Mixtral
MoE Models Explained: Why Mixtral Uses 46B Parameters But Runs Like 13B
Mixture of Experts explained for local AI — why MoE models run fast but still need full VRAM. Mixtral, DeepSeek V3, DBRX compared with dense model alternatives.
Mixtral VRAM Requirements: 8x7B and 8x22B at Every Quantization Level
Mixtral 8x7B has 46.7B params but only 12.9B activate per token. You still need VRAM for all 46.7B. Exact VRAM for every quant from Q2 to FP16.
Mixtral 8x7B & 8x22B VRAM Requirements
Mixtral 8x7B and 8x22B VRAM requirements at every quantization level. Exact numbers from Q2 to FP16, GPU recommendations, and KV cache impact explained.
Are Mistral Models Still Worth Running? Only Nemo 12B (Here's Why)
Mistral Medium 3.5-128B dropped April 29, 2026: dense 128B, 256k context, Modified MIT. Hardware reality, license caveats, which Mistral to actually run.