-4-6v-vs-llama-3-1-405b
- Last updated: 2026-10-12
- Shared benchmarks: 11

## Summary

- They share 11 benchmarks with published results for both. GLM-4.6V scores higher in 7 categories and Llama 3.1-405B in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-4.6V leads 56.6 to 38.9.

## Snapshot

| | GLM-4.6V | Llama 3.1-405B |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 41.3 | 30.7 |
| Rank | 137 | 288 |
| Context | 128K | — |
| Input $/M | $0.30 | — |
| Output $/M | $0.90 | — |
| Weights | Open | Open |

## Coding

- GLM-4.6V: 40.9 (#128)
- Llama 3.1-405B: 33.1 (#262)

| Benchmark | GLM-4.6V | Llama 3.1-405B |
|---|---|---|
| LMArena Coding | 1390 | 1291 |
| WeirdML | — | 21.4% |

## Agentic & Tool Use

- GLM-4.6V: —
- Llama 3.1-405B: 21.0 (#140)

| Benchmark | GLM-4.6V | Llama 3.1-405B |
|---|---|---|
| TheAgentCompany | — | 7.4% |
| Cybench | — | 7.5% |

## Reasoning

- GLM-4.6V: 27.6 (#115)
- Llama 3.1-405B: 16.8 (#300)

| Benchmark | GLM-4.6V | Llama 3.1-405B |
|---|---|---|
| LMArena Hard Prompts | 1368 | 1269 |
| SimpleBench | — | 23% |
| Kagi LLM Benchmark | — | 45% |
| DTBench | — | 61.4% |
| BIG-Bench Hard | — | 82.9% |
| Epoch Capabilities Index | — | 128.75 |
| ForecastBench | — | 59.9 |
| HellaSwag | — | 89.2% |
| PIQA | — | 85.9% |
| WinoGrande | — | 89.2% |

## Math

- GLM-4.6V: —
- Llama 3.1-405B: 18.4 (#290)

| Benchmark | GLM-4.6V | Llama 3.1-405B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 9.7% |
| Omni-MATH | — | 24.9% |
| LMArena Math | — | 1281 |
| MATH Level 5 | — | 49.8% |

## Knowledge

- GLM-4.6V: 38.0 (#149)
- Llama 3.1-405B: 30.4 (#227)

| Benchmark | GLM-4.6V | Llama 3.1-405B |
|---|---|---|
| LMArena Expert | 1371 | 1243 |
| GPQA Diamond | — | 50.9% |
| MMLU-Pro | — | 72.3% |
| Confabulations | — | 17.6% |
| GPQA (HELM) | — | 52.2% |
| ARC (AI2) Challenge | — | 95.3% |
| MMLU | — | 84.5% |
| TriviaQA | — | 82.7% |

## Multimodal

- GLM-4.6V: 34.8 (#90)
- Llama 3.1-405B: —

| Benchmark | GLM-4.6V | Llama 3.1-405B |
|---|---|---|
| LMArena Vision | 1164 | — |

## Multilingual

- GLM-4.6V: 48.6 (#141)
- Llama 3.1-405B: 40.7 (#214)

| Benchmark | GLM-4.6V | Llama 3.1-405B |
|---|---|---|
| LMArena Non-English | 1359 | 1248 |
| LMArena Chinese | 1425 | 1242 |
| LMArena Russian | 1340 | 1265 |
| LMArena French | — | 1279 |
| LMArena German | — | 1252 |
| LMArena Japanese | — | 1208 |
| LMArena Korean | — | 1184 |
| LMArena Spanish | — | 1260 |

## Instruction Following

- GLM-4.6V: 71.4 (#151)
- Llama 3.1-405B: 65.9 (#214)

| Benchmark | GLM-4.6V | Llama 3.1-405B |
|---|---|---|
| LMArena Instruction Following | 1352 | 1259 |
| IFEval | — | 81.1% |

## Long Context

- GLM-4.6V: 41.3 (#143)
- Llama 3.1-405B: 38.4 (#197)

| Benchmark | GLM-4.6V | Llama 3.1-405B |
|---|---|---|
| LMArena Longer Query | 1358 | 1266 |

## Writing & Preference

- GLM-4.6V: 56.6 (#137)
- Llama 3.1-405B: 38.9 (#251)

| Benchmark | GLM-4.6V | Llama 3.1-405B |
|---|---|---|
| LMArena Text | 1377 | 1284 |
| LMArena Creative Writing | 1347 | 1262 |
| LMArena Multi-Turn | 1360 | 1297 |
| EQ-Bench Creative Writing | — | 870 |
| WildBench | — | 78.3% |

## FAQ

### Is GLM-4.6V better than Llama 3.1-405B?

GLM-4.6V is the stronger model overall, scoring 41.3 to 30.7 on the Noometry Index.

### Is GLM-4.6V or Llama 3.1-405B better for coding?

GLM-4.6V scores higher on coding benchmarks: 40.9 versus 33.1 in the Noometry coding category.

### How many benchmarks do GLM-4.6V and Llama 3.1-405B share?

11 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and Llama 3.1-405B has 42.