# GLM-4.7-Flash vs Granite 4.2 8B

> Granite 4.2 8B is the stronger model overall, scoring 40.0 to 38.4 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-4-7-flash-vs-granite-4-2-8b
- Last updated: 2026-10-10
- Shared benchmarks: 11

## Summary

- They share 11 benchmarks with published results for both. GLM-4.7-Flash scores higher in 4 categories and Granite 4.2 8B in 3 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Granite 4.2 8B leads 25.5 to 20.2.
- Granite 4.2 8B is cheaper at $0.06 / $0.25 per million input/output tokens, against $0.06 / $0.40 for GLM-4.7-Flash.
- GLM-4.7-Flash accepts more context: 200K tokens versus 131K.

## Snapshot

| | GLM-4.7-Flash | Granite 4.2 8B |
|---|---|---|
| Provider | Z.ai (Zhipu) | IBM |
| Noometry Index | 38.4 | 40.0 |
| Rank | 175 | 143 |
| Context | 200K | 131K |
| Input $/M | $0.06 | $0.06 |
| Output $/M | $0.40 | $0.25 |
| Weights | Open | Open |

## Coding

- GLM-4.7-Flash: 40.0 (#133)
- Granite 4.2 8B: 39.9 (#138)

| Benchmark | GLM-4.7-Flash | Granite 4.2 8B |
|---|---|---|
| LMArena Coding | 1383 | 1379 |

## Reasoning

- GLM-4.7-Flash: 20.2 (#224)
- Granite 4.2 8B: 25.5 (#130)

| Benchmark | GLM-4.7-Flash | Granite 4.2 8B |
|---|---|---|
| LMArena Hard Prompts | 1356 | 1327 |
| Chess Puzzles | 0% | — |

## Math

- GLM-4.7-Flash: 34.4 (#159)
- Granite 4.2 8B: —

| Benchmark | GLM-4.7-Flash | Granite 4.2 8B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 58.3% | — |
| LMArena Math | 1354 | — |

## Knowledge

- GLM-4.7-Flash: 35.4 (#177)
- Granite 4.2 8B: 37.7 (#144)

| Benchmark | GLM-4.7-Flash | Granite 4.2 8B |
|---|---|---|
| LMArena Expert | 1357 | 1380 |
| GPQA Diamond | 60.5% | — |
| Vectara Hallucination Rate | 9.3% | — |

## Multilingual

- GLM-4.7-Flash: 46.8 (#152)
- Granite 4.2 8B: 44.5 (#173)

| Benchmark | GLM-4.7-Flash | Granite 4.2 8B |
|---|---|---|
| LMArena Non-English | 1331 | 1299 |
| LMArena Chinese | 1403 | 1361 |
| LMArena Russian | 1333 | 1283 |
| LMArena French | 1332 | — |
| LMArena German | 1336 | — |
| LMArena Korean | 1284 | — |
| LMArena Spanish | 1351 | — |

## Instruction Following

- GLM-4.7-Flash: 70.3 (#162)
- Granite 4.2 8B: 68.7 (#183)

| Benchmark | GLM-4.7-Flash | Granite 4.2 8B |
|---|---|---|
| LMArena Instruction Following | 1327 | 1298 |

## Long Context

- GLM-4.7-Flash: 40.9 (#143)
- Granite 4.2 8B: 40.2 (#154)

| Benchmark | GLM-4.7-Flash | Granite 4.2 8B |
|---|---|---|
| LMArena Longer Query | 1345 | 1323 |

## Writing & Preference

- GLM-4.7-Flash: 47.7 (#206)
- Granite 4.2 8B: 49.8 (#183)

| Benchmark | GLM-4.7-Flash | Granite 4.2 8B |
|---|---|---|
| LMArena Text | 1351 | 1319 |
| LMArena Creative Writing | 1297 | 1238 |
| LMArena Multi-Turn | 1342 | 1299 |
| EQ-Bench Creative Writing | 1125 | — |

## FAQ

### Is GLM-4.7-Flash better than Granite 4.2 8B?

Granite 4.2 8B is the stronger model overall, scoring 40.0 to 38.4 on the Noometry Index.

### Which is cheaper, GLM-4.7-Flash or Granite 4.2 8B?

Granite 4.2 8B is cheaper. It lists at $0.06 per million input tokens and $0.25 per million output tokens; GLM-4.7-Flash lists at $0.06 and $0.40.

### Is GLM-4.7-Flash or Granite 4.2 8B better for coding?

They score almost the same on coding (40.0 vs 39.9); test both on your own repository before choosing.

### Which has the bigger context window?

GLM-4.7-Flash does, with 200K tokens against 131K.

### How many benchmarks do GLM-4.7-Flash and Granite 4.2 8B share?

11 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Granite 4.2 8B has 11.