# GLM-4.6 vs Olmo 3.1 32b Think

> GLM-4.6 is the stronger model overall, scoring 40.9 to 37.3 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-4-6-vs-olmo-3-1-32b-think
- Last updated: 2026-10-10
- Shared benchmarks: 15

## Summary

- They share 15 benchmarks with published results for both. GLM-4.6 scores higher in 7 categories and Olmo 3.1 32b Think in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where GLM-4.6 leads 53.6 to 38.3.

## Snapshot

| | GLM-4.6 | Olmo 3.1 32b Think |
|---|---|---|
| Provider | Z.ai (Zhipu) | Allen Institute for AI (Ai2) |
| Noometry Index | 40.9 | 37.3 |
| Rank | 132 | 191 |
| Context | 205K | — |
| Input $/M | $0.60 | — |
| Output $/M | $2.20 | — |
| Weights | Open | Open |

## Coding

- GLM-4.6: 39.9 (#137)
- Olmo 3.1 32b Think: 37.1 (#186)

| Benchmark | GLM-4.6 | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Coding | 1449 | 1292 |
| SWE-bench Verified (bash only) | 55.4% | — |
| LMArena WebDev | 1339 | — |
| SciCode | 38.4% | — |
| ALE-Bench | 340.82 | — |

## Agentic & Tool Use

- GLM-4.6: 32.1 (#60)
- Olmo 3.1 32b Think: —

| Benchmark | GLM-4.6 | Olmo 3.1 32b Think |
|---|---|---|
| Terminal-Bench | 24.5% | — |
| Berkeley Function Calling Leaderboard | 72.4% | — |

## Reasoning

- GLM-4.6: 23.1 (#168)
- Olmo 3.1 32b Think: 24.1 (#151)

| Benchmark | GLM-4.6 | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Hard Prompts | 1440 | 1272 |
| Kagi LLM Benchmark | 47.4% | — |
| CritPt | 1.1% | — |

## Math

- GLM-4.6: 36.4 (#115)
- Olmo 3.1 32b Think: 33.6 (#170)

| Benchmark | GLM-4.6 | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Math | 1431 | 1305 |
| FrontierMath (Feb 2025 set) | 3.8% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |

## Knowledge

- GLM-4.6: 39.6 (#118)
- Olmo 3.1 32b Think: 35.0 (#178)

| Benchmark | GLM-4.6 | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Expert | 1432 | 1294 |
| Vectara Hallucination Rate | 9.5% | — |

## Multilingual

- GLM-4.6: 53.6 (#62)
- Olmo 3.1 32b Think: 38.3 (#226)

| Benchmark | GLM-4.6 | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Non-English | 1426 | 1210 |
| LMArena Chinese | 1500 | 1241 |
| LMArena French | 1459 | 1262 |
| LMArena German | 1447 | 1260 |
| LMArena Russian | 1418 | 1193 |
| LMArena Spanish | 1436 | 1288 |
| LMArena Japanese | 1394 | — |
| LMArena Korean | 1401 | — |

## Instruction Following

- GLM-4.6: 74.5 (#93)
- Olmo 3.1 32b Think: 65.8 (#213)

| Benchmark | GLM-4.6 | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Instruction Following | 1410 | 1246 |

## Long Context

- GLM-4.6: 43.4 (#91)
- Olmo 3.1 32b Think: 38.6 (#190)

| Benchmark | GLM-4.6 | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Longer Query | 1423 | 1272 |

## Writing & Preference

- GLM-4.6: 61.3 (#86)
- Olmo 3.1 32b Think: 46.4 (#215)

| Benchmark | GLM-4.6 | Olmo 3.1 32b Think |
|---|---|---|
| LMArena Text | 1440 | 1271 |
| LMArena Creative Writing | 1411 | 1226 |
| LMArena Multi-Turn | 1427 | 1252 |
| EQ-Bench Creative Writing | 1411 | — |

## FAQ

### Is GLM-4.6 better than Olmo 3.1 32b Think?

GLM-4.6 is the stronger model overall, scoring 40.9 to 37.3 on the Noometry Index.

### Is GLM-4.6 or Olmo 3.1 32b Think better for coding?

GLM-4.6 scores higher on coding benchmarks: 39.9 versus 37.1 in the Noometry coding category.

### How many benchmarks do GLM-4.6 and Olmo 3.1 32b Think share?

15 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Olmo 3.1 32b Think has 15.