Best Local Vision Models by VRAM (October 2026)
Open-weight vision-language models sized by VRAM: Qwen3-VL 2B to 235B-A22B, Mistral Small 3.2, Gemma 3, Pixtral, and where each tier breaks.
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#ollama
Best Local LLM for Spreadsheet Analysis on a Laptop
Practical tier guide to running a local LLM on Excel, CSV, and tabular data. Picks by RAM, JSON output for clean rows, and what to skip.
Self-Host a Private AI Home Server: A Primer (October 2026)
How to pick the hardware, OS, and runtime for a 24/7 local AI server, from a low-power mini PC to a used 3090 workstation, and what each costs to run.
Best Local AI for Creative Writing: Private Drafts
Run an LLM against your novel without sending an unpublished manuscript to a vendor. Models, front ends, and what the tradeoffs are.
What's New in Ollama 0.40, and Should You Upgrade?
v0.40.0-rc0 ships MLX-by-default on Apple Silicon, v0.35 adds decision models, transformers runs llama.cpp quants. What changed and how to upgrade.
Best Local AI for Email: Triage, Draft, Reply Privately
Run an AI assistant against your inbox without sending mail to Google, Microsoft, or any third party. RAG setup and tradeoffs.
Decision Models: Ollama and OpenAI Ship Jev APIs in 24 Hours
Ollama 0.35 adds Jev-style decision models locally the same day OpenAI previews its Decisions API for Luna. Same primitive, two stacks.
Best Local LLM for Long-Document Q&A: How to Chat with a Book
Which local LLM should you use to ask questions about a 500-page PDF without uploading it? A practical guide by context window and hardware tier.
MoE vs Dense Models for Local AI (September 2026)
What the 'A3B' and 'A22B' suffixes mean, when Mixture-of-Experts beats a dense model on your hardware, and how to read a model card to tell which is which.
Best Local Models by Context Window (October 2026)
Local LLMs ranked by maximum context length: 32K, 128K, 256K, and 1M+ tiers, with the model that fits each tier and the VRAM each one needs.
Best Local LLM for Everyday Tasks (Chat, Writing, Summarizing)
Which open-weight LLM should you actually run for everyday chat, writing, and summarizing? A tier-by-tier guide from 8 GB laptops to 32 GB desktops.
Best Local Coding Models by VRAM (September 2026)
Open-weight coding LLMs sized by VRAM: Qwen2.5-Coder, Qwen3-Coder, Devstral Small 2, KAT-Coder, GLM-4.7-Flash, and the trade-offs at each tier.
What Thinking Mode Actually Costs You (September 2026)
Reasoning tokens, latency, and KV cache cost of thinking mode in local LLMs. How to toggle it per runner and when it is the wrong choice.
How to Safely Download and Verify Open-Source LLMs
Sourced steps to safely download and verify an open-source LLM: safetensors, GPG-signed commits, pinned revisions, and HF / Ollama integrity checks.
Local LLM Backends Compared: Ollama, LM Studio, llama.cpp, vLLM
How Ollama, LM Studio, llama.cpp, and vLLM differ on model format, OpenAI-compatible API, hardware support, and which to pick for a home server.
Serve a Local Model to Your Team (September 2026)
Auth, reverse proxy, HTTPS, concurrency and audit: how a small team shares one local model without exposing it to the public internet.
Best Local Reasoning Models by VRAM (October 2026)
Reasoning-capable open-weight models sized by VRAM. DeepSeek-R1, Qwen3 with thinking, QwQ, Phi-4 reasoning, gpt-oss, and the licence traps.
Local AI When One GPU Isn't Enough (September 2026)
Multi-GPU options for self-hosted AI when one card runs out of room: how Ollama, llama.cpp and vLLM split models, and what the interconnects actually cost.
Run an LLM Locally on a Raspberry Pi (October 2026)
Raspberry Pi 4 and Pi 5 can run small open-weight models on CPU alone. What fits on 2 GB, 4 GB, 8 GB, or 16 GB of RAM, and what speed is realistic.
Ollama's New Pricing: What the Credit-Pool Change Actually Means
Ollama swapped GPU-hour billing for per-token credits across Pro, Max and Team plans. What the tiers cost, what's free, and how the no-logging promise holds up.
Best Used GPUs for Local AI in 2026 (September 2026)
The RTX 30 and 40 series cards that still clear current Ollama and llama.cpp floors, what VRAM tier each opens, and which variants are worth the used premium.
Serve a Local Model to Your Household (August 2026)
Practical patterns for letting two to six people in one home share one local model on one machine, with the right chat UI, bind address, and overlay network.
Local AI on AMD and Intel GPUs (September 2026)
What works on AMD Radeon and Intel Arc hardware today, where the official ROCm and SYCL paths stop, and how Vulkan fills the gap.
Serving a Local Model to Your Household Without Exposing It
None of the mainstream inference servers ask for a password, and vLLM binds every interface by default. The safe pattern for household serving.