The Local-Only LLMs Showdown is heating up as builders push on-device AI with modest GPUs. On a RTX3060 12GB, the crowd converges on Gemma 3 12B as a fast, capable fit for everyday tasks [1]. Other strong options include qwen3 30B A3B and lighter contenders like Llama 3 and Qwen3 for longer context, with note that smaller 7B–8B models excel in some scenarios [1].
Best local models for 12GB GPUs - Gemma 3 12B – fast, image-input capable, a popular pick for 3060-class GPUs [1]. - qwen3 30B A3B – a solid alternative for broader knowledge tasks [1]. - Mistral Nemo – older but with niche strengths in certain domains [1].
Budgeting for local deployments - A 5,000–10,000 EUR budgetOften leads to a mix of consumer and prosumer GPUs; questions linger between two RTX 3090s vs newer cards like L40S, A6000, or 4090 for voice agents and local hosting [2]. - Base tooling like LLM Studio can help test multiple models locally, useful when you’re sizing for 13 clients and 20–30 chats concurrently [2].
16GB VRAM coding agents on Linux - On a 16GB VRAM laptop with 64–80GB RAM, options include gpt-oss 120B BF16, GLM-4.5-Air, Qwen3-Coder-30B-A3B, and Devstral-24B; decode speeds vary widely (roughly 20t/s for gpt-oss, ~10t/s for GLM in some tests) [3].
Real-world use cases - People are building voice-driven computer assistants for slides, drafting, and task automation; many lean on Gemma and local toolchains to craft co-pilot-like experiences without cloud dependencies [4].
16GB-VRAM model comparisons and takeaways - In 16GB VRAM battles, GPT-OSS often leads with around 80–90 tokens/sec in some setups, while other options hover lower (roughly 15–40 tokens/sec) depending on quantization and backend [5].
Bottom line: local LLM viability hinges on picking the right model for your GPU and workload. Look for balanced dev setups—Gemma, Qwen3, and GLM variants—paired with a sensible hardware plan [1][2][3][4][5].
References
Best Local Model for RTX3060 12GB
Self-hosted LLM thread comparing Gemma 3, Qwen3, Llama3, DeepSeek R1 on RTX3060 12GB; discusses privacy, speed, and setup tips included.
View sourceLocal AI Setup for Chatbots – Hardware Suggestions for a 5–10k € Budget?
Discusses local chatbot setup, multiple users, Qdrant, budget 5-10k EUR, GPU options (RTX 3090, L40S, A6000) and hardware guidance.
View sourceBest local Coding agent for Cursor/IntelliJ AI with 16GB VRAM and 64GB or 80GB RAM on Linux?
Evaluates local LLMs under hardware limits for coding tasks; compares speed, quality, and policy concerns and practical viability of options.
View sourceWhat are your real life/WORK use cases with LOCAL LLMs
Discusses work uses, tooling, models like Qwen3 VL, GLM 4.5V; mentions efficiency, parallelization, workflows, and coding tasks in local environments.
View sourceSince Character.ai is ruined by age verification, what's the best local models you know of for 16GB Vram? (Quantized is fine)
Discusses local LLaMA-like models for 16GB VRAM, weighing sizes 16-32B, 20-30B; compares speed, emotional grasp, and character emulation, others versions.
View source