# GLM-4.6 vs Olmo 7b Instruct

> GLM-4.6 is the stronger model overall, scoring 41.4 to 30.3 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-4-6-vs-olmo-7b-instruct
- Last updated: 2026-10-11
- Shared benchmarks: 10

## Summary

- They share 10 benchmarks with published results for both. GLM-4.6 scores higher in 6 categories and Olmo 7b Instruct in 0 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-4.6 leads 61.1 to 25.8.

## Snapshot

| | GLM-4.6 | Olmo 7b Instruct |
|---|---|---|
| Provider | Z.ai (Zhipu) | Allen Institute for AI (Ai2) |
| Noometry Index | 41.4 | 30.3 |
| Rank | 135 | 295 |
| Context | 205K | — |
| Input $/M | $0.60 | — |
| Output $/M | $2.20 | — |
| Weights | Open | Open |

## Coding

- GLM-4.6: 40.1 (#148)
- Olmo 7b Instruct: 29.6 (#303)

| Benchmark | GLM-4.6 | Olmo 7b Instruct |
|---|---|---|
| LMArena Coding | 1449 | 1016 |
| 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)
- Olmo 7b Instruct: —

| Benchmark | GLM-4.6 | Olmo 7b Instruct |
|---|---|---|
| Terminal-Bench | 24.5% | — |
| Berkeley Function Calling Leaderboard | 72.4% | — |

## Reasoning

- GLM-4.6: 23.7 (#172)
- Olmo 7b Instruct: 18.8 (#274)

| Benchmark | GLM-4.6 | Olmo 7b Instruct |
|---|---|---|
| LMArena Hard Prompts | 1440 | 993 |
| Kagi LLM Benchmark | 47.4% | — |
| CritPt | 1.1% | — |

## Math

- GLM-4.6: 39.1 (#111)
- Olmo 7b Instruct: 30.2 (#237)

| Benchmark | GLM-4.6 | Olmo 7b Instruct |
|---|---|---|
| LMArena Math | 1432 | 1018 |
| FrontierMath (Feb 2025 set) | 3.8% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |

## Knowledge

- GLM-4.6: 40.2 (#124)
- Olmo 7b Instruct: —

| Benchmark | GLM-4.6 | Olmo 7b Instruct |
|---|---|---|
| Vectara Hallucination Rate | 9.5% | — |
| LMArena Expert | 1431 | — |

## Multilingual

- GLM-4.6: 53.5 (#66)
- Olmo 7b Instruct: 24.0 (#291)

| Benchmark | GLM-4.6 | Olmo 7b Instruct |
|---|---|---|
| LMArena Non-English | 1426 | 977 |
| LMArena Chinese | 1499 | 1014 |
| LMArena Russian | 1419 | 947 |
| LMArena French | 1459 | — |
| LMArena German | 1447 | — |
| LMArena Japanese | 1393 | — |
| LMArena Korean | 1400 | — |
| LMArena Spanish | 1436 | — |

## Instruction Following

- GLM-4.6: 74.3 (#98)
- Olmo 7b Instruct: 49.0 (#301)

| Benchmark | GLM-4.6 | Olmo 7b Instruct |
|---|---|---|
| LMArena Instruction Following | 1410 | 978 |

## Long Context

- GLM-4.6: 43.4 (#94)
- Olmo 7b Instruct: —

| Benchmark | GLM-4.6 | Olmo 7b Instruct |
|---|---|---|
| LMArena Longer Query | 1422 | — |

## Writing & Preference

- GLM-4.6: 61.1 (#90)
- Olmo 7b Instruct: 25.8 (#303)

| Benchmark | GLM-4.6 | Olmo 7b Instruct |
|---|---|---|
| LMArena Text | 1440 | 1032 |
| LMArena Creative Writing | 1411 | 990 |
| LMArena Multi-Turn | 1427 | 1007 |
| EQ-Bench Creative Writing | 1411 | — |

## FAQ

### Is GLM-4.6 better than Olmo 7b Instruct?

GLM-4.6 is the stronger model overall, scoring 41.4 to 30.3 on the Noometry Index.

### Is GLM-4.6 or Olmo 7b Instruct better for coding?

GLM-4.6 scores higher on coding benchmarks: 40.1 versus 29.6 in the Noometry coding category.

### How many benchmarks do GLM-4.6 and Olmo 7b Instruct share?

10 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Olmo 7b Instruct has 10.