GLM-4.6 Instruct vs MiniMax-M2 Instruct: which model should you choose?
We compared GLM-4.6 Instruct and MiniMax-M2 Instruct on price, context window and 12 benchmarks. GLM-4.6 Instruct has the stronger average benchmark score; GLM-4.6 Instruct is cheaper on a blended 3:1 basis.
GLM-4.6 Instruct
GLM-4.6 Instruct is a multimodal model from Zhipu AI. It offers a 1,000,000-token context window, costs $5.15 per million input tokens and $24.32 per million output tokens, and averages 80.4 across the index's benchmark suite.
- Input
- $5.15 / 1M
- Output
- $24.32 / 1M
- Context
- 1,000,000
- Avg score
- 80.4
- Open weights
- Yes
MiniMax-M2 Instruct
MiniMax-M2 Instruct is a multimodal model from MiniMax. It offers a 128,000-token context window, costs $5.11 per million input tokens and $25.04 per million output tokens, and averages 79.4 across the index's benchmark suite.
- Input
- $5.11 / 1M
- Output
- $25.04 / 1M
- Context
- 128,000
- Avg score
- 79.4
- Open weights
- Yes
Specification comparison
| Spec | GLM-4.6 Instruct | MiniMax-M2 Instruct | Edge |
|---|---|---|---|
| Input price / 1M | $5.15 | $5.11 | B |
| Output price / 1M | $24.32 | $25.04 | A |
| Context window | 1,000,000 | 128,000 | A |
| Max output | 128,000 | 4,096 | A |
| Average score | 80.4 | 79.4 | A |
| Arena Elo | 1426.6 | 1442.2 | B |
| Open weights | Yes | Yes | Tie |
Benchmark comparison
GLM-4.6 Instruct wins 8, MiniMax-M2 Instruct wins 4, and 0 benchmarks are tied. The table shows the modelled score for each model and the gap.
| Benchmark | GLM-4.6 Instruct | MiniMax-M2 Instruct | Gap | Winner |
|---|---|---|---|---|
| MMLU-Pro | 80.6 | 82.1 | 1.5 | MiniMax-M2 Instruct |
| GPQA Diamond | 75.8 | 73.7 | 2.1 | GLM-4.6 Instruct |
| SWE-bench Verified | 70.5 | 69.9 | 0.6 | GLM-4.6 Instruct |
| HumanEval | 85.3 | 86.7 | 1.4 | MiniMax-M2 Instruct |
| MATH-500 | 84.9 | 82.1 | 2.8 | GLM-4.6 Instruct |
| AIME 2025 | 74.5 | 77.8 | 3.3 | MiniMax-M2 Instruct |
| LiveCodeBench | 72.6 | 71.1 | 1.5 | GLM-4.6 Instruct |
| IFEval | 87.4 | 87.3 | 0.1 | GLM-4.6 Instruct |
| TruthfulQA | 83.8 | 80.0 | 3.8 | GLM-4.6 Instruct |
| HellaSwag | 90.6 | 88.5 | 2.1 | GLM-4.6 Instruct |
| MMMU | 78.9 | 74.1 | 4.8 | GLM-4.6 Instruct |
| Arena Elo | 1426.6 | 1442.2 | 15.6 | MiniMax-M2 Instruct |
Price analysis
On a blended 3:1 input-to-output basis, GLM-4.6 Instruct costs about $9.94 per million tokens and MiniMax-M2 Instruct costs about $10.09. GLM-4.6 Instruct is roughly 1% cheaper than MiniMax-M2 Instruct. At high volume, that gap compounds quickly, so price should carry real weight unless the quality difference is decisive.
GLM-4.6 Instruct has the larger context window at 1,000,000 tokens, compared with 128,000 for MiniMax-M2 Instruct. That matters for long documents, large codebases and multi-step agent traces.
Verdict
Across 12 shared benchmarks, GLM-4.6 Instruct wins 8, MiniMax-M2 Instruct wins 4, and 0 are tied. On the index average, GLM-4.6 Instruct leads MiniMax-M2 Instruct by 1.0 points (80.4 versus 79.4).
The price picture favours GLM-4.6 Instruct. The context picture favours GLM-4.6 Instruct. Those two dimensions often matter more than a few benchmark points once a model is good enough for the task.
If you need a single default, start with GLM-4.6 Instruct for quality-sensitive work, and check whether its price holds at your expected volume before committing.
Choose GLM-4.6 Instruct if
- You want the higher average benchmark score in this index.
- Unit cost matters and you want the cheaper blended price.
- You need the larger 1,000,000-token context window.
- You need the larger 128,000-token output limit.
Choose MiniMax-M2 Instruct if
- You prefer MiniMax's tooling or already use it.
FAQ
Is GLM-4.6 Instruct better than MiniMax-M2 Instruct?
On the index average, GLM-4.6 Instruct leads MiniMax-M2 Instruct by 1.0 points (80.4 versus 79.4). The better choice depends on price, context and your task. GLM-4.6 Instruct wins 8 benchmarks, MiniMax-M2 Instruct wins 4.
Which is cheaper, GLM-4.6 Instruct or MiniMax-M2 Instruct?
GLM-4.6 Instruct is cheaper on a blended 3:1 basis at about $9.94 per million tokens, versus $10.09 for MiniMax-M2 Instruct.
Which has the larger context window?
GLM-4.6 Instruct has the larger context window at 1,000,000 tokens. MiniMax-M2 Instruct has 128,000 tokens.
Are these models open weights?
GLM-4.6 Instruct is open weights; MiniMax-M2 Instruct is open weights.
Which should I choose for production?
If you need a single default, start with GLM-4.6 Instruct for quality-sensitive work, and check whether its price holds at your expected volume before committing.