# GLM-4.7-Flash vs Llama 13b

> GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 24.4 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-4-7-flash-vs-llama-13b
- Last updated: 2026-10-11
- Shared benchmarks: 8

## Summary

- They share 8 benchmarks with published results for both. GLM-4.7-Flash scores higher in 6 categories and Llama 13b in 0 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-4.7-Flash leads 47.4 to 13.8.

## Snapshot

| | GLM-4.7-Flash | Llama 13b |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 38.8 | 24.4 |
| Rank | 180 | 348 |
| Context | 200K | — |
| Input $/M | $0.06 | — |
| Output $/M | $0.40 | — |
| Weights | Open | Open |

## Coding

- GLM-4.7-Flash: 40.6 (#135)
- Llama 13b: 21.4 (#337)

| Benchmark | GLM-4.7-Flash | Llama 13b |
|---|---|---|
| LMArena Coding | 1383 | 683 |

## Reasoning

- GLM-4.7-Flash: 20.9 (#229)
- Llama 13b: 14.0 (#329)

| Benchmark | GLM-4.7-Flash | Llama 13b |
|---|---|---|
| LMArena Hard Prompts | 1356 | 728 |
| Chess Puzzles | 0% | — |
| BIG-Bench Hard | — | 37.9% |
| Epoch Capabilities Index | — | 100.58 |
| HellaSwag | — | 79.2% |
| LAMBADA | — | 75.2% |
| PIQA | — | 80.1% |
| WinoGrande | — | 73% |

## Math

- GLM-4.7-Flash: 36.1 (#173)
- Llama 13b: 26.7 (#256)

| Benchmark | GLM-4.7-Flash | Llama 13b |
|---|---|---|
| LMArena Math | 1355 | 838 |
| OTIS Mock AIME 2024-2025 | 58.3% | — |
| GSM8K | — | 20.6% |

## Knowledge

- GLM-4.7-Flash: 35.5 (#184)
- Llama 13b: —

| Benchmark | GLM-4.7-Flash | Llama 13b |
|---|---|---|
| GPQA Diamond | 60.5% | — |
| Vectara Hallucination Rate | 9.3% | — |
| LMArena Expert | 1357 | — |
| ARC (AI2) Challenge | — | 52.7% |
| BoolQ | — | 78.7% |
| MMLU | — | 47.7% |
| OpenBookQA | — | 56.4% |
| TriviaQA | — | 77.9% |

## Multimodal

- GLM-4.7-Flash: —
- Llama 13b: —

| Benchmark | GLM-4.7-Flash | Llama 13b |
|---|---|---|
| ScienceQA | — | 43.3% |

## Multilingual

- GLM-4.7-Flash: 46.5 (#158)
- Llama 13b: 16.6 (#297)

| Benchmark | GLM-4.7-Flash | Llama 13b |
|---|---|---|
| LMArena Non-English | 1330 | 819 |
| LMArena Chinese | 1403 | — |
| LMArena French | 1332 | — |
| LMArena German | 1337 | — |
| LMArena Korean | 1283 | — |
| LMArena Russian | 1332 | — |
| LMArena Spanish | 1350 | — |

## Instruction Following

- GLM-4.7-Flash: 70.1 (#167)
- Llama 13b: 36.7 (#305)

| Benchmark | GLM-4.7-Flash | Llama 13b |
|---|---|---|
| LMArena Instruction Following | 1327 | 781 |

## Long Context

- GLM-4.7-Flash: 40.9 (#148)
- Llama 13b: —

| Benchmark | GLM-4.7-Flash | Llama 13b |
|---|---|---|
| LMArena Longer Query | 1345 | — |

## Writing & Preference

- GLM-4.7-Flash: 47.4 (#210)
- Llama 13b: 13.8 (#312)

| Benchmark | GLM-4.7-Flash | Llama 13b |
|---|---|---|
| LMArena Text | 1351 | 834 |
| LMArena Creative Writing | 1297 | 794 |
| LMArena Multi-Turn | 1342 | 753 |
| EQ-Bench Creative Writing | 1125 | — |

## FAQ

### Is GLM-4.7-Flash better than Llama 13b?

GLM-4.7-Flash is the stronger model overall, scoring 38.8 to 24.4 on the Noometry Index.

### Is GLM-4.7-Flash or Llama 13b better for coding?

GLM-4.7-Flash scores higher on coding benchmarks: 40.6 versus 21.4 in the Noometry coding category.

### How many benchmarks do GLM-4.7-Flash and Llama 13b share?

8 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Llama 13b has 21.