# GLM-4.6 vs Llama 3.2 3B

> GLM-4.6 is the stronger model overall, scoring 40.9 to 28.4 on the Noometry Index. Llama 3.2 3B costs 8.3× less per token, which makes it the better buy when GLM-4.6's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/glm-4-6-vs-llama-3-2-3b
- Last updated: 2026-10-10
- Shared benchmarks: 15

## Summary

- They share 15 benchmarks with published results for both. GLM-4.6 scores higher in 9 categories and Llama 3.2 3B in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-4.6 leads 61.3 to 24.9.
- The biggest single-benchmark swing is Berkeley Function Calling Leaderboard: 72.4% for GLM-4.6 and 21.9% for Llama 3.2 3B.
- Llama 3.2 3B is cheaper at $0.05 / $0.33 per million input/output tokens, against $0.60 / $2.20 for GLM-4.6.
- GLM-4.6 accepts more context: 205K tokens versus 131K.

## Snapshot

| | GLM-4.6 | Llama 3.2 3B |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 40.9 | 28.4 |
| Rank | 132 | 318 |
| Context | 205K | 131K |
| Input $/M | $0.60 | $0.05 |
| Output $/M | $2.20 | $0.33 |
| Weights | Open | Open |

## Coding

- GLM-4.6: 39.9 (#137)
- Llama 3.2 3B: 27.1 (#314)

| Benchmark | GLM-4.6 | Llama 3.2 3B |
|---|---|---|
| LMArena Coding | 1449 | 1098 |
| SWE-bench Verified (bash only) | 55.4% | — |
| LMArena WebDev | 1339 | — |
| SciCode | 38.4% | — |
| BigCodeBench Instruct | — | 23.4% |
| BigCodeBench Complete | — | 28.3% |
| ALE-Bench | 340.82 | — |

## Agentic & Tool Use

- GLM-4.6: 32.1 (#60)
- Llama 3.2 3B: 19.9 (#135)

| Benchmark | GLM-4.6 | Llama 3.2 3B |
|---|---|---|
| Berkeley Function Calling Leaderboard | 72.4% | 21.9% |
| Terminal-Bench | 24.5% | — |
| BALROG | — | 10.1% |

## Reasoning

- GLM-4.6: 23.1 (#168)
- Llama 3.2 3B: 20.1 (#225)

| Benchmark | GLM-4.6 | Llama 3.2 3B |
|---|---|---|
| LMArena Hard Prompts | 1440 | 1095 |
| Kagi LLM Benchmark | 47.4% | — |
| CritPt | 1.1% | — |

## Math

- GLM-4.6: 36.4 (#115)
- Llama 3.2 3B: 29.9 (#213)

| Benchmark | GLM-4.6 | Llama 3.2 3B |
|---|---|---|
| LMArena Math | 1431 | 1126 |
| FrontierMath (Feb 2025 set) | 3.8% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |

## Knowledge

- GLM-4.6: 39.6 (#118)
- Llama 3.2 3B: 29.1 (#232)

| Benchmark | GLM-4.6 | Llama 3.2 3B |
|---|---|---|
| LMArena Expert | 1432 | 1090 |
| Vectara Hallucination Rate | 9.5% | — |

## Multilingual

- GLM-4.6: 53.6 (#62)
- Llama 3.2 3B: 26.4 (#276)

| Benchmark | GLM-4.6 | Llama 3.2 3B |
|---|---|---|
| LMArena Non-English | 1426 | 1019 |
| LMArena Chinese | 1500 | 1017 |
| LMArena German | 1447 | 1056 |
| LMArena Russian | 1418 | 949 |
| LMArena French | 1459 | — |
| LMArena Japanese | 1394 | — |
| LMArena Korean | 1401 | — |
| LMArena Spanish | 1436 | — |

## Instruction Following

- GLM-4.6: 74.5 (#93)
- Llama 3.2 3B: 56.3 (#270)

| Benchmark | GLM-4.6 | Llama 3.2 3B |
|---|---|---|
| LMArena Instruction Following | 1410 | 1089 |

## Long Context

- GLM-4.6: 43.4 (#91)
- Llama 3.2 3B: 33.4 (#256)

| Benchmark | GLM-4.6 | Llama 3.2 3B |
|---|---|---|
| LMArena Longer Query | 1423 | 1101 |

## Writing & Preference

- GLM-4.6: 61.3 (#86)
- Llama 3.2 3B: 24.9 (#302)

| Benchmark | GLM-4.6 | Llama 3.2 3B |
|---|---|---|
| LMArena Text | 1440 | 1110 |
| LMArena Creative Writing | 1411 | 1094 |
| EQ-Bench Creative Writing | 1411 | 595 |
| LMArena Multi-Turn | 1427 | 1105 |

## FAQ

### Is GLM-4.6 better than Llama 3.2 3B?

GLM-4.6 is the stronger model overall, scoring 40.9 to 28.4 on the Noometry Index. Llama 3.2 3B costs 8.3× less per token, which makes it the better buy when GLM-4.6's lead doesn't matter for your workload.

### Which is cheaper, GLM-4.6 or Llama 3.2 3B?

Llama 3.2 3B is cheaper. It lists at $0.05 per million input tokens and $0.33 per million output tokens; GLM-4.6 lists at $0.60 and $2.20.

### Is GLM-4.6 or Llama 3.2 3B better for coding?

GLM-4.6 scores higher on coding benchmarks: 39.9 versus 27.1 in the Noometry coding category.

### Which has the bigger context window?

GLM-4.6 does, with 205K tokens against 131K.

### How many benchmarks do GLM-4.6 and Llama 3.2 3B share?

15 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and Llama 3.2 3B has 18.