MiniMax M3
MiniMax M3 publishes its weights, but at 428B parameters (23B active per token) no consumer machine holds the checkpoint. This page covers the access paths that work and the open models that actually run locally.
Why you can't run MiniMax M3 locally
At 428B parameters (23B active per token), a Q4-class build of MiniMax M3 would need roughly 257 GB — only a maxed-out 512GB Mac Studio could even hold the weights, with no real headroom. That figure is arithmetic, not opinion: 0.6 GB per billion parameters is the standard Q4 rule we apply across the whole catalog. The weights themselves are public (official source linked below); capacity, not licensing, is the wall.
What works instead: the hosted API. For most workloads, the open models below deliver the same job on hardware that fits under a desk.
Jun 1, 2026 MiniMax release. Native-multimodal MoE (~428B total / ~23B active) with 1M context via MiniMax Sparse Attention. SWE-Bench Pro 59.0%, Terminal-Bench 2.1 66.0%. Open weights; cloud/API for nearly all users.
What to run locally instead of MiniMax M3
Frequently asked questions
Can I run MiniMax M3 locally?
Not on hardware you can buy. The weights are public, but MiniMax M3 is a 428B-parameter model (23B active), and a Q4-class build would need roughly 257 GB — only a maxed-out 512GB Mac Studio could even hold the weights, with no real headroom. Until the ecosystem ships a smaller official build, the API or a smaller open model is the practical path.
How do I access MiniMax M3?
Through the vendor's hosted API. The official source is linked on this page.
What is the best local alternative to MiniMax M3?
Qwen3 235B A22B is the strongest local model we track (235B, from 192 GB machines), with Qwen3.5 122B-A10B Instruct close behind. Both run on a single high-memory Mac or GPU — see their pages for exact hardware.
Cite this page
ModelFit: MiniMax M3 — specs, memory math and hardware verdicts. https://modelfit.io/models/minimax-m3/ (dataset updated 2026-09-03, CC BY 4.0).