Local LLM model fit
Qwen3 4B Thinking 2507 is a 4.02B Qwen model. This page estimates Q4 VRAM fit, Ollama command, context planning, and fallback choices for common local AI GPUs.
Small local reasoning, routing, tool decisions, and lightweight coding on 6GB-8GB GPUs. Weakness: Thinking mode can be slower and the 256k context claim still needs practical VRAM headroom.
| Hardware | Examples | Clean capacity | Q4 need | Status | Calculator |
|---|---|---|---|---|---|
| 6 GB VRAM entry GPU | GTX 1660, RTX 2060 6GB | 4.5 GB clean VRAM | 3.2 GB | Runs locally | Open calculator |
| 8 GB VRAM mainstream GPU | RTX 3060 Ti, RTX 4060, RTX 3070 | 6.5 GB clean VRAM | 3.2 GB | Runs locally | Open calculator |
| 10 GB VRAM older high-end GPU | RTX 3080 10GB | 8.5 GB clean VRAM | 3.2 GB | Runs locally | Open calculator |
| 12 GB VRAM local agent GPU | RTX 3060 12GB, RTX 4070, RTX 5070 | 10.5 GB clean VRAM | 3.2 GB | Runs locally | Open calculator |
| 16 GB VRAM creator GPU | RTX 4060 Ti 16GB, RTX 4080, RTX 5070 Ti, RTX 5080 | 14.5 GB clean VRAM | 3.2 GB | Runs locally | Open calculator |
| 24 GB VRAM homelab workstation | RTX 3090, RTX 4090 | 22.5 GB clean VRAM | 3.2 GB | Runs locally | Open calculator |
| 32 GB VRAM Blackwell workstation | RTX 5090 | 30.5 GB clean VRAM | 3.2 GB | Runs locally | Open calculator |
| 48 GB VRAM workstation | RTX A6000, L40S 48GB | 46.5 GB clean VRAM | 3.2 GB | Runs locally | Open calculator |
| Apple Silicon 32 GB unified memory | M2 Max 32GB, M3 Max 36GB | 26 GB unified | 3.2 GB | Runs locally | Open calculator |
| Apple Silicon 256 GB unified memory | Mac Studio M3 Ultra 256GB, Mac Studio M4 Ultra 256GB | 250 GB unified | 3.2 GB | Runs locally | Open calculator |
| Quantization | Estimated memory | Use case |
|---|---|---|
| Q4 / 4-bit | 3.2 GB | Default local inference balance |
| Q5 / 5-bit | 4 GB | Better quality, more VRAM |
| Q8 / 8-bit | 6.4 GB | High quality, much more VRAM |
| FP16 / 16-bit | 12.8 GB | Mostly workstation/server use |
This is a practical planning estimate, not a benchmark. Real memory use changes with backend, context length, KV cache, quantization file, drivers, and offloading settings.
4B · Small multimodal local assistant and low-resource setups
4B · Efficient multimodal local assistant and edge-style agent workflows
7B · Small local coding assistant and agent tool generation
8B · Fast general local assistant with reasoning/coding balance