# GLM-4.5 vs Llama 3.1-70B

> GLM-4.5 is the stronger model overall, scoring 41.4 to 29.4 on the Noometry Index. Llama 3.1-70B costs 2.5× 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-3-1-70b
- Last updated: 2026-10-10
- Shared benchmarks: 19

## Summary

- They share 19 benchmarks with published results for both. GLM-4.5 scores higher in 8 categories and Llama 3.1-70B in 0 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-4.5 leads 36.3 to 12.7.
- The biggest single-benchmark swing is WeirdML: 40.6% for GLM-4.5 and 9% for Llama 3.1-70B.
- Llama 3.1-70B is cheaper at $0.40 / $0.40 per million input/output tokens, against $0.60 / $2.20 for GLM-4.5.
- GLM-4.5 accepts more context: 131K tokens versus 128K.

## Snapshot

| | GLM-4.5 | Llama 3.1-70B |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 41.4 | 29.4 |
| Rank | 125 | 299 |
| Context | 131K | 128K |
| Input $/M | $0.60 | $0.40 |
| Output $/M | $2.20 | $0.40 |
| Weights | Open | Open |

## Coding

- GLM-4.5: 41.1 (#121)
- Llama 3.1-70B: 29.8 (#292)

| Benchmark | GLM-4.5 | Llama 3.1-70B |
|---|---|---|
| WeirdML | 40.6% | 9% |
| LMArena Coding | 1434 | 1260 |
| SWE-bench Verified (bash only) | 54.2% | — |
| BigCodeBench Instruct | — | 46.1% |
| BigCodeBench Complete | — | 54.8% |
| ALE-Bench | 344.82 | — |
| AlgoTune | 1.52 | — |

## Agentic & Tool Use

- GLM-4.5: —
- Llama 3.1-70B: 24.9 (#104)

| Benchmark | GLM-4.5 | Llama 3.1-70B |
|---|---|---|
| TheAgentCompany | — | 6.9% |
| BALROG | — | 27.9% |

## Reasoning

- GLM-4.5: 27.7 (#99)
- Llama 3.1-70B: 20.8 (#215)

| Benchmark | GLM-4.5 | Llama 3.1-70B |
|---|---|---|
| LMArena Hard Prompts | 1430 | 1241 |
| Kagi LLM Benchmark | 57.9% | — |
| DTBench | — | 60% |
| LMCA | — | 14.8% |
| Epoch Capabilities Index | — | 125.91 |

## Math

- GLM-4.5: 36.3 (#119)
- Llama 3.1-70B: 12.7 (#298)

| Benchmark | GLM-4.5 | Llama 3.1-70B |
|---|---|---|
| LMArena Math | 1427 | 1252 |
| OTIS Mock AIME 2024-2025 | — | 3.6% |
| Omni-MATH | — | 21% |
| MATH Level 5 | — | 36.7% |

## Knowledge

- GLM-4.5: 35.5 (#172)
- Llama 3.1-70B: 24.1 (#264)

| Benchmark | GLM-4.5 | Llama 3.1-70B |
|---|---|---|
| LMArena Expert | 1433 | 1209 |
| GPQA Diamond | — | 44.2% |
| Humanity's Last Exam | 8.3% | — |
| MMLU-Pro | — | 65.3% |
| Confabulations | 11.3% | — |
| GPQA (HELM) | — | 42.6% |
| MMLU | — | 80.1% |

## Multilingual

- GLM-4.5: 53.0 (#74)
- Llama 3.1-70B: 38.9 (#220)

| Benchmark | GLM-4.5 | Llama 3.1-70B |
|---|---|---|
| LMArena Non-English | 1417 | 1219 |
| LMArena Chinese | 1465 | 1215 |
| LMArena French | 1423 | 1260 |
| LMArena German | 1406 | 1222 |
| LMArena Japanese | 1416 | 1132 |
| LMArena Korean | 1382 | 1140 |
| LMArena Russian | 1414 | 1234 |
| LMArena Spanish | 1454 | 1253 |

## Instruction Following

- GLM-4.5: 74.3 (#100)
- Llama 3.1-70B: 65.5 (#218)

| Benchmark | GLM-4.5 | Llama 3.1-70B |
|---|---|---|
| LMArena Instruction Following | 1405 | 1231 |
| IFEval | — | 82.1% |

## Long Context

- GLM-4.5: 38.2 (#196)
- Llama 3.1-70B: 37.6 (#208)

| Benchmark | GLM-4.5 | Llama 3.1-70B |
|---|---|---|
| LMArena Longer Query | 1413 | 1241 |
| Fiction.LiveBench | 58.3% | — |

## Writing & Preference

- GLM-4.5: 57.7 (#121)
- Llama 3.1-70B: 35.6 (#262)

| Benchmark | GLM-4.5 | Llama 3.1-70B |
|---|---|---|
| LMArena Text | 1430 | 1261 |
| LMArena Creative Writing | 1395 | 1232 |
| EQ-Bench Creative Writing | 1343 | 784 |
| LMArena Multi-Turn | 1415 | 1256 |
| Short-Story Creative Writing | 73.4% | — |
| WildBench | — | 75.8% |

## FAQ

### Is GLM-4.5 better than Llama 3.1-70B?

GLM-4.5 is the stronger model overall, scoring 41.4 to 29.4 on the Noometry Index. Llama 3.1-70B costs 2.5× 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 3.1-70B?

Llama 3.1-70B is cheaper. It lists at $0.40 per million input tokens and $0.40 per million output tokens; GLM-4.5 lists at $0.60 and $2.20.

### Is GLM-4.5 or Llama 3.1-70B better for coding?

GLM-4.5 scores higher on coding benchmarks: 41.1 versus 29.8 in the Noometry coding category.

### Which has the bigger context window?

GLM-4.5 does, with 131K tokens against 128K.

### How many benchmarks do GLM-4.5 and Llama 3.1-70B share?

19 benchmarks have published results for both models. GLM-4.5 has 27 scored results on Noometry and Llama 3.1-70B has 35.