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How to Compare Local AI Models Side by Side on Linux in 2026 (One Question, Up to Six Models)

This story is from 2026-10-29. It is preserved in the archive; the latest stories are on the live feed.

You run Ollama, LM Studio or a llama.cpp server on your Linux box, you have pulled a handful of models, and you want to know which one writes the best answer for your own prompts. Off Grid AI Desktop splits its chat into two to six panes. Each pane runs on its own model, one question goes to all of…

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  1. 2026-10-29 09:51 · DEV Community — AI
    How to Compare Local AI Models Side by Side on Linux in 2026 (One Question, Up to Six Models)

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  1. I tested LFM2.5-24B-A2B vs Qwen3.6-35B-A3B on 75 fresh multi-step tool tasks. Qwen solved 91%, LFM2.5 49%, and LFM2.5 said "done" on most of its failures — r/LocalLLM
  2. Basalt (NVFP4) vs Unsloth Studio (llama.cpp IQ4_XS) — 5090 with 64GB RAM — r/LocalLLM
  3. Gemma 3 1B on the Nexus 5X (Directly on the Linux Kernel, No Android) — 2 GB RAM, 4.47 t/s — r/LocalLLM
  4. Nanbeige4.3-33B Q4 on a MacBook Pro M5 Max, mlx-lm vs llama.cpp vs Kapitsa, Prefill/Decode 512 to 32K range. — r/LocalLLaMA
  5. A 2013 Mac Pro runs a 35B model at 66 tok/s reading. The first benchmark I trusted was wrong by about 9x. — r/LocalLLM
  6. mtmd: enable video input support for LFM3 model family by tdakhran · Pull Request #31283 · ggml-org/llama.cpp — r/LocalLLaMA
  7. shura.cpp: a llama.cpp fork with a VRAM governor, so a 35B MoE can share one 16 GB card with the desktop you keep using — r/LocalLLM
  8. LiquidAI/LFM3-Omni-2B-GGUF — r/LocalLLaMA

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