Best Local LLM for Cover Letters and Resumes
Practical tier guide to running a local LLM for cover letters, resumes, and CV drafts. Picks by RAM, instruction following, and what to keep offline.
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#gemma
Best Local LLM for Multilingual Use (October 2026)
Which open-weight model actually handles non-English work, what each provider claims about language coverage, and the tradeoffs between breadth and depth.
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.
Best Local Models by Context Window (September 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.
How to Choose an Open-Weight Model Family (September 2026)
Qwen, Llama, Mistral, Gemma, DeepSeek, Phi - which family to commit to, what each is good at, and the licence traps that send you back to negotiate.
Open-Weight LLM Showdown Week 16: Kimi K2.6 Storms the Rankings, Qwen 3.6 Holds the Line, and Consumer GPUs Hit a Ceiling
Three weeks away and the leaderboard reshuffled. Kimi K2.6 brings 1T parameters under open weights, Qwen 3.6 stays the consumer GPU king, and DeepSeek V4-Flash proves too hungry for single-card setups.
Open-Weight LLM Showdown Week 13: DeepSeek V4 Crashes the Party, Gemma 4 Proves Itself, and ICLR Drops Hints
DeepSeek returns with a 1.6T MoE monster under MIT license, Gemma 4's 31B dense model climbs to #3 on Arena AI, and ICLR 2026 papers point to what's next for local inference.
Open Source AI Wins: DeepSeek V4 Narrows the Gap, Apache 2.0 Becomes the Default, and Ollama Hits 52 Million Downloads
DeepSeek V4 Pro approaches frontier-level performance. Google, Mistral, and Alibaba ship under Apache 2.0. Ollama hits 52 million monthly downloads.
Open-Weight LLM Showdown Week 12: Alibaba's Dense 27B Model Just Made MoE Optional
Qwen3.6-27B scores 77.2% on SWE-Bench Verified with a dense architecture that fits on a single RTX 4090. The MoE efficiency narrative just got complicated.
Open-Weight LLM Showdown Week 11: Qwen 3.6 Fires Back, and the 3B Active War Is Real
Alibaba drops Qwen3.6-35B-A3B with 73.4% on SWE-Bench Verified and Apache 2.0 licensing. The 3-billion active parameter class now has three serious contenders.
Open Source AI Wins: Google Drops Gemma 4 Under Apache 2.0, Mozilla Builds a Copilot Killer, and a 30-Person Lab Ships a 400B Model
Google gives Gemma 4 a real open-source license. Mozilla launches Thunderbolt for self-hosted enterprise AI. Arcee AI trains a 400B reasoning model for $20 million. And Milla Jovovich broke GitHub.
Open-Weight LLM Showdown Week 9: Six Labs, One License, and the Speed War That Decides Everything
Google, Alibaba, Meta, Mistral, OpenAI, and Zhipu all ship competitive open-weight models under permissive licenses. The battleground shifts from benchmarks to inference speed on your actual GPU.
Open Source AI Wins: Qwen Goes Agentic, Gemma Goes Apache, and OpenAI Kills Sora to Focus on What Matters
Alibaba's Qwen 3.6 Plus ships the first truly agentic open model. Google finally picks a real license. And OpenAI's Sora shutdown proves closed-source video generation can't pay the bills.
Open-Weight LLM Showdown Week 8: Gemma 4 Rewrites the Rules, Then Trips Over Its Own Feet
Google's Gemma 4 lands with Apache 2.0 licensing and benchmark-topping scores. But a nasty inference speed problem means Qwen still wins on your actual hardware.
Open-Weight LLM Showdown: Qwen3, Llama 4, GLM-5, and Gemma 3 on Real Hardware
Forget the marketing - here's how the latest open-weight models actually perform on your GPU, from 8GB budget cards to 24GB workstations.