Hardware Guide
The short answer: whether ComfyUI runs at all depends first on VRAM; how smoothly it runs depends on RAM, storage, and cooling.
New users often ask “can my computer handle this?” — just check the three tiers below.
Three Tiers (Most Practical)
Section titled “Three Tiers (Most Practical)”1) Entry Tier (just get started)
Section titled “1) Entry Tier (just get started)”- GPU VRAM: 6–8 GB
- System RAM: 16 GB
- Storage: at least 100 GB free (SSD recommended)
What you can do:
- Run SD1.5 basic text-to-image
- Keep resolution at 512–768 for stability
- LoRA works, but don’t stack too many
What to expect:
- Slow generation
- More complex workflows may run out of VRAM
- Running many programs simultaneously causes lag
2) Comfortable Tier (mainstream recommendation)
Section titled “2) Comfortable Tier (mainstream recommendation)”- GPU VRAM: 10–12 GB (e.g., RTX 3060 12G — noticeably better experience)
- System RAM: 32 GB
- Storage: 1 TB NVMe SSD (system + models + cache with room to spare)
What you can do:
- SD1.5 basically free to use
- SDXL common workflows run fine
- ControlNet, Inpainting, Outpainting iterate stably
3) Pro Tier (heavy use)
Section titled “3) Pro Tier (heavy use)”- GPU VRAM: 16–24 GB+
- System RAM: 64 GB (or more)
- Storage: 2 TB+ NVMe SSD (model libraries grow fast)
Best for:
- SDXL high-resolution with multi-condition control
- Multi-LoRA / multi-ControlNet combinations
- More complex production-grade workflows
Approximate VRAM Requirements by Scenario
Section titled “Approximate VRAM Requirements by Scenario”These are estimates for planning purposes — nodes, resolution, batch size, and sampler all affect actual usage.
| Scenario | Approx. VRAM | Notes |
|---|---|---|
| SD1.5 basic text-to-image (512) | 4–6 GB | Most beginner-friendly |
| SD1.5 + 1–2 LoRAs | 6–8 GB | More LoRAs = more VRAM |
| SD1.5 + ControlNet | 8–12 GB | Depends on preprocessing and resolution |
| SDXL basic text-to-image (1024) | 10–14 GB | 8 GB possible but tight |
| SDXL + ControlNet / multi-condition | 14–24 GB | 16 GB+ recommended for production |
| Flux / other large model workflows | 16 GB+ to be comfortable | 24 GB+ for best experience |
If you frequently hit CUDA out of memory, try these in order:
- Reduce resolution
- Reduce batch size (images per run)
- Reduce parallel nodes or model count
- Close other VRAM-hungry programs (games, video apps, browser with many tabs)
How Much Storage Do You Actually Need?
Section titled “How Much Storage Do You Actually Need?”Many people underestimate storage needs. Model files fill up drives fast.
Rough estimates:
- One SD1.5 checkpoint: 2–7 GB
- One SDXL checkpoint: 6–14 GB (common range)
- One LoRA: tens of MB to 1 GB+
- One ControlNet model: 1–3 GB+
If you plan to use ComfyUI long-term, 1 TB SSD is a comfortable starting point.
Don’t just think “can I fit it” — factor in cache, output images, and version backups.
CPU and RAM
Section titled “CPU and RAM”- CPU: not the main actor, but it can’t be too weak; preprocessing, decompression, loading, and system responsiveness all rely on it.
- RAM: 16 GB minimum, 32 GB is more stable. Too little RAM means heavy swap usage — everything feels “half a second behind.”
Mac vs. Windows
Section titled “Mac vs. Windows”- Windows + NVIDIA: currently the most hassle-free combination for compatibility and tutorials.
- Mac (Apple Silicon): works, and the experience keeps improving — but check individual node and custom plugin compatibility beforehand.
Not saying Mac can’t be used — just that when following someone else’s workflow, you’ll occasionally hit “works for them, needs a workaround for you.”
Decision Summary
Section titled “Decision Summary”- Want to try it first: 8 GB VRAM is enough — don’t wait for a perfect machine.
- Committing long-term: prioritize budget for VRAM and SSD.
- Want complex workflows: aim for 16 GB+ VRAM — it saves a lot of headaches.