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Description
Motivation.
FLUX.2-dev is a high-quality text-to-image model by Black Forest Labs. Following the successful integration in PR #1629, this RFC proposes acceleration feature support to improve inference efficiency and reduce deployment costs.
Current Status
Model Info:
- Name: FLUX.2-dev
- Source: https://huggingface.co/black-forest-labs/FLUX.2-dev
- Integration PR: #1629 (merged)
- Total Model Size: ~112.6 GB (Transformer ~64.3 GB + T5-XXL text encoder ~48.0 GB)
Currently Supported Features (from PR #1629):
| Feature | Status | Notes |
|---|---|---|
| Text-to-Image | ✅ Supported | 1024x1024 generation |
| Image-to-Image | ✅ Supported | Image editing capabilities |
| Tensor Parallel | ✅ Supported | TP=1 & cpu-offload, TP=2 & cpu-offload, TP=4 working |
Performance (from PR #1629):
| Config | GPU Memory | Peak Memory | Time per Image | Status |
|---|---|---|---|---|
| Diffusers (baseline) | - | 104.9s | ✅ | |
| TP=1 + CPU Offload | 66696MiB | 67352MiB | 89.8s | ✅ |
| TP=2 | 81112MiB | 81182MiB MiB | 39.1s | ✅ |
| TP=4 | 68160MiB | 81116MiB MiB | 29.1s | ✅ |
| TP=1 (no offload) | OOM | - | - | ❌ |
Proposed Acceleration Features
1. Model x Feature Matrix
Following the format from issue #1217, here's the acceleration feature roadmap for FLUX.2-dev:
| Feature | Priority | Status | Notes |
|---|---|---|---|
| ⚡TeaCache | P0 | ✅ https://github.com/vllm-project/vllm-omni/pull/1871 | Significant speedup potential |
| ⚡Cache-DiT | P0 | ✅ https://github.com/vllm-project/vllm-omni/pull/1814 | Alternative to TeaCache |
| 🔀SP (Ulysses & Ring) | P2 | ⏳ https://github.com/vllm-project/vllm-omni/pull/3244 | Sequence parallelism |
| 🔀CFG-Parallel | P0 | ✅ https://github.com/vllm-project/vllm-omni/pull/2010 | Verify compatibility |
| 🔀Tensor-Parallel | Done | ✅ https://github.com/vllm-project/vllm-omni/pull/1629 | TP=1 & cpu-offload, TP=2 & cpu-offload, TP=4 working |
| 💾VAE-Patch-Parallel | P1 | 🙋 Not supported | Reduce VAE memory pressure |
| 💾GGUF-Quantization | P1 | ⏳ https://github.com/vllm-project/vllm-omni/pull/3027 | Low-bit quantization |
2. Feature Priority Analysis
High Priority (P0):
- TeaCache / Cache-DiT
- CFG-Parallel
Medium Priority (P1):
- GGUF-Quantization
- VAE-Patch-Parallel
Low Priority (P2):
- Ulysses-SP
- Ring-SP
Proposed Change.
Please provide the detailed design document of the RFC using the template.
Feedback Period.
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CC List.
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Any Other Things.
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