The best photorealism and text-in-image accuracy of any local model in 2026. Multi-reference image conditioning. Handles 1000-character prompts with full semantic fidelity — the definitive standard for professional AI photography.
This model requires a specialized High-VRAM environment. Ensure you have the latest CUDA Drivers or Metal Framework installed.
Minimum VRAM: 26GB VRAM Recommended
The FLUX.2 Dev model by Black Forest Labs is a 32B diffusion parameter architecture optimized for image tasks. It requires approximately 24GB of VRAM to comfortably run locally using a BF16 quantization. Extending the context window up to 0 tokens will dynamically allocate further VRAM, meaning high-bandwidth memory hardware is strictly advised.
For running FLUX.2 Dev at maximum tokens-per-second, we recommend using LM Studio or Ollama with a GGUF quantization (Q4_K_M or Q6_K). If you are multi-GPU, use vLLM to distribute the layers across your VRAM pool for optimal throughput.
You will need a GPU with at least 26GB of VRAM to run the BF16 quantized version smoothly with a moderate context window.
The simplest method is utilizing Ollama by executing 'ollama run flux2-dev' directly in your command line. Alternatively, you can search for the model via LM Studio's interface.