# GLM-4.7 vs GLM-4.7-Flash

> GLM-4.7 is the stronger model overall, scoring 42.0 to 38.8 on the Noometry Index. GLM-4.7-Flash costs 6.9× less per token, which makes it the better buy when GLM-4.7's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/glm-4-7-vs-glm-4-7-flash
- Last updated: 2026-10-10
- Shared benchmarks: 21

## Summary

- They share 21 benchmarks with published results for both. GLM-4.7 scores higher in 8 categories and GLM-4.7-Flash in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where GLM-4.7 leads 60.9 to 47.4.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 83.3% for GLM-4.7 and 58.3% for GLM-4.7-Flash.
- GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $0.60 / $2.20 for GLM-4.7.
- GLM-4.7 accepts more context: 205K tokens versus 200K.

## Snapshot

| | GLM-4.7 | GLM-4.7-Flash |
|---|---|---|
| Provider | Z.ai (Zhipu) | Z.ai (Zhipu) |
| Noometry Index | 42.0 | 38.8 |
| Rank | 124 | 180 |
| Context | 205K | 200K |
| Input $/M | $0.60 | $0.06 |
| Output $/M | $2.20 | $0.40 |
| Weights | Open | Open |

## Coding

- GLM-4.7: 44.0 (#79)
- GLM-4.7-Flash: 40.6 (#135)

| Benchmark | GLM-4.7 | GLM-4.7-Flash |
|---|---|---|
| LMArena Coding | 1454 | 1383 |
| LMArena WebDev | 1435 | — |
| SciCode | 45.1% | — |
| ALE-Bench | 399.48 | — |

## Agentic & Tool Use

- GLM-4.7: 26.5 (#103)
- GLM-4.7-Flash: —

| Benchmark | GLM-4.7 | GLM-4.7-Flash |
|---|---|---|
| Terminal-Bench | 33.4% | — |
| Vending-Bench 2 | 2,377 | — |

## Reasoning

- GLM-4.7: 24.3 (#164)
- GLM-4.7-Flash: 20.9 (#229)

| Benchmark | GLM-4.7 | GLM-4.7-Flash |
|---|---|---|
| Chess Puzzles | 6% | 0% |
| LMArena Hard Prompts | 1443 | 1356 |
| SimpleBench | 47.7% | — |
| CritPt | 1.7% | — |
| Epoch Capabilities Index | 143.51 | — |

## Math

- GLM-4.7: 38.6 (#135)
- GLM-4.7-Flash: 36.1 (#173)

| Benchmark | GLM-4.7 | GLM-4.7-Flash |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 83.3% | 58.3% |
| LMArena Math | 1423 | 1355 |
| ProofBench | 6% | — |
| FrontierMath (Feb 2025 set) | 2.4% | — |
| FrontierMath Tier 4 (v1) | 0% | — |

## Knowledge

- GLM-4.7: 47.0 (#80)
- GLM-4.7-Flash: 35.5 (#184)

| Benchmark | GLM-4.7 | GLM-4.7-Flash |
|---|---|---|
| GPQA Diamond | 83.3% | 60.5% |
| Vectara Hallucination Rate | 11.7% | 9.3% |
| LMArena Expert | 1424 | 1357 |
| SimpleQA Verified | 32.2% | — |

## Multilingual

- GLM-4.7: 52.8 (#79)
- GLM-4.7-Flash: 46.5 (#158)

| Benchmark | GLM-4.7 | GLM-4.7-Flash |
|---|---|---|
| LMArena Non-English | 1417 | 1330 |
| LMArena Chinese | 1495 | 1403 |
| LMArena French | 1432 | 1332 |
| LMArena German | 1424 | 1337 |
| LMArena Korean | 1399 | 1283 |
| LMArena Russian | 1423 | 1332 |
| LMArena Spanish | 1434 | 1350 |
| LMArena Japanese | 1439 | — |

## Instruction Following

- GLM-4.7: 74.4 (#95)
- GLM-4.7-Flash: 70.1 (#167)

| Benchmark | GLM-4.7 | GLM-4.7-Flash |
|---|---|---|
| LMArena Instruction Following | 1411 | 1327 |

## Long Context

- GLM-4.7: 42.8 (#116)
- GLM-4.7-Flash: 40.9 (#148)

| Benchmark | GLM-4.7 | GLM-4.7-Flash |
|---|---|---|
| LMArena Longer Query | 1432 | 1345 |
| CL-bench | 15.9% | — |
| CL-bench Life | 10.9% | — |

## Writing & Preference

- GLM-4.7: 60.9 (#93)
- GLM-4.7-Flash: 47.4 (#210)

| Benchmark | GLM-4.7 | GLM-4.7-Flash |
|---|---|---|
| LMArena Text | 1435 | 1351 |
| LMArena Creative Writing | 1401 | 1297 |
| EQ-Bench Creative Writing | 1413 | 1125 |
| LMArena Multi-Turn | 1446 | 1342 |

## FAQ

### Is GLM-4.7 better than GLM-4.7-Flash?

GLM-4.7 is the stronger model overall, scoring 42.0 to 38.8 on the Noometry Index. GLM-4.7-Flash costs 6.9× less per token, which makes it the better buy when GLM-4.7's lead doesn't matter for your workload.

### Which is cheaper, GLM-4.7 or GLM-4.7-Flash?

GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; GLM-4.7 lists at $0.60 and $2.20.

### Is GLM-4.7 or GLM-4.7-Flash better for coding?

GLM-4.7 scores higher on coding benchmarks: 44.0 versus 40.6 in the Noometry coding category.

### Which has the bigger context window?

GLM-4.7 does, with 205K tokens against 200K.

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

21 benchmarks have published results for both models. GLM-4.7 has 36 scored results on Noometry and GLM-4.7-Flash has 21.