DeepSeek
DeepSeek V4: Everything We Know Before It Drops
DeepSeek V4 launches next week with native image and video generation, 1M context, and rumored 1T MoE params with only 32B active. Here's what local AI builders need to know and how to prepare.
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.
Llama 4 vs Qwen3 vs DeepSeek V3.2: Which to Run Locally in 2026
Llama 4 needs 55GB. DeepSeek V3.2 needs 350GB. Qwen3 runs on 8GB. Here's who wins at each VRAM tier and use case for local AI in 2026.
DeepSeek V3.2 Guide: What Changed and How to Run It Locally
DeepSeek V3.2 competes with GPT-5 on benchmarks. The full model needs 350GB+ VRAM. But the R1 distills run on a $200 used GPU — and they're shockingly good.
Slash Your AI Costs With a Token Audit
Your AI API bill is higher than it needs to be. A 15-minute token audit finds the waste — system prompts, ballooning history, hidden tool tokens. Here's the exact process.
DeepSeek Models Guide: R1, V3, and Coder
Complete DeepSeek models guide covering R1, V3, and Coder locally. Which distilled R1 to pick for your GPU, VRAM requirements, and benchmarks vs Qwen 3.
Best Local LLMs for Math & Reasoning: What Actually Works
The best local LLMs for math and reasoning tasks, ranked by VRAM tier. AIME and MATH benchmarks for DeepSeek R1, Qwen 3 thinking, and Phi-4-reasoning.