# GLM-4.6V vs gpt-oss-20b

> GLM-4.6V is the stronger model overall, scoring 40.9 to 32.1 on the Noometry Index. gpt-oss-20b costs 13× less per token, which makes it the better buy when GLM-4.6V's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/glm-4-6v-vs-gpt-oss-20b
- Last updated: 2026-10-10
- Shared benchmarks: 11

## Summary

- They share 11 benchmarks with published results for both. GLM-4.6V scores higher in 7 categories and gpt-oss-20b in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-4.6V leads 56.8 to 35.8.
- gpt-oss-20b is cheaper at $0.018 / $0.09 per million input/output tokens, against $0.30 / $0.90 for GLM-4.6V.
- gpt-oss-20b accepts more context: 131K tokens versus 128K.

## Snapshot

| | GLM-4.6V | gpt-oss-20b |
|---|---|---|
| Provider | Z.ai (Zhipu) | OpenAI |
| Noometry Index | 40.9 | 32.1 |
| Rank | 133 | 249 |
| Context | 128K | 131K |
| Input $/M | $0.30 | $0.018 |
| Output $/M | $0.90 | $0.09 |
| Weights | Open | Open |

## Coding

- GLM-4.6V: 40.2 (#128)
- gpt-oss-20b: 37.1 (#185)

| Benchmark | GLM-4.6V | gpt-oss-20b |
|---|---|---|
| LMArena Coding | 1390 | 1307 |
| SciCode | — | 34.4% |
| WeirdML | — | 40.9% |
| ALE-Bench | — | 566.05 |

## Agentic & Tool Use

- GLM-4.6V: —
- gpt-oss-20b: 9.2 (#146)

| Benchmark | GLM-4.6V | gpt-oss-20b |
|---|---|---|
| Terminal-Bench | — | 3.4% |

## Reasoning

- GLM-4.6V: 26.5 (#117)
- gpt-oss-20b: 18.8 (#251)

| Benchmark | GLM-4.6V | gpt-oss-20b |
|---|---|---|
| LMArena Hard Prompts | 1368 | 1274 |
| Kagi LLM Benchmark | — | 53.2% |
| CritPt | — | 1.4% |
| Chess Puzzles | — | 4% |
| DTBench | — | 68% |
| LMCA | — | 14.5% |
| Epoch Capabilities Index | — | 137.81 |

## Math

- GLM-4.6V: —
- gpt-oss-20b: 37.6 (#93)

| Benchmark | GLM-4.6V | gpt-oss-20b |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 65.3% |
| Omni-MATH | — | 56.5% |
| LMArena Math | — | 1317 |

## Knowledge

- GLM-4.6V: 37.4 (#148)
- gpt-oss-20b: 34.6 (#186)

| Benchmark | GLM-4.6V | gpt-oss-20b |
|---|---|---|
| LMArena Expert | 1372 | 1258 |
| GPQA Diamond | — | 60.8% |
| MMLU-Pro | — | 74% |
| GPQA (HELM) | — | 59.4% |

## Multimodal

- GLM-4.6V: 34.2 (#83)
- gpt-oss-20b: —

| Benchmark | GLM-4.6V | gpt-oss-20b |
|---|---|---|
| LMArena Vision | 1164 | — |

## Multilingual

- GLM-4.6V: 48.8 (#135)
- gpt-oss-20b: 42.4 (#192)

| Benchmark | GLM-4.6V | gpt-oss-20b |
|---|---|---|
| LMArena Non-English | 1359 | 1269 |
| LMArena Chinese | 1426 | 1311 |
| LMArena Russian | 1341 | 1279 |
| LMArena German | — | 1249 |
| LMArena Japanese | — | 1245 |
| LMArena Korean | — | 1239 |
| LMArena Spanish | — | 1267 |

## Instruction Following

- GLM-4.6V: 71.6 (#145)
- gpt-oss-20b: 62.0 (#235)

| Benchmark | GLM-4.6V | gpt-oss-20b |
|---|---|---|
| LMArena Instruction Following | 1351 | 1236 |
| IFEval | — | 73.2% |

## Long Context

- GLM-4.6V: 41.3 (#138)
- gpt-oss-20b: 37.9 (#203)

| Benchmark | GLM-4.6V | gpt-oss-20b |
|---|---|---|
| LMArena Longer Query | 1358 | 1251 |

## Writing & Preference

- GLM-4.6V: 56.8 (#132)
- gpt-oss-20b: 35.8 (#260)

| Benchmark | GLM-4.6V | gpt-oss-20b |
|---|---|---|
| LMArena Text | 1377 | 1288 |
| LMArena Creative Writing | 1347 | 1201 |
| LMArena Multi-Turn | 1359 | 1268 |
| EQ-Bench Creative Writing | — | 666 |
| WildBench | — | 73.7% |

## FAQ

### Is GLM-4.6V better than gpt-oss-20b?

GLM-4.6V is the stronger model overall, scoring 40.9 to 32.1 on the Noometry Index. gpt-oss-20b costs 13× less per token, which makes it the better buy when GLM-4.6V's lead doesn't matter for your workload.

### Which is cheaper, GLM-4.6V or gpt-oss-20b?

gpt-oss-20b is cheaper. It lists at $0.018 per million input tokens and $0.09 per million output tokens; GLM-4.6V lists at $0.30 and $0.90.

### Is GLM-4.6V or gpt-oss-20b better for coding?

GLM-4.6V scores higher on coding benchmarks: 40.2 versus 37.1 in the Noometry coding category.

### Which has the bigger context window?

gpt-oss-20b does, with 131K tokens against 128K.

### How many benchmarks do GLM-4.6V and gpt-oss-20b share?

11 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and gpt-oss-20b has 34.