# Gemini 3.6 Flash vs GLM-4.7

> Gemini 3.6 Flash is the stronger model overall, scoring 54.1 to 42.0 on the Noometry Index. GLM-4.7 costs 1.5× less per token, which makes it the better buy when Gemini 3.6 Flash's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/gemini-3-6-flash-vs-glm-4-7
- Last updated: 2026-10-11
- Shared benchmarks: 28

## Summary

- They share 28 benchmarks with published results for both. Gemini 3.6 Flash scores higher in 9 categories and GLM-4.7 in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Gemini 3.6 Flash leads 58.8 to 24.3.
- The biggest single-benchmark swing is Chess Puzzles: 43% for Gemini 3.6 Flash and 6% for GLM-4.7.
- GLM-4.7 is cheaper at $0.60 / $2.20 per million input/output tokens, against $0.75 / $3.75 for Gemini 3.6 Flash.
- Gemini 3.6 Flash accepts more context: 1.05M tokens versus 205K.
- GLM-4.7 has downloadable open weights; the other is API-only.

## Snapshot

| | Gemini 3.6 Flash | GLM-4.7 |
|---|---|---|
| Provider | Google | Z.ai (Zhipu) |
| Noometry Index | 54.1 | 42.0 |
| Rank | 33 | 124 |
| Context | 1.05M | 205K |
| Input $/M | $0.75 | $0.60 |
| Output $/M | $3.75 | $2.20 |
| Weights | Proprietary | Open |

## Coding

- Gemini 3.6 Flash: 50.0 (#48)
- GLM-4.7: 44.0 (#79)

| Benchmark | Gemini 3.6 Flash | GLM-4.7 |
|---|---|---|
| LMArena WebDev | 1538 | 1435 |
| SciCode | 52.7% | 45.1% |
| LMArena Coding | 1491 | 1454 |
| ALE-Bench | 715.52 | 399.48 |
| DeepSWE | 46.7% | — |
| FrontierCode | 34.4% | — |
| WeirdML | 56.1% | — |

## Agentic & Tool Use

- Gemini 3.6 Flash: 32.3 (#65)
- GLM-4.7: 26.5 (#103)

| Benchmark | Gemini 3.6 Flash | GLM-4.7 |
|---|---|---|
| Terminal-Bench | — | 33.4% |
| APEX-Agents | 46.9% | — |
| GDP.pdf | 14% | — |
| Vending-Bench 2 | — | 2,377 |

## Reasoning

- Gemini 3.6 Flash: 58.8 (#22)
- GLM-4.7: 24.3 (#164)

| Benchmark | Gemini 3.6 Flash | GLM-4.7 |
|---|---|---|
| CritPt | 10.6% | 1.7% |
| Chess Puzzles | 43% | 6% |
| LMArena Hard Prompts | 1485 | 1443 |
| Epoch Capabilities Index | 154.25 | 143.51 |
| ARC-AGI-2 | 60.4% | — |
| SimpleBench | — | 47.7% |
| NYT Connections (extended) | 89% | — |
| ARC-AGI-1 | 91.2% | — |
| Mystery Game Puzzles | 30% | — |
| DTBench | 95.5% | — |
| LMCA | 44.9% | — |

## Math

- Gemini 3.6 Flash: 57.3 (#40)
- GLM-4.7: 38.6 (#135)

| Benchmark | Gemini 3.6 Flash | GLM-4.7 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 94.2% | 83.3% |
| ProofBench | 36% | 6% |
| LMArena Math | 1505 | 1423 |
| FrontierMath (Tiers 1-3) | 58.9% | — |
| FrontierMath Tier 4 | 22% | — |
| MathArena Final-Answer Competitions | 70.8% | — |
| FrontierMath (Feb 2025 set) | — | 2.4% |
| FrontierMath Tier 4 (v1) | — | 0% |

## Knowledge

- Gemini 3.6 Flash: 67.8 (#8)
- GLM-4.7: 47.0 (#80)

| Benchmark | Gemini 3.6 Flash | GLM-4.7 |
|---|---|---|
| GPQA Diamond | 94.1% | 83.3% |
| SimpleQA Verified | 66.2% | 32.2% |
| LMArena Expert | 1488 | 1424 |
| Vectara Hallucination Rate | — | 11.7% |

## Multimodal

- Gemini 3.6 Flash: 38.5 (#64)
- GLM-4.7: —

| Benchmark | Gemini 3.6 Flash | GLM-4.7 |
|---|---|---|
| LMArena Vision | 1298 | — |
| Blueprint-Bench 2 | 31.2% | — |
| Furniture Assembly | 23.3% | — |
| LMArena Document | 1456 | — |

## Multilingual

- Gemini 3.6 Flash: 56.5 (#19)
- GLM-4.7: 52.8 (#79)

| Benchmark | Gemini 3.6 Flash | GLM-4.7 |
|---|---|---|
| LMArena Non-English | 1469 | 1417 |
| LMArena Chinese | 1531 | 1495 |
| LMArena French | 1504 | 1432 |
| LMArena German | 1478 | 1424 |
| LMArena Japanese | 1476 | 1439 |
| LMArena Korean | 1431 | 1399 |
| LMArena Russian | 1487 | 1423 |
| LMArena Spanish | 1475 | 1434 |

## Instruction Following

- Gemini 3.6 Flash: 77.0 (#33)
- GLM-4.7: 74.4 (#95)

| Benchmark | Gemini 3.6 Flash | GLM-4.7 |
|---|---|---|
| LMArena Instruction Following | 1466 | 1411 |

## Long Context

- Gemini 3.6 Flash: 45.1 (#50)
- GLM-4.7: 42.8 (#116)

| Benchmark | Gemini 3.6 Flash | GLM-4.7 |
|---|---|---|
| LMArena Longer Query | 1474 | 1432 |
| CL-bench | — | 15.9% |
| CL-bench Life | — | 10.9% |

## Writing & Preference

- Gemini 3.6 Flash: 68.2 (#27)
- GLM-4.7: 60.9 (#93)

| Benchmark | Gemini 3.6 Flash | GLM-4.7 |
|---|---|---|
| LMArena Text | 1479 | 1435 |
| LMArena Creative Writing | 1465 | 1401 |
| EQ-Bench Creative Writing | 1604 | 1413 |
| LMArena Multi-Turn | 1481 | 1446 |

## FAQ

### Is Gemini 3.6 Flash better than GLM-4.7?

Gemini 3.6 Flash is the stronger model overall, scoring 54.1 to 42.0 on the Noometry Index. GLM-4.7 costs 1.5× less per token, which makes it the better buy when Gemini 3.6 Flash's lead doesn't matter for your workload.

### Which is cheaper, Gemini 3.6 Flash or GLM-4.7?

GLM-4.7 is cheaper. It lists at $0.60 per million input tokens and $2.20 per million output tokens; Gemini 3.6 Flash lists at $0.75 and $3.75.

### Is Gemini 3.6 Flash or GLM-4.7 better for coding?

Gemini 3.6 Flash scores higher on coding benchmarks: 50.0 versus 44.0 in the Noometry coding category.

### Which has the bigger context window?

Gemini 3.6 Flash does, with 1.05M tokens against 205K.

### How many benchmarks do Gemini 3.6 Flash and GLM-4.7 share?

28 benchmarks have published results for both models. Gemini 3.6 Flash has 46 scored results on Noometry and GLM-4.7 has 36.