API cost decision in 10 seconds
GLM 4.6V vs MiniMax M2
Pick GLM 4.6V for lower cost; pick MiniMax M2 only if the larger context window matters more.
Pricing data updated:
Prices normalized to USD per 1M tokens
Sample workload: 1M input + 500K output
Budget verdict
Pick GLM 4.6V for lower cost; pick MiniMax M2 only if the larger context window matters more.
On the standard 1M input plus 500K output workload, GLM 4.6V is estimated at $0.75 vs $0.76 for MiniMax M2, saving $0.005 (0.7% lower).
Cost-first pickGLM 4.6V
Context-first pickMiniMax M2
Sample savings$0.0050.7%
10x traffic gap$0.05
MiniMax M2 has more context, but GLM 4.6V saves $0.005 on the standard workload. At 10x that traffic, the same price gap is about $0.05. Use the calculator below to replace the sample workload with your own token volume.
Cost sensitivity
Workload Sensitivity
Cost winner changes by workload shape: input-heavy / RAG favors MiniMax M2, balanced workload favors GLM 4.6V, and output-heavy chatbot favors GLM 4.6V.
| Workload shape | Token mix | Better pick | GLM 4.6V | MiniMax M2 |
|---|---|---|---|---|
| Input-heavy / RAG | 5M input + 500K output | MiniMax M2 | $1.95 | $1.77 |
| Balanced workload | 1M input + 1M output | GLM 4.6V | $1.2 | $1.25 |
| Output-heavy chatbot | 1M input + 5M output | GLM 4.6V | $4.8 | $5.25 |
Estimate your workload cost
Your Workload Cost
This estimate uses normalized public API pricing per 1M tokens. It is a planning aid, not a billing quote. Verify provider pricing, limits, and terms before production use.
Quick Decision
MiniMax M2 has the lower input price, GLM 4.6V has the lower output price, and MiniMax M2 offers the larger context window.
For a 1M input token plus 500K output token workload, the estimated API cost is $0.75 for GLM 4.6V and $0.76 for MiniMax M2.
Choose GLM 4.6V when you care most about lower output-token price.
Choose MiniMax M2 when you care most about lower input-token price, and larger context window.
| Feature | GLM 4.6V (Z.ai) | MiniMax M2 (MiniMax) |
|---|---|---|
| Input Price prompt tokens per 1M | $0.3 | $0.26 |
| Completion Price per 1M tokens | $0.9 | $1 |
| Sample Workload Cost 1M input + 500K output | $0.75 | $0.76 |
| Context Window | 131.07K | 204.8K |
| Release Date | 2025-12-08 | 2025-10-23 |
GLM-4.6V is a large multimodal model designed for high-fidelity visual understanding and long-context reasoning across images, documents, and mixed media. It supports up to 128K tokens, processes complex page layouts...
MiniMax-M2 is a compact, high-efficiency large language model optimized for end-to-end coding and agentic workflows. With 10 billion activated parameters (230 billion total), it delivers near-frontier intelligence across general reasoning,...
Use-Case Decision Matrix
| Use case | Better pick | Why |
|---|---|---|
| Budget-constrained production | GLM 4.6V | On the standard 1M input plus 500K output workload, GLM 4.6V is estimated at $0.75 vs $0.76 for MiniMax M2, saving $0.005 (0.7% lower). |
| High-volume input processing | MiniMax M2 | Lower prompt-token price matters most when prompts or retrieved passages dominate the bill. |
| Long responses and chatbots | GLM 4.6V | Lower output-token price matters most when assistants generate many completion tokens. |
| RAG or long-document work | MiniMax M2 | A larger context window leaves more room for retrieved passages and source files. |