ComfyUI Beginners Guide: Your First Image in 10 Minutes

ComfyUI’s node-based interface looks intimidating at first. When you open it for the first time, you’re presented with a canvas full of connected boxes and wires rather than the input fields you might expect. But the default workflow is already wired up and functional — your first image is closer than it looks. This guide walks through exactly what you’re seeing and how to get from the default screen to a generated image.

The Interface at a Glance

ComfyUI runs in your browser, typically at http://127.0.0.1:8188. The main area is a canvas — you can pan around it by clicking and dragging the background, and zoom with the scroll wheel.

The top-right corner has a small menu bar with buttons for loading/saving workflows, clearing the canvas, and accessing settings. If you’ve installed ComfyUI Manager, there’s also a Manager button here.

On the right side is the Queue panel. When you click Queue Prompt, your generation appears here and shows progress. Completed images appear in the output node on the canvas and are also saved to the ComfyUI/output/ folder automatically.

The Default Workflow

When you first open ComfyUI, a default workflow is loaded. It’s a simple text-to-image pipeline for Stable Diffusion and contains these nodes:

• Load Checkpoint — loads your model file
• CLIP Text Encode (positive) — your positive prompt
• CLIP Text Encode (negative) — your negative prompt
• Empty Latent Image — sets the resolution and batch size
• KSampler — runs the diffusion process
• VAE Decode — converts the latent image back to pixels
• Save Image — saves and displays the output

These nodes are wired together left to right, and data flows along the wires. The coloured dots on each node are connection points — yellow for model data, purple for conditioning (prompts), red for latent images, and so on. Wires can only connect matching types.

Loading a Model

Click on the Load Checkpoint node. You’ll see a dropdown labelled with the currently selected model (or “None” if no model is loaded). Click it and select the model you downloaded. If you’ve placed a .safetensors or .ckpt file in ComfyUI/models/checkpoints/ and it doesn’t appear, restart ComfyUI.

The Load Checkpoint node outputs three things: the model itself, CLIP (for text encoding), and the VAE (for image decoding). You can see these as the three output dots on the right side of the node, each connected to the appropriate downstream node.

Writing Your Prompt

Click on the upper CLIP Text Encode node (the positive one — usually labelled “positive” or wired to the positive conditioning input on the KSampler). There’s a text area inside the node. Click it and type your prompt.

A few prompting tips for SD 1.5 and SDXL:

• Be specific. “A red fox sitting on a snow-covered log, winter forest, soft morning light, photorealistic” produces better results than “a fox in the snow”.
• Quality boosters work: adding masterpiece, best quality, highly detailed at the start helps with SD 1.5 and SDXL (less so with Flux).
• Negative prompts matter for these models. The lower CLIP Text Encode is your negative prompt — common entries include blurry, low quality, deformed, extra limbs, watermark.

For Flux models, prompting works differently — natural language descriptions work better than keyword lists, and negative prompts have no effect.

The KSampler Node

The KSampler is the core of the pipeline — it runs the diffusion process. The main settings to understand:

• seed: The random seed. Same seed + same settings = same image. Change it for variety. Click the dice icon to randomise on each run.
• steps: Number of diffusion steps. 20 is a good default for SD 1.5/SDXL. More steps = more refined output, but diminishing returns above 30–40.
• cfg: Classifier-Free Guidance scale. Higher values follow the prompt more closely but can produce over-saturated results. 7–8 is a good default for SD 1.5. For Flux, use 1.0.
• sampler_name: The sampling algorithm. euler_a and dpmpp_2m are popular choices for SD 1.5/SDXL. For Flux, use euler.
• scheduler: Works alongside the sampler. karras is a solid default for most models.
• denoise: At 1.0 for text-to-image. Only change this for image-to-image workflows.

Setting the Resolution

The Empty Latent Image node controls output resolution. SD 1.5’s native resolution is 512×512 — going higher works but may produce duplicated subjects. SDXL is designed for 1024×1024. Change width and height by clicking the number fields.

The batch_size field controls how many images to generate per queue. Leave it at 1 until you know what you’re doing — generating batches is faster overall but fills your VRAM quickly.

Generating Your First Image

With a model loaded and a prompt written, click Queue Prompt (top of the right panel, or press Ctrl+Enter). The progress appears in the Queue panel. Generation time depends on your hardware and settings — on a mid-range GPU, SD 1.5 at 20 steps takes a few seconds. SDXL takes longer.

The completed image appears inside the Save Image node on the canvas and is saved to ComfyUI/output/. Right-click the image in the node to open it in a new tab or copy it.

Common First-Run Mistakes

• Wrong model for the workflow: Loading a Flux model into the standard SD checkpoint workflow won’t work. Flux needs its own node setup. See How to Install Flux in ComfyUI.
• High CFG with Flux: If you accidentally loaded a Flux model and images look like abstract noise, set CFG to 1.0.
• Out of memory errors: Lower the resolution, reduce batch size to 1, or add --lowvram to your launch command.
• Model not appearing in dropdown: File must be in models/checkpoints/, not a subfolder. Restart ComfyUI after adding files.
• Black images: Often a VAE issue with certain model files. Try a different checkpoint or add an explicit VAE Loader node pointed at a known-good VAE.

Next Steps

Once you’ve generated your first image, the natural next step is exploring better models. See Best Models for ComfyUI in 2026 for a rundown of what’s worth using, or jump straight to installing Flux if your hardware can handle it.

If you get stuck at any point, the ComfyUI GitHub issues page and the r/comfyui subreddit are both active and helpful. Most beginner problems — missing models, black images, error nodes — have been encountered and solved many times before. A quick search will usually find the answer faster than waiting for a reply.

For a full index of every ComfyUI guide on Serverman, see the ComfyUI complete guide and hub.