Flux2-TurboV2 Acceleration

This workflow is a Flux.2 Turbo V2 accelerated text-to-image (or optional reference-guided) setup using the ComfyUI “custom sampler” stack instead of the classic KSampler. It loads the Flux2 UNet (flux2_dev_fp8mixed.safetensors), the Flux2 text encoder (mistral_3_small_flux2_fp8…, type flux2), and the Flux2 VAE (flux2-vae.safetensors). Then it applies a model-only Turbo LoRA (Flux2TurboComfyv2.safetensors) at strength 1.0 before sampling, which is the main speed/behavior change in this graph.

Sampling is assembled from modular nodes: CLIPTextEncode → FluxGuidance (guidance=4) produces the conditioning, then BasicGuider + KSamplerSelect(euler) + Flux2Scheduler(steps=8) feed into SamplerCustomAdvanced. The base latent comes from EmptyFlux2LatentImage with fixed width/height, and you can optionally enable ReferenceLatent nodes (Ctrl-B) to inject one or more reference images; if you bypass them, it becomes pure text-to-image. Finally the latent is VAE-decoded and saved. In short: Turbo LoRA + custom sampler pipeline, with optional reference-latent anchoring when you want extra similarity control.

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