# GLM-4.6 vs MiniMax-M2

> GLM-4.6 is the stronger model overall, scoring 41.4 to 37.4 on the Noometry Index. MiniMax-M2 costs 1.9× less per token, which makes it the better buy when GLM-4.6's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/glm-4-6-vs-minimax-m2
- Last updated: 2026-10-11
- Shared benchmarks: 19

## Summary

- They share 19 benchmarks with published results for both. GLM-4.6 scores higher in 9 categories and MiniMax-M2 in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in multilingual, where GLM-4.6 leads 53.5 to 45.3.
- The biggest single-benchmark swing is Kagi LLM Benchmark: 47.4% for GLM-4.6 and 57.8% for MiniMax-M2.
- MiniMax-M2 is cheaper at $0.30 / $1.20 per million input/output tokens, against $0.60 / $2.20 for GLM-4.6.

## Snapshot

| | GLM-4.6 | MiniMax-M2 |
|---|---|---|
| Provider | Z.ai (Zhipu) | MiniMax |
| Noometry Index | 41.4 | 37.4 |
| Rank | 135 | 204 |
| Context | 205K | 205K |
| Input $/M | $0.60 | $0.30 |
| Output $/M | $2.20 | $1.20 |
| Weights | Open | Open |

## Coding

- GLM-4.6: 40.1 (#148)
- MiniMax-M2: 39.3 (#159)

| Benchmark | GLM-4.6 | MiniMax-M2 |
|---|---|---|
| SWE-bench Verified (bash only) | 55.4% | 61% |
| LMArena WebDev | 1340 | 1297 |
| LMArena Coding | 1449 | 1370 |
| SciCode | 38.4% | — |
| ALE-Bench | 340.82 | — |

## Agentic & Tool Use

- GLM-4.6: 32.3 (#66)
- MiniMax-M2: 25.1 (#109)

| Benchmark | GLM-4.6 | MiniMax-M2 |
|---|---|---|
| Terminal-Bench | 24.5% | 30% |
| Berkeley Function Calling Leaderboard | 72.4% | — |
| Vending-Bench 2 | — | 160.6 |

## Reasoning

- GLM-4.6: 23.7 (#172)
- MiniMax-M2: 19.4 (#258)

| Benchmark | GLM-4.6 | MiniMax-M2 |
|---|---|---|
| Kagi LLM Benchmark | 47.4% | 57.8% |
| LMArena Hard Prompts | 1440 | 1357 |
| NYT Connections (extended) | — | 14.8% |
| CritPt | 1.1% | — |

## Math

- GLM-4.6: 39.1 (#111)
- MiniMax-M2: 37.3 (#160)

| Benchmark | GLM-4.6 | MiniMax-M2 |
|---|---|---|
| LMArena Math | 1432 | 1352 |
| FrontierMath (Feb 2025 set) | 3.8% | — |
| FrontierMath Tier 4 (v1) | 2.1% | — |

## Knowledge

- GLM-4.6: 40.2 (#124)
- MiniMax-M2: 37.0 (#163)

| Benchmark | GLM-4.6 | MiniMax-M2 |
|---|---|---|
| LMArena Expert | 1431 | 1337 |
| Vectara Hallucination Rate | 9.5% | — |

## Multilingual

- GLM-4.6: 53.5 (#66)
- MiniMax-M2: 45.3 (#171)

| Benchmark | GLM-4.6 | MiniMax-M2 |
|---|---|---|
| LMArena Non-English | 1426 | 1313 |
| LMArena Chinese | 1499 | 1366 |
| LMArena French | 1459 | 1335 |
| LMArena German | 1447 | 1355 |
| LMArena Russian | 1419 | 1331 |
| LMArena Spanish | 1436 | 1326 |
| LMArena Japanese | 1393 | — |
| LMArena Korean | 1400 | — |

## Instruction Following

- GLM-4.6: 74.3 (#98)
- MiniMax-M2: 70.2 (#166)

| Benchmark | GLM-4.6 | MiniMax-M2 |
|---|---|---|
| LMArena Instruction Following | 1410 | 1328 |

## Long Context

- GLM-4.6: 43.4 (#94)
- MiniMax-M2: 40.5 (#153)

| Benchmark | GLM-4.6 | MiniMax-M2 |
|---|---|---|
| LMArena Longer Query | 1422 | 1331 |

## Writing & Preference

- GLM-4.6: 61.1 (#90)
- MiniMax-M2: 53.0 (#162)

| Benchmark | GLM-4.6 | MiniMax-M2 |
|---|---|---|
| LMArena Text | 1440 | 1340 |
| LMArena Creative Writing | 1411 | 1286 |
| LMArena Multi-Turn | 1427 | 1361 |
| EQ-Bench Creative Writing | 1411 | — |

## FAQ

### Is GLM-4.6 better than MiniMax-M2?

GLM-4.6 is the stronger model overall, scoring 41.4 to 37.4 on the Noometry Index. MiniMax-M2 costs 1.9× less per token, which makes it the better buy when GLM-4.6's lead doesn't matter for your workload.

### Which is cheaper, GLM-4.6 or MiniMax-M2?

MiniMax-M2 is cheaper. It lists at $0.30 per million input tokens and $1.20 per million output tokens; GLM-4.6 lists at $0.60 and $2.20.

### Is GLM-4.6 or MiniMax-M2 better for coding?

They score almost the same on coding (40.1 vs 39.3); test both on your own repository before choosing.

### Which has the bigger context window?

Both accept 205K tokens.

### How many benchmarks do GLM-4.6 and MiniMax-M2 share?

19 benchmarks have published results for both models. GLM-4.6 has 29 scored results on Noometry and MiniMax-M2 has 21.