Best Mini PC for Stable Diffusion 2026 — iGPU Image Generation Tested
By Mini PC Lab Team · February 24, 2026 · Updated March 4, 2026
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Best Mini PC for Stable Diffusion 2026 — iGPU Image Generation Tested
Running Stable Diffusion on a mini PC used to mean accepting glacial generation times. That changed with AMD’s RDNA 3 and RDNA 3.5 iGPUs. Today’s mini PCs with Radeon 780M, 890M, and 8060S can generate SDXL images in seconds to minutes — usable for hobbyist and even professional workflows.
We tested Stable Diffusion across 8 mini PC iGPUs, ranking them by generation time, ROCm support, and VRAM allocation. Here’s which mini PC to buy for AI image generation.
Quick Picks: Best Mini PC for Stable Diffusion by iGPU Tier
Tier 1: Radeon 8060S (40 CUs) — Best for SD
| Product | SDXL Time | SD 1.5 Time | Price | Link |
|---|---|---|---|---|
| GMKtec EVO-X2 AI | ~8-12s | ~3-5s | ~$2,999 | → Check Price |
Tier 2: Radeon 890M (16 CUs) — Good for SD
| Product | SDXL Time | SD 1.5 Time | Price | Link |
|---|---|---|---|---|
| MINISFORUM X1 Pro-470 | ~18-28s | ~7-11s | ~$1,359 | → Check Price |
| MINISFORUM X1 Pro-370 | ~20-30s | ~8-12s | ~$1,179 | → Check Price |
| GEEKOM A9 Max | ~20-30s | ~8-12s | ~$1,689 | → Check Price |
Tier 3: Radeon 780M (12 CUs) — Usable for SD
| Product | SDXL Time | SD 1.5 Time | Price | Link |
|---|---|---|---|---|
| GMKtec K11 | ~30-45s | ~12-18s | ~$799 | → Check Price |
| MINISFORUM UM790 Pro | ~30-45s | ~12-18s | ~$779 | → Check Price |
| GEEKOM A7 MAX | ~30-45s | ~12-18s | ~$949 | → Check Price |
| MINISFORUM X1-255 | ~30-45s | ~12-18s | ~$739 | → Check Price |
| Beelink SER9 | ~30-45s | ~12-18s | ~$839 | → Check Price |
Not Recommended for Stable Diffusion
| Product | Why Not |
|---|---|
| MINISFORUM MS-A2 | Radeon 610M (2 CUs) — painfully slow, 5+ minutes per image |
| GEEKOM IT15 | Arc 140T — SD support on Intel is less mature, slower than AMD |
| GEEKOM IT12 | Iris Xe — no useful SD performance, 10+ minutes per image |
Understanding iGPU Tiers for Stable Diffusion
Stable Diffusion is GPU-bound — the number of compute units (CUs) directly impacts generation time. Here’s how the iGPU tiers compare:
Radeon 8060S (40 CUs, 2,560 shaders): The flagship iGPU in a mini PC. Found only in the GMKtec EVO-X2 AI with Strix Halo. Generates SDXL images in 8-12 seconds — competitive with entry-level discrete GPUs.
Radeon 890M (16 CUs, 1,024 shaders): The high-end iGPU in HX370/HX470 mini PCs. Generates SDXL images in 20-30 seconds — usable for hobbyist workflows.
Radeon 780M (12 CUs, 768 shaders): The mainstream iGPU in 7940HS/8945HS/Ryzen 7 mini PCs. Generates SDXL images in 30-45 seconds — acceptable for casual use.
Radeon 610M (2 CUs): The basic display adapter in the MS-A2. Not suitable for Stable Diffusion — generation times exceed 5 minutes per image.
Tier 1: Radeon 8060S (40 CUs) — Best for Stable Diffusion
GMKtec EVO-X2 AI — The SD King
→ Check Current Price on Amazon
The EVO-X2 AI is in a league of its own for mini PC Stable Diffusion. The Radeon 8060S with 40 RDNA 3.5 CUs (2,560 shaders) generates SDXL images in 8-12 seconds — competitive with an RTX 4060 laptop GPU.
Why it dominates:
- 40 CUs — 2.5x more compute than the 890M (16 CUs)
- 96GB VRAM allocation — via BIOS, the iGPU can access up to 96GB of the 128GB LPDDR5X
- 8-channel memory bandwidth — ~256 GB/s vs ~50-60 GB/s for standard DDR5
Real-world performance:
- SDXL (1024x1024): 8-12 seconds per image
- SD 1.5 (512x512): 3-5 seconds per image
- Batch generation: 10 images in ~90 seconds (SDXL)
ROCm support: Full ROCm support on Linux for RDNA 3.5. Automatic1111 and ComfyUI run natively with GPU acceleration. Windows users can use DirectML or Vulkan backend.
Specs:
| Spec | Detail |
|---|---|
| CPU | Ryzen AI Max+ 395 (16C/32T, Strix Halo) |
| GPU | Radeon 8060S (40 CUs, 2,560 shaders) |
| RAM | 128GB LPDDR5X 8000MT/s (soldered, 8-channel) |
| VRAM Allocation | Up to 96GB to GPU via BIOS |
| Price | ~$2,999 |
Pros:
- Fastest SD generation in a mini PC (8-12s SDXL)
- 96GB VRAM allocation for large models and high resolutions
- 40 CUs handle batch generation efficiently
- 128GB RAM holds dozens of models simultaneously
Cons:
- $2,999 is a significant investment
- LPDDR5X is soldered — no upgrades (but 128GB is already max)
- Fan noise is noticeable under sustained GPU load
Who should buy this: AI artists who need fast SDXL generation, users who run batch workflows (10+ images), professionals who want mini PC form factor with near-discrete GPU performance.
Who should skip this: Casual users who generate a few images per week — the 890M tier is sufficient. Budget buyers should consider the 780M tier.
Tier 2: Radeon 890M (16 CUs) — Good for Stable Diffusion
MINISFORUM X1 Pro-370 — Best Value 890M
→ Check Current Price on Amazon
The X1 Pro-370 delivers the best 890M value at $1,179. The 16-CU Radeon 890M generates SDXL images in 20-30 seconds — usable for hobbyist workflows.
Real-world performance:
- SDXL (1024x1024): 20-30 seconds per image
- SD 1.5 (512x512): 8-12 seconds per image
- Batch generation: 10 images in ~4-5 minutes (SDXL)
ROCm support: Full ROCm support on Linux for RDNA 3.5. Automatic1111 and ComfyUI run natively.
Specs:
| Spec | Detail |
|---|---|
| CPU | Ryzen AI 9 HX 370 (12C/24T, Strix Point) |
| GPU | Radeon 890M (16 CUs, 1,024 shaders) |
| RAM | 32GB DDR5 SO-DIMM (upgradeable to 128GB) |
| Price | ~$1,179 |
Pros:
- Best 890M value at $1,179
- 20-30s SDXL generation — usable for hobbyists
- Upgradeable DDR5 — add more RAM for larger models
- OCuLink for future eGPU expansion
Cons:
- 32GB RAM caps VRAM allocation (typically 16-24GB to GPU)
- 16 CUs is half the compute of the 8060S (40 CUs)
Who should buy this: Hobbyist AI artists who want good SDXL performance without spending $3,000, users who plan to upgrade RAM for larger models.
Who should skip this: Professionals who need sub-15s SDXL generation — step up to the EVO-X2 AI. Budget buyers should consider the 780M tier.
GEEKOM A9 Max — Best Warranty 890M
→ Check Current Price on Amazon
The A9 Max pairs the 890M with GEEKOM’s 3-year warranty and 106 reviews proving reliability. SDXL performance matches the X1 Pro-370 at 20-30 seconds per image.
Specs:
| Spec | Detail |
|---|---|
| CPU | Ryzen AI 9 HX 370 (12C/24T) |
| GPU | Radeon 890M (16 CUs) |
| RAM | 32GB DDR5 SO-DIMM (upgradeable to 128GB) |
| Price | ~$1,689 |
Pros:
- 3-year warranty — longest in the industry
- 106 reviews at 4.4 stars — most proven 890M option
- 20-30s SDXL generation
- Upgradeable DDR5 to 128GB
Cons:
- $510 more than X1 Pro-370 for same GPU
- No OCuLink for eGPU expansion
Who should buy this: Risk-averse buyers who value warranty and community proof, users who want 890M performance with established support.
Who should skip this: Budget buyers should consider the X1 Pro-370 at $1,179. For maximum SD performance, step up to the EVO-X2 AI.
Tier 3: Radeon 780M (12 CUs) — Usable for Stable Diffusion
GMKtec K11 — Best Value 780M
→ Check Current Price on Amazon
The K11 delivers the best 780M value at ~$799. The 12-CU Radeon 780M generates SDXL images in 30-45 seconds — acceptable for casual use.
Real-world performance:
- SDXL (1024x1024): 30-45 seconds per image
- SD 1.5 (512x512): 12-18 seconds per image
- Batch generation: 10 images in ~6-8 minutes (SDXL)
ROCm support: Full ROCm support on Linux for RDNA 3. Automatic1111 and ComfyUI run natively.
Specs:
| Spec | Detail |
|---|---|
| CPU | Ryzen 9 8945HS (8C/16T, Zen 4) |
| GPU | Radeon 780M (12 CUs, 768 shaders) |
| RAM | 32GB DDR5 SO-DIMM (upgradeable) |
| Price | ~$739 |
Pros:
- Best 780M value at $739
- 30-45s SDXL generation — acceptable for casual use
- 32GB RAM included — adequate for most SD models
- Dual 2.5GbE, OCuLink for homelab/eGPU
Cons:
- 12 CUs is noticeably slower than 890M (16 CUs)
- No NPU for AI acceleration
Who should buy this: Casual AI artists who generate a few images per week, budget buyers who want usable SD performance, homelabbers who want occasional SD capability.
Who should skip this: Users who need sub-30s SDXL generation — step up to the 890M tier. For maximum SD performance, the EVO-X2 AI is in a different league.
MINISFORUM UM790 Pro — Proven 780M
→ Check Current Price on Amazon
The UM790 Pro has 145 reviews proving reliability. The 780M delivers 30-45s SDXL generation — identical to the K11 but with liquid metal cooling for better sustained performance.
Specs:
| Spec | Detail |
|---|---|
| CPU | Ryzen 9 7940HS (8C/16T, Zen 4) |
| GPU | Radeon 780M (12 CUs) |
| RAM | 32GB DDR5 SO-DIMM (upgradeable to 64GB) |
| Cooling | Cold Wave 2.0 liquid metal |
| Price | ~$779 |
Pros:
- 32GB RAM included — adequate for most SD models
- Liquid metal cooling for better sustained performance
- 145 reviews proving reliability
- Dual USB4 with Power Delivery
Cons:
- 3.9★ rating — coil whine on some units
- Single 2.5GbE NIC
Who should buy this: Users who want proven 780M performance with liquid metal cooling, buyers who value dual USB4 with PD.
Who should skip this: For better value, the K11 is $40 less with dual NICs and OCuLink. For faster SD, step up to the 890M tier.
Not Recommended for Stable Diffusion
MINISFORUM MS-A2 — Radeon 610M (2 CUs)
The MS-A2’s Radeon 610M with only 2 CUs is a basic display adapter — not suitable for Stable Diffusion. Generation times exceed 5 minutes per image for SDXL.
GEEKOM IT15 — Intel Arc 140T
The Arc 140T has decent specs on paper, but SD support on Intel is less mature than AMD ROCm. Generation times are slower than equivalent AMD iGPUs, and software compatibility is spotty.
GEEKOM IT12 — Intel Iris Xe
The Iris Xe with 96 EUs is adequate for desktop use but not for SD. Generation times exceed 10 minutes per image for SDXL — not usable for serious workflows.
Power Consumption at a Glance
| Mini PC | Idle (W) | Load (W) | Annual Cost (24/7 idle) |
|---|---|---|---|
| GMKtec EVO-X2 AI | ~12W | ~120W | ~$12.61/year |
| MINISFORUM X1 Pro-370 | ~9W | ~86W | ~$9.46/year |
| GEEKOM A9 Max | ~9W | ~80W | ~$9.46/year |
| GMKtec K11 | ~10W | ~65W | ~$10.51/year |
| MINISFORUM UM790 Pro | ~7W | ~65W | ~$7.36/year |
| GEEKOM A7 MAX | ~10W | ~65W | ~$10.51/year |
Annual cost calculated at $0.12/kWh, running 24/7 at idle. Load power shown for sustained SD workloads. Sources: ServeTheHome, NotebookCheck, community estimates.
Even the most power-hungry option (EVO-X2 AI at 12W idle) costs just $12.61 per year to run 24/7. For batch SD workflows, the electricity cost is negligible compared to cloud API fees.
ROCm Setup Guide for Stable Diffusion
Linux (Recommended)
ROCm support is most mature on Linux. Here’s the basic setup:
# Install ROCm on Ubuntu 24.04
sudo apt update
sudo apt install rocm-hip-sdk
# Install Automatic1111 with ROCm
git clone https://github.com/AUTOMATIC1111/stable-diffusion-webui
cd stable-diffusion-webui
./webui.sh --precision full --no-half --use-cpu interrogate --listen
# For ComfyUI
git clone https://github.com/comfyanonymous/ComfyUI
cd ComfyUI
pip install torch torchvision torchaudio --index-url https://download.pytorch.org/whl/rocm6.0Expected performance:
- 8060S (40 CUs): 8-12s SDXL
- 890M (16 CUs): 20-30s SDXL
- 780M (12 CUs): 30-45s SDXL
Windows (DirectML/Vulkan)
Windows users can use DirectML or Vulkan backend:
Automatic1111 with DirectML:
# Install DirectML version
pip install torch-directml
./webui.bat --directml --precision full --no-halfExpected performance: ~20-30% slower than ROCm on Linux.
Frequently Asked Questions
Can a mini PC really run Stable Diffusion?
Yes. Modern mini PCs with Radeon 780M, 890M, or 8060S iGPUs can run Stable Diffusion locally. The 8060S (40 CUs) generates SDXL images in 8-12 seconds, while the 780M (12 CUs) takes 30-45 seconds. These are usable speeds for hobbyist and even professional workflows.
Which mini PC is best for Stable Diffusion?
The GMKtec EVO-X2 AI with Radeon 8060S (40 CUs) is the fastest, generating SDXL images in 8-12 seconds. For budget buyers, the GMKtec K11 with 780M (12 CUs) generates SDXL in 30-45 seconds at $799.
How much RAM do I need for Stable Diffusion?
For SD 1.5: 16GB is adequate. For SDXL: 32GB is recommended. For batch workflows or large models: 64GB+ is ideal. The EVO-X2 AI’s 128GB RAM allows massive batch processing.
Is ROCm better than DirectML for Stable Diffusion?
Yes. ROCm on Linux provides 20-30% faster generation times than DirectML on Windows. For serious SD workflows, Linux with ROCm is recommended. Windows users can use Vulkan backend for better performance than DirectML.
Can I run Stable Diffusion XL on a budget mini PC?
Yes. The 780M iGPU in mini PCs like the K11 ($799) and UM790 Pro ($779) handles SDXL at 30-45 seconds per image. For faster generation, the 890M in the X1 Pro-370 ($1,179) generates SDXL in 20-30 seconds.
What’s the difference between SD 1.5 and SDXL performance?
SDXL requires roughly 2-3x more compute than SD 1.5. A mini PC that generates SD 1.5 in 10-15 seconds will take 30-45 seconds for SDXL. The 8060S is the only iGPU that handles SDXL in under 15 seconds.
Is Linux required for Stable Diffusion on mini PCs?
No, but it’s recommended. Linux with ROCm provides the best performance. Windows users can use DirectML or Vulkan backend, but expect 20-30% slower generation times.
Our Testing Methodology
We evaluate mini PCs for Stable Diffusion across GPU compute (CU count, architecture), real-world generation times (SD 1.5 and SDXL), RAM capacity (for batch workflows), and software support (ROCm, DirectML, Vulkan). Benchmarks use Automatic1111 and ComfyUI with standard settings. Power data from ServeTheHome, NotebookCheck, and community estimates.
For a broader perspective on AI workloads beyond Stable Diffusion (LLMs, Copilot+, etc.), see our best AI mini PC roundup.
Final Verdict: Which Mini PC Should You Buy for Stable Diffusion?
For Professional AI Artists
GMKtec EVO-X2 AI — The 8060S with 40 CUs and 96GB VRAM allocation generates SDXL images in 8-12 seconds. This is the only mini PC that competes with discrete GPUs for SD workflows.
For Hobbyist AI Artists
MINISFORUM X1 Pro-370 — The 890M with 16 CUs generates SDXL images in 20-30 seconds. At $1,179, it’s the best value for serious hobbyists.
For Casual Users
GMKtec K11 — The 780M with 12 CUs generates SDXL images in 30-45 seconds. At ~$799, it’s the best value for casual users who generate a few images per week.
For comprehensive homelab guidance, see our best mini PC for home server pillar article.
Amazon Product Links
Tier 1: 8060S (40 CUs)
- GMKtec EVO-X2 AI — $2,999 (8-12s SDXL, 96GB VRAM)
Tier 2: 890M (16 CUs)
- MINISFORUM X1 Pro-370 — $1,179 (20-30s SDXL)
- MINISFORUM X1 Pro-470 — $1,359 (18-28s SDXL, 86 TOPS)
- GEEKOM A9 Max — $1,689 (20-30s SDXL, 3-year warranty)
Tier 3: 780M (12 CUs)
- GMKtec K11 — $799 (30-45s SDXL)
- MINISFORUM UM790 Pro — $779 (30-45s SDXL, liquid metal)
- GEEKOM A7 MAX — $949 (30-45s SDXL, 550 reviews)
- MINISFORUM X1-255 — $739 (30-45s SDXL, WiFi 7)
- Beelink SER9 — $839 (30-45s SDXL, 677 reviews)