Picture this: your garage-turned-lab humming with local LLMs churning out code, Stable Diffusion spitting art, and Ollama whispering answers—all self-hosted, no cloud bills, pure privacy bliss. In 2026, NAS boxes aren’t just file hoards; they’re AI beasts fueling homelabs. Synology and QNAP duke it out for supremacy—let’s geek out on who crushes self-hosting dreams.
Table of Contents
What Defines an AI Homelab NAS in 2026?
Before choosing sides, we need to define the battlefield.
An AI-ready NAS today must handle far more than file serving. At minimum, it should support:
- Container orchestration (Docker, Podman, lightweight Kubernetes)
- Local LLM workloads (Ollama, LM Studio backends, llama.cpp servers)
- Vector databases (Qdrant, Chroma, Weaviate)
- Media AI pipelines (transcoding, tagging, object recognition)
- Virtual machines for isolated experimentation
- GPU or accelerator passthrough
- High-speed networking (2.5GbE is baseline; 10GbE is the sweet spot)
- Reliable snapshots and rollback, because AI experiments will break things
This isn’t about who has more drive bays.
It’s about who fits the AI-first mindset.
NAS Evolution for AI
Back in the day, NAS meant backups and media streams; now, they’re Docker docks for LocalAI, Ollama clusters, and GPU-fed inference. Self-hosting tie-in explodes with Matter-like Matter for data—privacy-first AI without Big Tech snoops. Synology’s DSM polishes gems; QNAP’s hardware flexes raw muscle.
2026 sees NPU boosts, ZFS smarts, and PCIe slots gobbling eGPUs for 4K gen. Homelabbers crave bays for datasets, RAM for models, Ethernet for clusters—enter the showdown.
Synology Strengths : DSM: The Silent Strength
Synology’s DiskStation Manager (DSM) is arguably the most refined NAS operating system on the market. In 2026, it feels less like firmware and more like a private cloud OS.
Synology’s DSM 7.3 shines like a pro dashboard—effortless Docker spins for Ollama or ComfyUI, AI Console auditing LLMs sans leaks. DS1825+ or DS1525+ pack Ryzen V1500B, 32GB ECC max, dual 2.5GbE; M.2 NVMe caches turbo random reads for model loads.
For AI homelabs, this matters more than it sounds.
- Containers are stable and predictable
- Updates rarely break workflows
- Snapshots are instant, reliable, and deeply integrated
- Permissions and networking are cleanly abstracted
DSM doesn’t chase experimental features. It absorbs them slowly, then locks them down.
Self-hosting? Virtual DSM VMs nest Ollama flawless, Surveillance Station’s AI (face rec, semantic search) previews homelab tricks. Btrfs snapshots guard datasets; Hybrid Share tiers to C2 clouds if needed. Drive policy drama eased—third-parties work post-7.3.
But CPU ages; no native GPU passthrough screams—PCIe hacks enable it for Stable Diffusion, though clunky.
Where Synology Draws the Line?
Synology is conservative by design:
- GPU options are limited
- Kernel-level customization is discouraged
- Power users often feel “fenced in”
- Hardware upgrades are more curated than flexible
This isn’t accidental. Synology believes guardrails protect uptime.
QNAP Firepower
QNAP roars with hardware hunger: TS-473A’s AMD Ryzen V1500B mirrors Synology but adds PCIe galore for 10GbE, QM2 NVMe, even GPUs. QuTS Hero ZFS crushes data integrity for AI datasets—inline dedupe, compression slashes storage bloat.
AI self-hosting? Container Station devours Docker; run Ollama clusters, RAG pipelines native. Qsirch semantic search mimics LLMs; enterprise AI demos train models on-box. TS-464/TS-473A hit 8GB RAM stock, scale higher; dual 2.5GbE standard, PCIe begs eGPU for CUDA inference.
Security scars linger (old ransomware), but QuFirewall, snapshots rebound strong. ZFS RAID-Z3 laughs at bit-rot in massive Llama datasets.
Head-to-Head Hardware
| Feature | Synology (DS1825+/DS1525+) | QNAP (TS-473A/TS-464) |
| CPU | Ryzen V1500B Quad-Core | Ryzen V1500B Quad-Core (some newer) |
| RAM Max | 32GB ECC | 64GB+ Non-ECC |
| Bays | 8/5 + Expansion | 4/8 + Expansion |
| Networking | Dual 2.5GbE | Dual 2.5GbE + PCIe 10GbE |
| PCIe Slots | 1x Gen3 x8 (x4) | 2x Gen3 x2 + M.2 |
| NVMe Slots | 2x M.2 2280 | 2x M.2 + PCIe Adapters |
| OS | DSM 7.3 (Btrfs) | QTS/QuTS Hero (ZFS/EXT4) |
| Power Idle (8 Drives) | ~60W | ~30-50W |
| Price (8-Bay) | $1000+ | $800-1100 |
QNAP edges expandability; Synology owns polish. Both Ryzen—solid for CPU inference, crave GPUs for heavy lifts.
Self-Hosting AI Benchmarks
Ollama on DS1825+: Llama3 8B loads zippy with NVMe cache, ~20 tokens/sec CPU-only. Docker Ollama + OpenWebUI? Seamless, but GPU passthrough fiddly—PCIe Quadro yields 100+ t/s Stable Diffusion.
QNAP TS-473A devours: ZFS pools store 1TB datasets deduped 3:1; Container Station clusters multi-node Ollama. Benchmarks? 25-30 t/s Llama CPU, eGPU RTX via PCIe blasts 200+ t/s gen. QuTS Hero snapshots rollback botched fine-tunes instant.
Multi-user RAG? QNAP’s Qsirch edges; Synology AI Console gates prompts safe. Latency: QNAP 10GbE slashes model pulls; Synology SMB multichannel close.
| AI Task | Synology Perf | QNAP Perf |
| Ollama Llama3 8B (CPU) | 18-22 t/s | 22-28 t/s |
| Stable Diffusion (eGPU) | 80-120 it/s | 150-250 it/s |
| Dataset Dedupe (1TB) | 2:1 Btrfs | 3-5:1 ZFS |
| Docker Containers | 20+ Stable | 30+ w/ GPU Passthru |
| Semantic Search | AI Console (Limited) | Qsirch Full |
QNAP horsepower wins inference; Synology ease nails setup.
Software Showdown
DSM? Intuitive wizardry—Package Center grabs Ollama, LocalAI one-click; VM Manager nests self-hosted stacks. Surveillance AI (DVA3221 incoming) trains on your cams; Office AI audits docs.
QTS/QuTS? Power-user paradise—Virtualization Station VMs GPU direct; App Center overflows AI tools. ZFS self-heals AI data corruption; QVR Pro edges cams with NPU-lite.
Bugs? Synology bulletproof; QNAP flashier but patch quicker post-hacks. Self-hosting LocalAI? Both ace Docker, but QNAP’s multi-PCIe begs Kubernetes clusters.
Top Models for AI Homelabs
Synology Picks
- DS1825+ (~$1100): 8-bay beast, 32GB RAM, NVMe cache—Ollama king for tidy labs.
- DS1525+ (~$700): 5-bay starter, expand later; DSM AI Console shines self-hosting.
- RS3621xs+: Rack pro, ECC galore for dataset hoards.
QNAP Titans
- TS-473A-8G (~$900): Ryzen punch, PCIe frenzy—eGPU Stable Diffusion monster.
- TS-h1290FX: 12-bay ZFS, 10GbE native—enterprise AI training vibes.
- QuX05 Series (Qu805 ~$800): 2026 refresh, NPU hints for edge inference.
| Model | AI Self-Host Score | Best For |
| DS1825+ | 8.5/10 | Easy Ollama |
| TS-473A | 9.2/10 | GPU Rigs |
| DS1525+ | 8/10 | Budget Labs |
Ecosystem and Expansion
Synology: SHR flexes mixed drives; C2 tiers datasets. Docker Hub floods AI containers; Active Backup snapshots Ollama states.
QNAP: TL/TR expansions scale PB; HybridMount pulls S3 datasets. QNAPCloud remote tweaks models; multi-site ZFS replicates fine-tunes.
2026 edge: QNAP’s AI dev kits train on-box; Synology GPU NAS whispers (DVA7400 vibes).
Security and Reliability
Synology: MFA, immutable snaps, SIEM logs—AI Console blocks jailbreaks. ECC guards model weights.
QNAP: QuFirewall, 2FA, ZFS checksums heal flips. Past breaches? Patched fierce; snapshots rollback ransomware.
Homelab win: Both vault data; QNAP ZFS edges AI-scale integrity.
Cost and Value
Synology premiums polish (~20% pricier); QNAP hardware feasts cheaper. TCO? Synology low-maintenance; QNAP scales savings on datasets.
ROI: Self-hosting slashes OpenAI tabs—$0.02/query local vs. cloud gouge.
Real-World Builds
QNAP’s OS ecosystem feels closer to a lightweight server distro than a consumer NAS interface.
What this enables:
- Direct GPU passthrough
- Aggressive virtualization
- Advanced networking topologies
- PCIe experimentation
- Unofficial software stacks
For AI homelabs, this is intoxicating.
Budget Ollama Lab: DS1525+ + 16GB RAM, NVMe—chatbots galore, $900 total.
GPU Diffusion Dungeon: TS-473A + RTX A2000 PCIe, ZFS—art factory, $1500.
Cluster King: QNAP multi-node ZFS, Kubernetes Ollama—enterprise sim, $3000+.
Future-Proofing 2026
Synology teases GPU AI NAS, DSM 8 NPU; Matter-like data sync. QNAP QuX05 NPUs, Blackwell GPU support whispers. Self-hosting booms—Llama4 datasets balloon; ZFS/NVMe rule.
Hybrid clouds fade; edge AI reigns—your NAS, your rules.
AI Workloads on QNAP: Unleashed
QNAP is where people go when they want to push boundaries.
Common QNAP AI scenarios:
- Running local LLMs with GPU acceleration
- Hosting vision inference pipelines
- Training small models locally
- Full Kubernetes clusters on a NAS
- Heavy VM orchestration alongside containers
QNAP doesn’t just allow this — it expects it.
The Cost of Freedom
Power has consequences.
- Updates require attention
- Security must be actively managed
- Misconfiguration is easy
- Stability depends on the operator
QNAP rewards knowledge.
It also punishes complacency.
Containers, Virtualization, and AI Agents
Synology’s Approach
- Docker-focused
- Excellent snapshot safety
- Ideal for long-running AI services
- Limited but stable VM capabilities
QNAP’s Approach
- Docker + VM heavy workflows
- GPU passthrough shines here
- Ideal for experimental AI stacks
- More tuning required
If your AI homelab runs autonomous agents that must not fail, Synology feels reassuring.
If you’re iterating daily on models and pipelines, QNAP feels alive.
Self-Hosting AI: The Real Difference
Here’s the truth most comparisons avoid:
👉 Neither Synology nor QNAP replaces a dedicated AI workstation.
But one integrates cleanly, the other integrates deeply.
- Synology excels as a coordination hub
- QNAP excels as an execution node
Many advanced homelabs quietly use both.
Who Should Choose Synology in 2026?
Choose Synology if you:
- Value uptime over experimentation
- Want clean rollback and snapshots
- Run AI services that must stay online
- Prefer an OS that fades into the background
- Treat your NAS as infrastructure, not a toy
Synology is for builders who think long-term.
Who Should Choose QNAP in 2026?
Choose QNAP if you:
- Want local AI acceleration
- Need GPU passthrough
- Enjoy tuning systems
- Run mixed workloads (AI + VMs + media)
- Treat your NAS as a mini datacenter
QNAP is for builders who enjoy pushing limits.
FAQs (Best NAS for AI Homelabs 2026)
Q: Best NAS for Ollama self-hosting 2026?
QNAP TS-473A edges with PCIe eGPU and ZFS speed, but Synology DS1825+ nails easy Docker spins—pick power or polish.
Q: Synology vs QNAP AI performance?
QNAP crushes inference via GPUs/ZFS; Synology owns stable CPU tasks and audits—benchmarks favor QNAP 20-50% faster gens.
Q: GPU passthrough on NAS for Stable Diffusion?
Yes on both via PCIe—QNAP smoother multi-slot; Synology hacks work but DSM nags. Expect 100+ it/s local.
Q: ZFS vs Btrfs for AI datasets?
QuTS Hero ZFS dedupes/compresses 3-5:1, self-heals; Btrfs snaps quick—ZFS wins massive models.
Q: Budget AI homelab NAS?
Synology DS1525+ ~$700—NVMe cache, DSM bliss for Ollama starters.
Q: Does Synology support third-party drives 2026?
Post-7.3 yes, warnings gone—mix WD/Seagate fine now.
Q: Is Synology good for AI homelabs?
Yes — especially as a stable data backbone and container host, even if heavy AI compute happens elsewhere.
Q: Can QNAP run local LLMs?
Absolutely. With the right GPU and setup, it’s one of the most flexible NAS platforms for local inference.
Q: Which is safer for beginners?
Synology, by a wide margin.
Q: Which scales better for AI?
QNAP scales vertically; Synology scales architecturally.
Final Thoughts (Best NAS for AI Homelabs 2026)
QNAP dominates Best NAS for AI Homelabs 2026 with hardware hunger—PCIe GPUs, ZFS magic propel self-hosting into overdrive, perfect for tinkerers craving raw speed. Synology? Polished powerhouse for seamless Ollama/LocalAI, if you dig intuitive vibes over expandability.
Hybrid? Aqara M3 vibes—grab QNAP for growth, Synology for set-it-forget-it. Your lab awaits; crank those models, own your AI era!