# GLM-4.6 vs Llama2 70b Steerlm Chat

> GLM-4.6 is the stronger model overall, scoring 41.4 to 31.8 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-4-6-vs-llama2-70b-steerlm-chat
- Last updated: 2026-10-12
- Shared benchmarks: 9

## Summary

- They share 9 benchmarks with published results for both. GLM-4.6 scores higher in 7 categories and Llama2 70b Steerlm Chat in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-4.6 leads 61.1 to 31.6.

## Snapshot

| | GLM-4.6 | Llama2 70b Steerlm Chat |
|---|---|---|
| Provider | Z.ai (Zhipu) | NVIDIA |
| Noometry Index | 41.4 | 31.8 |
| Rank | 135 | 268 |
| Context | 205K | — |
| Input $/M | $0.60 | — |
| Output $/M | $2.20 | — |
| Weights | Open | Open |

## Coding

- GLM-4.6: 40.1 (#148)
- Llama2 70b Steerlm Chat: 29.9 (#300)

| Benchmark | GLM-4.6 | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Coding | 1449 | 1025 |
| SWE-bench Verified (bash only) | 55.4% | — |
| LMArena WebDev | 1340 | — |
| SciCode | 38.4% | — |
| ALE-Bench | 340.82 | — |

## Agentic & Tool Use

- GLM-4.6: 32.3 (#66)
- Llama2 70b Steerlm Chat: —

| Benchmark | GLM-4.6 | Llama2 70b Steerlm Chat |
|---|---|---|
| Terminal-Bench | 24.5% | — |
| Berkeley Function Calling Leaderboard | 72.4% | — |

## Reasoning

- GLM-4.6: 23.7 (#172)
- Llama2 70b Steerlm Chat: 20.0 (#246)

| Benchmark | GLM-4.6 | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Hard Prompts | 1440 | 1047 |
| Kagi LLM Benchmark | 47.4% | — |
| CritPt | 1.1% | — |

## Math

- GLM-4.6: 39.1 (#111)
- Llama2 70b Steerlm Chat: 31.3 (#226)

| Benchmark | GLM-4.6 | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Math | 1432 | 1072 |
| FrontierMath (Feb 2025 set) | 3.8% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |

## Knowledge

- GLM-4.6: 40.2 (#124)
- Llama2 70b Steerlm Chat: —

| Benchmark | GLM-4.6 | Llama2 70b Steerlm Chat |
|---|---|---|
| Vectara Hallucination Rate | 9.5% | — |
| LMArena Expert | 1431 | — |

## Multilingual

- GLM-4.6: 53.5 (#66)
- Llama2 70b Steerlm Chat: 28.8 (#270)

| Benchmark | GLM-4.6 | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Non-English | 1426 | 1063 |
| LMArena Chinese | 1499 | — |
| LMArena French | 1459 | — |
| LMArena German | 1447 | — |
| LMArena Japanese | 1393 | — |
| LMArena Korean | 1400 | — |
| LMArena Russian | 1419 | — |
| LMArena Spanish | 1436 | — |

## Instruction Following

- GLM-4.6: 74.3 (#98)
- Llama2 70b Steerlm Chat: 54.2 (#279)

| Benchmark | GLM-4.6 | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Instruction Following | 1410 | 1060 |

## Long Context

- GLM-4.6: 43.4 (#94)
- Llama2 70b Steerlm Chat: 30.4 (#288)

| Benchmark | GLM-4.6 | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Longer Query | 1422 | 998 |

## Writing & Preference

- GLM-4.6: 61.1 (#90)
- Llama2 70b Steerlm Chat: 31.6 (#283)

| Benchmark | GLM-4.6 | Llama2 70b Steerlm Chat |
|---|---|---|
| LMArena Text | 1440 | 1098 |
| LMArena Creative Writing | 1411 | 1091 |
| LMArena Multi-Turn | 1427 | 1058 |
| EQ-Bench Creative Writing | 1411 | — |

## FAQ

### Is GLM-4.6 better than Llama2 70b Steerlm Chat?

GLM-4.6 is the stronger model overall, scoring 41.4 to 31.8 on the Noometry Index.

### Is GLM-4.6 or Llama2 70b Steerlm Chat better for coding?

GLM-4.6 scores higher on coding benchmarks: 40.1 versus 29.9 in the Noometry coding category.

### How many benchmarks do GLM-4.6 and Llama2 70b Steerlm Chat share?

9 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Llama2 70b Steerlm Chat has 9.