# GLM-5 vs Llama 3.1-405B

> GLM-5 is the stronger model overall, scoring 46.1 to 30.7 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-5-vs-llama-3-1-405b
- Last updated: 2026-10-10
- Shared benchmarks: 25

## Summary

- They share 25 benchmarks with published results for both. GLM-5 scores higher in 9 categories and Llama 3.1-405B in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5 leads 46.4 to 18.4.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 80% for GLM-5 and 9.7% for Llama 3.1-405B.

## Snapshot

| | GLM-5 | Llama 3.1-405B |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 46.1 | 30.7 |
| Rank | 66 | 288 |
| Context | 205K | — |
| Input $/M | $1 | — |
| Output $/M | $3.20 | — |
| Weights | Open | Open |

## Coding

- GLM-5: 49.0 (#52)
- Llama 3.1-405B: 33.1 (#262)

| Benchmark | GLM-5 | Llama 3.1-405B |
|---|---|---|
| WeirdML | 48.2% | 21.4% |
| LMArena Coding | 1461 | 1291 |
| SWE-bench Verified | 72.1% | — |
| SWE-bench Verified (bash only) | 72.8% | — |
| LMArena WebDev | 1434 | — |
| SWE-bench Multilingual | 69.7% | — |
| ALE-Bench | 765.62 | — |

## Agentic & Tool Use

- GLM-5: 31.1 (#71)
- Llama 3.1-405B: 21.0 (#140)

| Benchmark | GLM-5 | Llama 3.1-405B |
|---|---|---|
| Terminal-Bench | 52.4% | — |
| TheAgentCompany | — | 7.4% |
| τ²-bench Airline | 82.5% | — |
| τ²-bench Banking | 9.8% | — |
| τ²-bench Retail | 73.7% | — |
| τ²-bench Telecom | 86.8% | — |
| Cybench | — | 7.5% |
| Vending-Bench 2 | 4,432 | — |

## Reasoning

- GLM-5: 27.6 (#116)
- Llama 3.1-405B: 16.8 (#300)

| Benchmark | GLM-5 | Llama 3.1-405B |
|---|---|---|
| SimpleBench | 53.2% | 23% |
| Kagi LLM Benchmark | 75% | 45% |
| LMArena Hard Prompts | 1452 | 1269 |
| Epoch Capabilities Index | 145.83 | 128.75 |
| ForecastBench | 61 | 59.9 |
| ARC-AGI-2 | 4.9% | — |
| NYT Connections (extended) | 74.8% | — |
| ARC-AGI-1 | 44.7% | — |
| Chess Puzzles | 10% | — |
| DTBench | — | 61.4% |
| BIG-Bench Hard | — | 82.9% |
| HellaSwag | — | 89.2% |
| PIQA | — | 85.9% |
| WinoGrande | — | 89.2% |

## Math

- GLM-5: 46.4 (#71)
- Llama 3.1-405B: 18.4 (#290)

| Benchmark | GLM-5 | Llama 3.1-405B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 80% | 9.7% |
| LMArena Math | 1440 | 1281 |
| MathArena Final-Answer Competitions | 65.7% | — |
| Omni-MATH | — | 24.9% |
| MATH Level 5 | — | 49.8% |
| FrontierMath (Feb 2025 set) | 16.4% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |

## Knowledge

- GLM-5: 52.3 (#64)
- Llama 3.1-405B: 30.4 (#227)

| Benchmark | GLM-5 | Llama 3.1-405B |
|---|---|---|
| GPQA Diamond | 87.8% | 50.9% |
| LMArena Expert | 1454 | 1243 |
| MMLU-Pro | — | 72.3% |
| Confabulations | — | 17.6% |
| Vectara Hallucination Rate | 10.1% | — |
| GPQA (HELM) | — | 52.2% |
| ARC (AI2) Challenge | — | 95.3% |
| MMLU | — | 84.5% |
| TriviaQA | — | 82.7% |

## Multilingual

- GLM-5: 53.7 (#58)
- Llama 3.1-405B: 40.7 (#214)

| Benchmark | GLM-5 | Llama 3.1-405B |
|---|---|---|
| LMArena Non-English | 1430 | 1248 |
| LMArena Chinese | 1511 | 1242 |
| LMArena French | 1455 | 1279 |
| LMArena German | 1445 | 1252 |
| LMArena Japanese | 1416 | 1208 |
| LMArena Korean | 1423 | 1184 |
| LMArena Russian | 1436 | 1265 |
| LMArena Spanish | 1454 | 1260 |

## Instruction Following

- GLM-5: 75.2 (#67)
- Llama 3.1-405B: 65.9 (#214)

| Benchmark | GLM-5 | Llama 3.1-405B |
|---|---|---|
| LMArena Instruction Following | 1428 | 1259 |
| IFEval | — | 81.1% |

## Long Context

- GLM-5: 44.7 (#60)
- Llama 3.1-405B: 38.4 (#197)

| Benchmark | GLM-5 | Llama 3.1-405B |
|---|---|---|
| LMArena Longer Query | 1446 | 1266 |
| CL-bench | 18.7% | — |

## Writing & Preference

- GLM-5: 66.0 (#38)
- Llama 3.1-405B: 38.9 (#251)

| Benchmark | GLM-5 | Llama 3.1-405B |
|---|---|---|
| LMArena Text | 1446 | 1284 |
| LMArena Creative Writing | 1439 | 1262 |
| EQ-Bench Creative Writing | 1601 | 870 |
| LMArena Multi-Turn | 1456 | 1297 |
| WildBench | — | 78.3% |

## FAQ

### Is GLM-5 better than Llama 3.1-405B?

GLM-5 is the stronger model overall, scoring 46.1 to 30.7 on the Noometry Index.

### Is GLM-5 or Llama 3.1-405B better for coding?

GLM-5 scores higher on coding benchmarks: 49.0 versus 33.1 in the Noometry coding category.

### How many benchmarks do GLM-5 and Llama 3.1-405B share?

25 benchmarks have published results for both models. GLM-5 has 45 scored results on Noometry and Llama 3.1-405B has 42.