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+# GPU Setup Research: Rack Server AI Workloads
+
+## Goal
+Cost-efficient rack-mountable GPU setup for:
+1. **LLM coding inference** (Ollama + qwen2.5-coder models)
+2. **Image generation** (ComfyUI / InvokeAI with Stable Diffusion)
+
+Target servers: Dell R720/R730 or HP DL380 equivalent (2U rack)
+
+## GPU Candidates Compared
+
+| Feature | Tesla P40 | RTX A2000 12GB | Tesla T4 | Tesla M40 |
+|---------|-----------|----------------|----------|-----------|
+| Architecture | Pascal (2016) | Ampere (2020) | Turing (2018) | Maxwell (2015) |
+| VRAM | 24GB GDDR5 | 12GB GDDR6 | 16GB GDDR6 | 24GB GDDR5 |
+| Tensor Cores | No | Yes | Yes | No |
+| TDP | 250W | 70W | 70W | 250W |
+| Compute Capability | 6.1 | 8.6 | 7.5 | 5.2 |
+| Cooling | Passive (needs fan) | Active (blower) | Passive (needs fan) | Passive (needs fan) |
+| Aux Power Required | Yes (8-pin) | No (bus-powered) | No (bus-powered) | Yes (8-pin) |
+| Used Price (2026) | ~$300 | ~$490 | ~$800+ | ~$100-150 |
+| PCIe | Gen3 x16 | Gen4 x16 | Gen3 x16 | Gen3 x16 |
+
+## Performance Benchmarks
+
+### LLM Inference (tokens/sec via Ollama)
+
+| Model | A2000 12GB | P40 24GB |
+|-------|------------|----------|
+| qwen2.5:14b | ~21 t/s | ~17 t/s |
+| llama3.2:3b-Q8 | ~50 t/s | ~40 t/s |
+| llama3.2:3b-Q4 | ~60 t/s | ~48 t/s |
+
+### Image Generation (ComfyUI)
+
+| GPU | SDXL 20 steps | Notes |
+|-----|---------------|-------|
+| P40 | ~49 seconds | Requires `--force-fp32` flag |
+| A2000 | ~16 seconds | ~3x faster than P40 |
+| RTX 4090 | ~3 seconds | Reference (16x faster than P40) |
+
+## Rack Server Compatibility
+
+### RTX A2000 in R720/R730
+- **Physical fit**: Yes. Dual-slot, low-profile, 167mm length
+- **Power**: 70W bus-powered, no aux cable needed. Must use 75W slots (slots 4-7 on R720)
+- **Cooling**: Blower-style fan exhausts out bracket — ideal for rack airflow
+- **Requirement**: Dual CPUs needed for GPU PCIe slots
+- **Confirmed working** in Dell R740XD (similar architecture)
+- Third-party single-slot cooler available from n3rdware for tighter fits
+
+### Tesla P40 in R720/R730
+- **Physical fit**: Yes. Full-length, single-slot, designed for rack servers
+- **Power**: 250W, requires 8-pin aux power. Needs GPU enablement kit (power cables + riser)
+- **Cooling**: Passive — relies on server chassis fans (which R720/R730 have)
+- **Requirement**: Dual CPUs, redundant 1100W PSUs recommended
+- **Natively supported** in these servers
+
+### R720 vs R730
+- R720: PCIe Gen2 (not a bottleneck for LLM inference, which is VRAM-bound)
+- R730: PCIe Gen3, generally preferred
+- Both support up to 2x double-wide or 4x single-wide GPUs
+
+## Setup Options Analysis
+
+### Option A: P40 + A2000 (~$800)
+- P40 for LLM coding (24GB fits 14B models)
+- A2000 for image gen (3x faster than P40, tensor cores)
+- Total power: ~320W GPU
+- **Best performance split**
+
+### Option B: Single P40 (~$300)
+- Use for both LLM and image gen
+- 24GB handles 14B models well
+- Image gen slow but usable (~49s SDXL)
+- **Best budget option**, upgrade later
+
+### Option C: Dual P40 (~$600)
+- One dedicated to LLM, one to image gen
+- 500W total GPU power draw
+- Both need passive cooling (server fans handle this)
+- Image gen still slow on P40
+
+### Option D: P40 + P4 (~$350)
+- P40 for LLM (24GB)
+- P4 for light image gen (8GB, passive, 75W)
+- P4 limited to SD 1.5 and smaller models
+- Low total power: ~325W
+
+## Recommendations
+
+### Budget Priority (under $500): Single P40
+Start with one P40. Your local-ai stack auto-selects qwen2.5:14b at 24GB VRAM.
+Image gen works with `--force-fp32` flag. Add a second GPU later.
+
+### Performance Priority (~$800): P40 + A2000
+Best of both worlds. P40 handles LLM inference with full 24GB VRAM.
+A2000 handles image gen 3x faster with modern Ampere architecture.
+Both fit in R720/R730. A2000 blower cooling works well in rack.
+
+### Configuration Notes for local-ai stack
+- Set `INVOKEAI_PRECISION=float32` when using P40 for image gen
+- Ollama `OLLAMA_NUM_GPU=999` works with both GPUs
+- For dual GPU: assign specific GPUs via `CUDA_VISIBLE_DEVICES`
+- P40 needs `--force-fp32` in ComfyUI launch args
+
+## Sources
+- [NVIDIA RTX A2000 Datasheet](https://www.nvidia.com/content/dam/en-zz/Solutions/design-visualization/rtx-a2000/nvidia-rtx-a2000-datasheet-1987439-r5.pdf)
+- [Lenovo ThinkSystem RTX A2000 Product Guide](https://lenovopress.lenovo.com/lp1919-thinksystem-nvidia-rtx-a2000-12gb-pcie-active-gpu)
+- [n3rdware Single-Slot A2000 Cooler](https://n3rdware.com/gpu-coolers/single-slot-rtx-a2000-cooler)
+- [Dell R730 Owner's Manual - Expansion Cards](https://www.dell.com/support/manuals/en-us/poweredge-r730/r730_ompublication/expansion-card-installation-guidelines)
+- [Dell R720 Owner's Manual - Expansion Cards](https://www.dell.com/support/manuals/en-us/poweredge-r720/720720xdom/expansion-card-installation-guidelines)
+- [ComfyUI GPU Benchmarks Discussion](https://github.com/Comfy-Org/ComfyUI/discussions/2970)
+- [ComfyUI P40 FP32 Issue](https://github.com/Comfy-Org/ComfyUI/issues/4363)
+- [How to Use Tesla P40 Guide](https://github.com/JingShing/How-to-use-tesla-p40)
+- [Build a Local LLM Server Under $1000](https://sanj.dev/post/affordable-ai-hardware-local-llms)
+- [Best Budget GPUs for AI 2026](https://techtactician.com/best-budget-gpus-for-local-ai-workflows/)