Dify Community Edition Deployment Support｜End-to-End Services from Hardware Sizing to Fully Offline Builds
All-in-one services specialized for the open-source edition
Why teams choose our Dify deployment support
🔓 Focused on the open-source edition
We specialize in deploying the Dify Community Edition (free). No dependency on commercial editions and no vendor lock-in. Licensing costs are zero.
🔧 Full hardware lifecycle support
From GPU/CPU selection, memory and storage design, to power consumption estimates. We provide a one-stop service from procurement to installation and configuration.
🌐 Cloud or fully offline—your choice
We support AWS/Azure and other clouds as well as completely offline (air-gapped) environments, enabling secure GenAI operations for high-confidentiality use cases.
Instance-based pricing model
We adopt a fixed monthly fee per instance. This means:
- ✅ No price increase when user counts grow
- ✅ Clear cost control by running separate instances per use case
- ✅ A predictable, fixed-cost model for budgeting
Cut costs with Dify Community Edition + open-source LLMs
| Item | Typical commercial AI services | Our Dify Community Edition support |
|---|---|---|
| Software license | ¥100,000–500,000 / month | ¥0 (free forever) |
| LLM usage fees | Usage-based (often hundreds of thousands of JPY / month) | ¥0 (when using open-source LLMs) |
| Customization | Limited / extra fees | Unlimited (source code modifiable) |
| Data location | Vendor cloud | Your environment (full control) |
| Offline operation | Not available | Fully offline supported |
End-to-end support: from hardware sizing to operations
1. Hardware sizing & procurement
The biggest challenge of running open-source LLMs in-house is hardware selection. We design the details below:
- GPU selection: from NVIDIA A100/H100 to RTX 4090—optimized to budget and model size
- CPU / memory layout: configurations that maximize inference throughput (e.g., AMD EPYC + 512GB RAM)
- Storage design: NVMe SSD layouts to reduce model load times
- Power & cooling: environment design for 1.5–5kW class systems
- Procurement support: best-price sourcing from domestic and overseas vendors
2. Flexible build options by environment
| Environment type | Characteristics | Best for |
|---|---|---|
| Public cloud | Built on AWS/Azure/GCP Scalability first | Dev environments, variable load |
| Private cloud | Built in your data center Security and cost optimization | Production, steady workloads |
| Fully offline | No Internet connectivity Highest security level | Sensitive data, regulatory use |
| Hybrid | On-prem + cloud combined Flexibility with security | Phased migration, DR planning |
3. Selecting and optimizing open-source LLMs
With extensive evaluation experience across open-source LLMs, we recommend models best suited to each use case:
- Qwen2.5 (72B/32B/7B): top-tier Japanese ability, commercial use allowed
- DeepSeek-V3: excellent cost efficiency with MoE for speed
- Llama 3.2 (405B/70B/8B): by Meta, highly stable
- Command-R+: strong for RAG, 104 languages
- Phi-3: lightweight models for edge devices
Through quantization (GGUF/AWQ/GPTQ), even large models can run on constrained hardware.
Pricing (one-time setup fee + monthly per instance)
One-time setup fee
| Plan | Scope | Setup fee |
| Minimum | Dify Community Edition setup Ollama integration (1–2 models) Basic RAG (pgvector) Weekly backups | ¥120,000 |
| Standard | All of the above, plus: Multi-LLM architecture RAG tuning (chunking/embedding) Load testing | ¥280,000 |
| Enterprise | Full design from requirements HA/cluster architecture Hardware sizing & procurement Offline (air-gapped) build Ops training & documentation | ¥500,000+ |
Monthly support (per instance)
| Basic | Pro | Enterprise | |
| Monthly (per instance) | ¥15,000 | ¥35,000 | ¥60,000+ |
| Users | Unlimited | Unlimited | Unlimited |
| Knowledge storage | 10GB | 100GB | Unlimited |
| Backups | Weekly | Daily | Real-time |
* Infrastructure costs (cloud usage, electricity, etc.) are separate.
* When using commercial APIs (e.g., OpenAI), API fees are charged separately.
Case studies｜Success with Dify Community Edition
[Case 1] Financial Institution A｜Fully offline GenAI
- Challenge: External APIs prohibited by regulation, yet GenAI required
- Architecture:
- Dify Community Edition + Qwen2.5-72B
- On-prem server with NVIDIA A100 80GB × 2
- Fully offline (air-gapped)
- Outcome:
- Confidential document summarization/analysis fully in-house
- ¥24M annual API cost reduction (¥0 API spend)
- 3× faster processing (local inference)
[Case 2] Manufacturer B｜Phased migration from cloud API to on-prem
- Challenge: ChatGPT API spend exceeded ¥200k/month
- Architecture:
- Phase 1: Dify CE on AWS
- Phase 2: Switch to open-source LLM (DeepSeek-V3)
- Phase 3: Full migration to corporate DC
- Outcome:
- 95% API cost reduction (to < ¥10k/month)
- 2× faster responses
- Deeper business-specific customization
Why Community Edition?｜Difference from commercial editions
| Feature | Community (free) | Commercial | Our support |
|---|---|---|---|
| Core features | ◎ Full features | ◎ Full features | All features supported |
| Source code | ◎ Fully open | △ Partially closed | Customization assistance |
| Official support | × None | ◎ Vendor support | ◎ Provided by us |
| License fees | ◎ Free forever | × Paid | – |
| Updates | ○ Community-driven | ◎ Guaranteed | We validate & apply |
Bottom line: Community Edition + our support delivers commercial-grade value at a fraction of the cost.
FAQ
Q: Is commercial use really allowed with the Community Edition?
A: Yes. Dify Community Edition is distributed under the Apache License 2.0, so commercial use is fully permitted. You can integrate it into internal systems without restriction.
Q: What hardware do we need?
A: It depends on your use case. For small footprints, you can run with CPU-only (no GPU). For larger workloads, we design an optimal configuration for you.
Q: How do we migrate from our current ChatGPT setup?
A: Dify is compatible with OpenAI-style APIs, so you can migrate existing prompts and workflows with minimal changes. We also create phased migration plans.
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