# GLM-4.7-Flash vs Grok 4.6

> Grok 4.6 is the stronger model overall, scoring 56.9 to 38.8 on the Noometry Index. GLM-4.7-Flash costs 21× less per token, which makes it the better buy when Grok 4.6's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/glm-4-7-flash-vs-grok-4-6
- Last updated: 2026-10-10
- Shared benchmarks: 19

## Summary

- They share 19 benchmarks with published results for both. GLM-4.7-Flash scores higher in 0 categories and Grok 4.6 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Grok 4.6 leads 61.4 to 20.9.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 58.3% for GLM-4.7-Flash and 99.2% for Grok 4.6.
- GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $2 / $6 for Grok 4.6.
- Grok 4.6 accepts more context: 500K tokens versus 200K.
- GLM-4.7-Flash has downloadable open weights; the other is API-only.

## Snapshot

| | GLM-4.7-Flash | Grok 4.6 |
|---|---|---|
| Provider | Z.ai (Zhipu) | xAI |
| Noometry Index | 38.8 | 56.9 |
| Rank | 180 | 21 |
| Context | 200K | 500K |
| Input $/M | $0.06 | $2 |
| Output $/M | $0.40 | $6 |
| Weights | Open | Proprietary |

## Coding

- GLM-4.7-Flash: 40.6 (#135)
- Grok 4.6: 58.5 (#16)

| Benchmark | GLM-4.7-Flash | Grok 4.6 |
|---|---|---|
| LMArena Coding | 1383 | 1465 |
| DeepSWE | — | 67.5% |
| FrontierCode | — | 48% |
| CursorBench | — | 41.4% |
| LMArena WebDev | — | 1617 |
| FrontierSWE | — | 25.3% |
| SciCode | — | 56.5% |
| WeirdML | — | 67.3% |
| ALE-Bench | — | 1,508 |

## Agentic & Tool Use

- GLM-4.7-Flash: —
- Grok 4.6: 39.4 (#27)

| Benchmark | GLM-4.7-Flash | Grok 4.6 |
|---|---|---|
| APEX-Agents | — | 65.3% |
| GDP.pdf | — | 17.2% |
| Vending-Bench 2 | — | 9,047 |

## Reasoning

- GLM-4.7-Flash: 20.9 (#229)
- Grok 4.6: 61.4 (#20)

| Benchmark | GLM-4.7-Flash | Grok 4.6 |
|---|---|---|
| Chess Puzzles | 0% | 40% |
| LMArena Hard Prompts | 1356 | 1447 |
| ARC-AGI-2 | — | 67.1% |
| SimpleBench | — | 75.9% |
| NYT Connections (extended) | — | 80% |
| ARC-AGI-1 | — | 87.5% |
| CritPt | — | 19.7% |
| EBR-Bench | — | 30.5% |
| Mystery Game Puzzles | — | 34% |
| DTBench | — | 97.3% |
| LMCA | — | 48.5% |
| Epoch Capabilities Index | — | 156.44 |

## Math

- GLM-4.7-Flash: 36.1 (#173)
- Grok 4.6: 67.0 (#24)

| Benchmark | GLM-4.7-Flash | Grok 4.6 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 58.3% | 99.2% |
| LMArena Math | 1355 | 1423 |
| FrontierMath (Tiers 1-3) | — | 66% |
| FrontierMath Tier 4 | — | 31.7% |
| ProofBench | — | 51% |

## Knowledge

- GLM-4.7-Flash: 35.5 (#184)
- Grok 4.6: 63.3 (#20)

| Benchmark | GLM-4.7-Flash | Grok 4.6 |
|---|---|---|
| GPQA Diamond | 60.5% | 94% |
| LMArena Expert | 1357 | 1467 |
| SimpleQA Verified | — | 49.3% |
| Vectara Hallucination Rate | 9.3% | — |

## Multimodal

- GLM-4.7-Flash: —
- Grok 4.6: 43.6 (#23)

| Benchmark | GLM-4.7-Flash | Grok 4.6 |
|---|---|---|
| LMArena Vision | — | 1263 |
| Blueprint-Bench 2 | — | 33.2% |
| Furniture Assembly | — | 40% |
| LMArena Document | — | 1452 |

## Multilingual

- GLM-4.7-Flash: 46.5 (#158)
- Grok 4.6: 53.0 (#74)

| Benchmark | GLM-4.7-Flash | Grok 4.6 |
|---|---|---|
| LMArena Non-English | 1330 | 1420 |
| LMArena Chinese | 1403 | 1480 |
| LMArena French | 1332 | 1461 |
| LMArena German | 1337 | 1431 |
| LMArena Korean | 1283 | 1397 |
| LMArena Russian | 1332 | 1422 |
| LMArena Spanish | 1350 | 1404 |
| LMArena Japanese | — | 1376 |

## Instruction Following

- GLM-4.7-Flash: 70.1 (#167)
- Grok 4.6: 75.4 (#63)

| Benchmark | GLM-4.7-Flash | Grok 4.6 |
|---|---|---|
| LMArena Instruction Following | 1327 | 1431 |

## Long Context

- GLM-4.7-Flash: 40.9 (#148)
- Grok 4.6: 44.5 (#66)

| Benchmark | GLM-4.7-Flash | Grok 4.6 |
|---|---|---|
| LMArena Longer Query | 1345 | 1454 |

## Writing & Preference

- GLM-4.7-Flash: 47.4 (#210)
- Grok 4.6: 62.3 (#80)

| Benchmark | GLM-4.7-Flash | Grok 4.6 |
|---|---|---|
| LMArena Text | 1351 | 1428 |
| LMArena Creative Writing | 1297 | 1428 |
| LMArena Multi-Turn | 1342 | 1425 |
| EQ-Bench Creative Writing | 1125 | — |

## FAQ

### Is GLM-4.7-Flash better than Grok 4.6?

Grok 4.6 is the stronger model overall, scoring 56.9 to 38.8 on the Noometry Index. GLM-4.7-Flash costs 21× less per token, which makes it the better buy when Grok 4.6's lead doesn't matter for your workload.

### Which is cheaper, GLM-4.7-Flash or Grok 4.6?

GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; Grok 4.6 lists at $2 and $6.

### Is GLM-4.7-Flash or Grok 4.6 better for coding?

Grok 4.6 scores higher on coding benchmarks: 58.5 versus 40.6 in the Noometry coding category.

### Which has the bigger context window?

Grok 4.6 does, with 500K tokens against 200K.

### How many benchmarks do GLM-4.7-Flash and Grok 4.6 share?

19 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Grok 4.6 has 49.