Smaller alternatives
Models that need less memory than MiniMax M2.7 and score about as well or better.
MiniMax M2.7
MoE
MiniMax · 228.7B (10B active) · Mixture of experts
MiniMax M2.7 is a 228.7B model from MiniMax with a 200K-token context. At Q4_K_M with an 8K context it needs about 131.5 GB; 166 GB leaves room for longer chats.
Mixture of experts
Parameters: 228.7B · Active: 10B
All 228.7B parameters load into memory, but only 10B work on each token, so it runs at the speed of a much smaller model.
Quantization options
| Quant | Bits | Memory | Quality | On your hardware |
|---|---|---|---|---|
| Q2_K | 3.16 | — | Noticeably worse | … |
| Q3_K_M | 4 | — | Some loss | … |
| Q4_K_M | 4.89 | — | Good | … |
| Q5_K_M | 5.7 | — | Good | … |
| Q6_K | 6.56 | — | Near original | … |
| Q8_0 | 8.5 | — | Near original | … |
| F16 | 16 | — | Original | … |
Memory by context length
At Q4_K_M. The context cache grows with every token the model keeps in mind.
| Context | Context cache | Total |
|---|---|---|
| 4K | 1 GB | 130.5 GB |
| 8K | 1.9 GB | 131.5 GB |
| 32K | 7.8 GB | 137.3 GB |
| 128K | 31 GB | 160.6 GB |
Next steps
Compare it with
Scored models of a similar size, side by side on your device.
Least hardware that runs it well
Desktop devices with the least memory that give MiniMax M2.7 grade A or S at Q4_K_M.
Can I run MiniMax M2.7 locally?
Can I run MiniMax M2.7 locally?
Yes, if your GPU or Mac has about 131.5 GB free for it at Q4_K_M. Open this page on that computer to see the grade for your exact hardware, then start it with llama.cpp, Ollama or LM Studio.
How much memory does MiniMax M2.7 need?
About 131.5 GB at Q4_K_M with an 8K context and 228.7 GB at Q8_0. Lower quantizations fit smaller cards with some loss in quality; longer contexts add to the total.