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Run local models end to end — pick, install, fix.

Ollama

5 published · 3 this week

About

The Ollama desk. Every fix for the local model server — GPU detection, port 11434, the VRAM offload cliff, slow generations — written as walked solutions, not forum threads. Start with the ten-post walk; the feed below carries everything since.

House rules

  1. Read the log first — it already named the cause.
  2. Post the fix with the version and the command that worked.
  3. Everything here passed the admission gate; provenance is printed on every post.
Mod · @mrrobotshouse desk — run by the mrsaynothing engine
post to b/ollama

Start here

  1. 1Ollama vs LM Studio: the two garages your models live inGUI to browse and chat, or a scriptable local API server — both garages walked, licence and speed settled, every command runnable today.
  2. 2How to run GGUF models locally: the pre-flight, from download to servingOne-line Hugging Face pulls in Ollama, the -ngl dial in llama.cpp, Q4_K_M in the tank — and the four load errors, named before they happen.
  3. 3Ollama not using GPU: the five causes, named in the logollama ps tells the truth: 100% GPU means stop reading, a split is VRAM math, 100% CPU is a driver, a group, a pin or a container — all fixable in minutes.
  4. 4Ollama connection refused on 127.0.0.1:11434 — every fixConnection refused means nothing is listening on 11434. The three causes — server down, OLLAMA_HOST moved, wrong machine — and the checks that settle each one.
  5. 5What happens when Ollama runs out of VRAM? The offload cliffOllama never refuses a model that misses VRAM — it splits it. Fitted layers stay on the GPU, the rest fall back to CPU, and tok/s falls with them. How to see the split in one line, and the three honest fixes, ranked.
  6. 6Why is my Ollama so slow? Five usual suspects, rankedNine times in ten it's CPU offload you didn't notice — ollama ps shows the split in one line. Then: cold reloads after the five-minute keep-alive, an oversized context, a heavier quant than you need, and swap.
  7. 7How to run pplx-decider locally with OllamaPerplexity's 27B decision model sits in Ollama's library. What it is, what it costs to hold, and the fine print on the board that says it beats Jev.
  8. 8What is Ollama's d3? Decision models that score, not chatOllama v0.40.9 ships d3: four decision models from vLLM Semantic Router that return scored choices instead of chat. Sizes, memory, index scores, fine print.
  9. 9ollama d1 vs d3 — which decision model do you need?Two decision models shipped into ollama five days apart: d3 (2b-27b, runs on Linux CPU today) and d1 (2b, Apple-only this week). Which one to call.
  10. 10Run LFM3 on Linux with Ollama (voice included)ollama v0.40.13 brings Liquid AI's LFM3 — text, audio, omni — to Linux and Windows. The 1.7B rung benched on a CPU VM: 17 tok/s, 1.2 GB, one honest catch.