AI model comparison
MiniMax M2 vs GLM 4.6
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
MiniMax
MiniMax M2
MiniMax-M2 is a compact, high-efficiency large language model optimized for end-to-end coding and agentic workflows.
- Input / 1M
- $0.30
- Output / 1M
- $1.20
- Context
- 205K
Z.ai
GLM 4.6
Compared with GLM-4.5, this generation brings several key improvements: Longer context window: The context window has been expanded from 128K to 200K tokens, enabling the model to handle more complex
- Input / 1M
- $0.43
- Output / 1M
- $1.75
- Context
- 205K
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
MiniMax M2
1.4x cheaper for a typical chat
Higher intelligence score
MiniMax M2
18.6 vs 18.5 on Artificial Analysis
Larger context window
Tie
205K vs 205K tokens
Newer release
MiniMax M2
Released October 23, 2025
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Coding index
Agentic index
Pricing
MiniMax M2 vs GLM 4.6 API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | ||
|---|---|---|
| Input tokensPer 1M tokens | $0.30 | $0.43 |
| Output tokensPer 1M tokens | $1.20 | $1.75 |
| Cached input (read)Per 1M tokens | Not available | $0.08 |
| Cache writePer 1M tokens | Not available | Not available |
What it costs in practice
Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.
Chat message
2K in, 500 out
Coding task
30K in, 4K out
Long document summary
150K in, 2K out
Specs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | ||
|---|---|---|
| Context window | 205K tokens | 205K tokens |
| Max output | 177K tokens | 16K tokens |
| Input types | Text | Text |
| Output types | Text | Text |
| Reasoning effort levels | Not available | Not available |
| Default reasoning effort | Not available | Not available |
| Release date | October 23, 2025 | September 30, 2025 |
Features
Supported features
API features available for each model.
| Metric | ||
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Supported | Supported |
| JSON mode | Supported | Supported |
| Reasoning | Supported | Supported |
| Temperature | Supported | Supported |
| Stop sequences | Supported | Supported |
| Deterministic seed | Supported | Supported |
| Verbosity control | Not supported | Not supported |
Keep exploring
More on these models
Other head-to-heads, the full model page, and the alternatives list for each model.
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- GLM 4.6 vs Gemini 3.1 Flash Lite
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- GLM 4.6 vs GLM 4.7
- GLM 4.6 vs Claude Haiku 4.5
- GLM 4.6 vs GPT-5 Mini
- GLM 4.6 vs GPT-5.1-Codex-Mini
- GLM 4.6 vs GLM 5.3 FlashX
- GLM 4.6 vs Step 3.7 Flash
- GLM 4.6 vs LongCat 2.0
- GLM 4.6 vs Qwen3.6 35B A3B
- GLM 4.6 vs Qwen3.5-122B-A10B
- GLM 4.6 vs Muse Glimmer 30B
Our take
MiniMax M2 is 1.4x cheaper for a typical chat. MiniMax M2 scores higher on the Artificial Analysis Intelligence Index (18.6 vs 18.5). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.
FAQ
Frequently asked questions
Is MiniMax M2 or GLM 4.6 cheaper?
MiniMax M2 is cheaper for a typical chat (2K input tokens and 500 output tokens). MiniMax M2 costs $0.30 per 1M input tokens and $1.20 per 1M output tokens, while GLM 4.6 costs $0.43 per 1M input tokens and $1.75 per 1M output tokens.
Which has a bigger context window, MiniMax M2 or GLM 4.6?
MiniMax M2 supports up to 205K tokens of context, compared with 205K for GLM 4.6.
Is MiniMax M2 smarter than GLM 4.6?
On the Artificial Analysis Intelligence Index, MiniMax M2 scores 18.6 and GLM 4.6 scores 18.5, putting MiniMax M2 ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use MiniMax M2 and GLM 4.6 at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see MiniMax M2 and GLM 4.6 answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to MiniMax M2 and GLM 4.6 at the same time. Compare the answers side by side and keep the best one.