Open-Weight LLM Showdown: Mistral Small 4 Arrives, DeepSeek V4 Finally Lands
Mistral drops a 119B MoE model under Apache 2.0, DeepSeek V4 emerges from stealth, and dual RTX 5090 setups are matching H100 on 70B inference. This week changed the game.
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Mistral drops a 119B MoE model under Apache 2.0, DeepSeek V4 emerges from stealth, and dual RTX 5090 setups are matching H100 on 70B inference. This week changed the game.
Stop paying $100/year for cloud transcription. Run Scriberr on your own hardware for free, private meeting notes with speaker identification.
GTC 2026's biggest announcements were open-source. Nemotron 3 Super runs locally on RTX PCs, LTX 2.3 generates 4K video with audio, and vLLM hits production grade.
Set up Fooocus on your own computer for unlimited AI image generation with no subscriptions, no data collection, and Midjourney-quality results.
Which local models can actually use tools, call functions, and run multi-step workflows? Function-calling and TAU-bench picks from 8GB to 32GB VRAM.
Head-to-head comparison of local chat and assistant models from 8GB to 32GB VRAM. Current picks: Qwen3.5, Gemma 4, GPT-OSS, Qwen3.6, and GLM-4.7-Flash.
Which open-weight coding model to run locally? HumanEval and SWE-bench picks from 8GB to 32GB GPUs, with IDE setup. Qwen2.5-Coder, Qwen3.6, Devstral.
Voice cloning, transcription, and TTS without the cloud. Parakeet, Canary, Whisper, Step-Audio-EditX, and Kokoro tested from 8GB to 32GB VRAM.
From TranslateGemma to LLM-based translation with Qwen and Aya Expanse. Privacy-first alternatives to Google Translate and DeepL, tested per GPU tier.
Run image analysis, document OCR, and visual reasoning locally. Qwen3-VL, InternVL3.5, Molmo2, and MiniCPM-V tested from 8GB to 32GB VRAM.
Georgi Gerganov's team is now at Hugging Face, unifying the model hub with the inference engine that powers Ollama, LM Studio, and the entire local AI ecosystem.
Complete guide to running local AI on 12GB GPUs - chat, coding, translation, vision, speech, and agents. The comfortable tier for RTX 3060 12GB and RTX 4070.
Complete guide to running local AI on 16GB GPUs - chat, coding, translation, vision, speech, and agents. The sweet spot for RTX 4060 Ti, RTX 5060, and Arc A770.
Complete guide to running local AI on 32GB GPUs - chat, coding, translation, vision, speech, and agents. The new frontier with RTX 5090. Near-lossless quantization and 70B models on a single card.
Complete guide to running local AI on 24GB GPUs - chat, coding, translation, vision, speech, and agents. Where local models start competing with cloud APIs. RTX 3090 and RTX 4090.
Run local AI on 8GB GPUs - chat, coding, vision, speech, and agents. Current model picks and honest limits for RTX 4060, RTX 3070, and similar cards.
Two weeks after our last roundup, the 5090 benchmarks are in and Qwen 3.5 Small models are running on phones. Here's the real performance picture.
Five missed release windows, a mysterious V4 Lite appearance, and silence from DeepSeek. What's really happening with China's most anticipated AI model?
Set up your own private translation server in minutes. Keep your text off corporate servers while getting quality translations in 50+ languages.
A $200/month Mac mini running an always-on AI agent with full file system access raises serious privacy questions - especially after Perplexity's recent security track record.
Run Stable Diffusion on your own GPU for private, cheaper image generation without subscriptions.
This week's open-source highlights: AI2's hybrid architecture proves transformers need help, autoresearch automates ML experiments overnight, and local inference gets serious upgrades.
Nvidia open-sources a 30B-parameter reasoning model that runs on consumer GPUs with a million-token context window. Here's what makes it different.
AI2 and Lambda trained a hybrid transformer-RNN model that's twice as data-efficient as pure transformers. But can you actually run it locally?