# GLM-4.5 vs Llama 3.2 3B

> GLM-4.5 is the stronger model overall, scoring 41.4 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-4.5's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/glm-4-5-vs-llama-3-2-3b
- Last updated: 2026-10-10
- Shared benchmarks: 14

## Summary

- They share 14 benchmarks with published results for both. GLM-4.5 scores higher in 8 categories and Llama 3.2 3B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-4.5 leads 57.7 to 24.9.
- Llama 3.2 3B is cheaper at $0.05 / $0.33 per million input/output tokens, against $0.60 / $2.20 for GLM-4.5.

## Snapshot

| | GLM-4.5 | Llama 3.2 3B |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 41.4 | 28.4 |
| Rank | 125 | 318 |
| Context | 131K | 131K |
| Input $/M | $0.60 | $0.05 |
| Output $/M | $2.20 | $0.33 |
| Weights | Open | Open |

## Coding

- GLM-4.5: 41.1 (#121)
- Llama 3.2 3B: 27.1 (#314)

| Benchmark | GLM-4.5 | Llama 3.2 3B |
|---|---|---|
| LMArena Coding | 1434 | 1098 |
| SWE-bench Verified (bash only) | 54.2% | — |
| WeirdML | 40.6% | — |
| BigCodeBench Instruct | — | 23.4% |
| BigCodeBench Complete | — | 28.3% |
| ALE-Bench | 344.82 | — |
| AlgoTune | 1.52 | — |

## Agentic & Tool Use

- GLM-4.5: —
- Llama 3.2 3B: 19.9 (#135)

| Benchmark | GLM-4.5 | Llama 3.2 3B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 21.9% |
| BALROG | — | 10.1% |

## Reasoning

- GLM-4.5: 27.7 (#99)
- Llama 3.2 3B: 20.1 (#225)

| Benchmark | GLM-4.5 | Llama 3.2 3B |
|---|---|---|
| LMArena Hard Prompts | 1430 | 1095 |
| Kagi LLM Benchmark | 57.9% | — |

## Math

- GLM-4.5: 36.3 (#119)
- Llama 3.2 3B: 29.9 (#213)

| Benchmark | GLM-4.5 | Llama 3.2 3B |
|---|---|---|
| LMArena Math | 1427 | 1126 |

## Knowledge

- GLM-4.5: 35.5 (#172)
- Llama 3.2 3B: 29.1 (#232)

| Benchmark | GLM-4.5 | Llama 3.2 3B |
|---|---|---|
| LMArena Expert | 1433 | 1090 |
| Humanity's Last Exam | 8.3% | — |
| Confabulations | 11.3% | — |

## Multilingual

- GLM-4.5: 53.0 (#74)
- Llama 3.2 3B: 26.4 (#276)

| Benchmark | GLM-4.5 | Llama 3.2 3B |
|---|---|---|
| LMArena Non-English | 1417 | 1019 |
| LMArena Chinese | 1465 | 1017 |
| LMArena German | 1406 | 1056 |
| LMArena Russian | 1414 | 949 |
| LMArena French | 1423 | — |
| LMArena Japanese | 1416 | — |
| LMArena Korean | 1382 | — |
| LMArena Spanish | 1454 | — |

## Instruction Following

- GLM-4.5: 74.3 (#100)
- Llama 3.2 3B: 56.3 (#270)

| Benchmark | GLM-4.5 | Llama 3.2 3B |
|---|---|---|
| LMArena Instruction Following | 1405 | 1089 |

## Long Context

- GLM-4.5: 38.2 (#196)
- Llama 3.2 3B: 33.4 (#256)

| Benchmark | GLM-4.5 | Llama 3.2 3B |
|---|---|---|
| LMArena Longer Query | 1413 | 1101 |
| Fiction.LiveBench | 58.3% | — |

## Writing & Preference

- GLM-4.5: 57.7 (#121)
- Llama 3.2 3B: 24.9 (#302)

| Benchmark | GLM-4.5 | Llama 3.2 3B |
|---|---|---|
| LMArena Text | 1430 | 1110 |
| LMArena Creative Writing | 1395 | 1094 |
| EQ-Bench Creative Writing | 1343 | 595 |
| LMArena Multi-Turn | 1415 | 1105 |
| Short-Story Creative Writing | 73.4% | — |

## FAQ

### Is GLM-4.5 better than Llama 3.2 3B?

GLM-4.5 is the stronger model overall, scoring 41.4 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-4.5's lead doesn't matter for your workload.

### Which is cheaper, GLM-4.5 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-4.5 lists at $0.60 and $2.20.

### Is GLM-4.5 or Llama 3.2 3B better for coding?

GLM-4.5 scores higher on coding benchmarks: 41.1 versus 27.1 in the Noometry coding category.

### Which has the bigger context window?

Both accept 131K tokens.

### How many benchmarks do GLM-4.5 and Llama 3.2 3B share?

14 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and Llama 3.2 3B has 18.