RTX Pro 6000
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Apr. 16, 2026 / Hardware Insights
What hardware you need for MiniMax-M2.7 230B (A10B) in 4-bit
Running MiniMax-M2.7 230B locally requires extreme VRAM, even with 4-bit quantization, and a dual high-end GPU setup is the practical baseline today. This article shows real VRAM usage and performance from a dual RTX Pro 6000 Blackwell system using MXFP4 quantization, with a focus on hardware limits and inference speed. Test setup and model details...
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Apr. 3, 2026 / Featured
What Hardware for Gemma 4 26B and 31B LLM Local Use
The new Gemma 4 models from Google DeepMind have landed, and for local LLM users this is one of the more practical releases in a while. The lineup gives us two interesting mid-size targets: a 26B MoE model (A4B) and a 31B dense model. Both support up to 256K context, tool calling, and personal agent-style...
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Feb. 26, 2026 / Hardware Insights
Qwen3.5 27B and Qwen3.5 35B: What Hardware Do You Actually Need? (GPU Benchmarks Inside)
Qwen3.5 27B fits comfortably on a 24 GB GPU up to 131k context in 4-bit, but becomes memory heavy at 262k. Qwen3.5 35B MoE in 4-bit is the more practical long-context model for 24 GB cards, and it is significantly faster in token generation despite having more total parameters. VRAM is still the main constraint,...
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Feb. 4, 2026 / Hardware Insights
Qwen3 Coder Next 80B A3B: what it takes to run it locally
Direct answer first: Qwen3 Coder Next 80B A3B is one of the most hardware-friendly 80B-class coding models released so far. Thanks to its MoE design with roughly 3B active parameters, a single high-VRAM GPU can run it at full 256k context, and even dual consumer GPUs can handle the 3-bit version comfortably. VRAM, not raw...
