# GLM-4.5V vs Llama 3.1-405B

> GLM-4.5V is the stronger model overall, scoring 39.2 to 30.4 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-4-5v-vs-llama-3-1-405b
- Last updated: 2026-10-10
- Shared benchmarks: 14

## Summary

- They share 14 benchmarks with published results for both. GLM-4.5V scores higher in 8 categories and Llama 3.1-405B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-4.5V leads 34.7 to 17.3.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 59.8% for GLM-4.5V and 45% for Llama 3.1-405B.

## Snapshot

| | GLM-4.5V | Llama 3.1-405B |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 39.2 | 30.4 |
| Rank | 158 | 279 |
| Context | 64K | — |
| Input $/M | $0.60 | — |
| Output $/M | $1.80 | — |
| Weights | Open | Open |

## Coding

- GLM-4.5V: 38.9 (#152)
- Llama 3.1-405B: 32.7 (#257)

| Benchmark | GLM-4.5V | Llama 3.1-405B |
|---|---|---|
| LMArena Coding | 1347 | 1291 |
| WeirdML | — | 21.4% |

## Agentic & Tool Use

- GLM-4.5V: —
- Llama 3.1-405B: 20.9 (#131)

| Benchmark | GLM-4.5V | Llama 3.1-405B |
|---|---|---|
| TheAgentCompany | — | 7.4% |
| Cybench | — | 7.5% |

## Reasoning

- GLM-4.5V: 26.5 (#118)
- Llama 3.1-405B: 16.4 (#293)

| Benchmark | GLM-4.5V | Llama 3.1-405B |
|---|---|---|
| Kagi LLM Benchmark | 59.8% | 45% |
| LMArena Hard Prompts | 1335 | 1270 |
| SimpleBench | — | 23% |
| DTBench | — | 61.4% |
| BIG-Bench Hard | — | 82.9% |
| Epoch Capabilities Index | — | 128.76 |
| ForecastBench | — | 59.9 |
| HellaSwag | — | 89.2% |
| PIQA | — | 85.9% |
| WinoGrande | — | 89.2% |

## Math

- GLM-4.5V: 34.7 (#157)
- Llama 3.1-405B: 17.3 (#283)

| Benchmark | GLM-4.5V | Llama 3.1-405B |
|---|---|---|
| LMArena Math | 1353 | 1281 |
| OTIS Mock AIME 2024-2025 | — | 9.7% |
| Omni-MATH | — | 24.9% |
| MATH Level 5 | — | 49.8% |

## Knowledge

- GLM-4.5V: 36.8 (#155)
- Llama 3.1-405B: 30.4 (#221)

| Benchmark | GLM-4.5V | Llama 3.1-405B |
|---|---|---|
| LMArena Expert | 1353 | 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-4.5V: 33.6 (#86)
- Llama 3.1-405B: —

| Benchmark | GLM-4.5V | Llama 3.1-405B |
|---|---|---|
| LMArena Vision | 1154 | — |

## Multilingual

- GLM-4.5V: 44.9 (#172)
- Llama 3.1-405B: 40.9 (#209)

| Benchmark | GLM-4.5V | Llama 3.1-405B |
|---|---|---|
| LMArena Non-English | 1304 | 1248 |
| LMArena Chinese | 1338 | 1242 |
| LMArena Russian | 1299 | 1265 |
| LMArena Spanish | 1335 | 1259 |
| LMArena French | — | 1278 |
| LMArena German | — | 1252 |
| LMArena Japanese | — | 1208 |
| LMArena Korean | — | 1184 |

## Instruction Following

- GLM-4.5V: 69.4 (#170)
- Llama 3.1-405B: 66.1 (#209)

| Benchmark | GLM-4.5V | Llama 3.1-405B |
|---|---|---|
| LMArena Instruction Following | 1311 | 1259 |
| IFEval | — | 81.1% |

## Long Context

- GLM-4.5V: 39.6 (#166)
- Llama 3.1-405B: 38.4 (#192)

| Benchmark | GLM-4.5V | Llama 3.1-405B |
|---|---|---|
| LMArena Longer Query | 1305 | 1266 |

## Writing & Preference

- GLM-4.5V: 52.7 (#162)
- Llama 3.1-405B: 39.1 (#246)

| Benchmark | GLM-4.5V | Llama 3.1-405B |
|---|---|---|
| LMArena Text | 1333 | 1284 |
| LMArena Creative Writing | 1295 | 1262 |
| LMArena Multi-Turn | 1333 | 1297 |
| EQ-Bench Creative Writing | — | 870 |
| WildBench | — | 78.3% |

## FAQ

### Is GLM-4.5V better than Llama 3.1-405B?

GLM-4.5V is the stronger model overall, scoring 39.2 to 30.4 on the Noometry Index.

### Is GLM-4.5V or Llama 3.1-405B better for coding?

GLM-4.5V scores higher on coding benchmarks: 38.9 versus 32.7 in the Noometry coding category.

### How many benchmarks do GLM-4.5V and Llama 3.1-405B share?

14 benchmarks have published results for both models. GLM-4.5V has 15 scored results on Noometry and Llama 3.1-405B has 42.