ComfyUI & Local AI GPU / VRAM Calculator
Calculate exact VRAM requirements (FP16, FP8, GGUF Q4) and compare hourly cloud GPU costs across RunPod, Vast.ai, and AWS for Flux.1, Wan 2.1, SDXL, LTX-Video, and HunyuanVideo.
ComfyUI Pipeline Parameters
FP8 preserves 98%+ fidelity while cutting weight VRAM by nearly 45%.
24GB VRAM Tier
Target: RTX 3090 / RTX 4090
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Vsurge Media builds private, auto-scaling ComfyUI API clusters on RunPod & Vast.ai with zero idle cloud waste.
Book Free AI Pipeline AuditCloud GPU Compatibility & Pricing Matrix
Live rates for 60 hours/month running Flux.1 Dev (12B) (FP8)
| GPU Model & Architecture | VRAM | Compatibility | RunPod Rate | Vast.ai Rate | AWS EC2 Rate | Est. Monthly (60h) | Cost / 100 Gens |
|---|---|---|---|---|---|---|---|
NVIDIA RTX 3060Ampere | 12 GB | OOM Risk (-5.8 GB) | $0.19/hr | $0.12/hr | N/A (Consumer) | $11.40Vast: $7.20 | $—~40.0s / gen |
NVIDIA RTX 4070 Ti SuperAda Lovelace | 16 GB | OOM Risk (-1.8 GB) | $0.29/hr | $0.20/hr | N/A (Consumer) | $17.40Vast: $12.00 | $—~20.6s / gen |
NVIDIA RTX 3090Ampere | 24 GB | Fits (+6.2 GB) | $0.34/hr | $0.22/hr | N/A (Consumer) | $20.40Vast: $13.20 | $0.203~21.5s / gen |
NVIDIA RTX 4090Ada Lovelace | 24 GB | Fits (+6.2 GB) | $0.69/hr | $0.44/hr | N/A (Consumer) | $41.40Vast: $26.40 | $0.268~14.0s / gen |
NVIDIA RTX 5090Blackwell | 32 GB | Fits (+14.2 GB) | $1.19/hr | $0.85/hr | N/A (Consumer) | $71.40Vast: $51.00 | $0.321~9.7s / gen |
NVIDIA RTX A6000Ampere Workstation | 48 GB | Fits (+30.2 GB) | $0.79/hr | $0.55/hr | $1.85/hr | $47.40Vast: $33.00 | $0.384~17.5s / gen |
NVIDIA L40SAda Lovelace Datacenter | 48 GB | Fits (+30.2 GB) | $1.09/hr | $0.82/hr | $2.24/hr | $65.40Vast: $49.20 | $0.369~12.2s / gen |
NVIDIA A100 SXMAmpere Datacenter | 80 GB | Fits (+62.2 GB) | $1.89/hr | $1.39/hr | $4.10/hr | $113.40Vast: $83.40 | $0.546~10.4s / gen |
NVIDIA H100 SXMHopper Datacenter | 80 GB | Fits (+62.2 GB) | $2.99/hr | $2.25/hr | $6.80/hr | $179.40Vast: $135.00 | $0.482~5.8s / gen |
Hardware & Workflow Specific Presets
Jump straight into pre-calculated VRAM and cloud cost configurations:
Flux.1 Dev VRAM & Cloud GPU Cost Calculator (24GB vs 16GB)
Calculate exact VRAM requirements for Flux.1 Dev (FP16, FP8, GGUF Q4) with LoRA & ControlNet. Compare RunPod vs Vast.ai cloud costs for 24GB vs 16GB GPUs.
Wan 2.1 Video Generation VRAM & RunPod GPU Calculator
Plan VRAM and calculate RunPod vs Vast.ai rental fees for Wan 2.1 14B text-to-video in ComfyUI. Avoid OOM crashes with FP8 and GGUF quantizations.
SDXL 1.0 ComfyUI VRAM Calculator for 12GB & 16GB GPUs
Calculate ComfyUI VRAM usage for SDXL 1.0 on budget 12GB RTX 3060 and 16GB RTX 4070 Ti GPUs with multi-ControlNet and LoRA stacks.
LTX-Video ComfyUI VRAM & Realtime GPU Cost Calculator
Realtime AI video generation VRAM calculator for Lightricks LTX-Video (2B). Compare RunPod, Vast.ai, and local GPU performance.
HunyuanVideo 13B ComfyUI VRAM & Cloud GPU Pricing Calculator
Calculate GPU VRAM and cloud rental expenses for Tencent HunyuanVideo (13B). Compare FP16, FP8, and GGUF quantizations on RunPod and Vast.ai.
Engineering Insights & VRAM Allocation Guide
Accurate VRAM planning is the difference between seamless batch generation and catastrophic CUDA OOM driver restarts. Below are benchmarked principles for local and cloud ComfyUI pipelines.
How much VRAM does Flux.1 Dev require in ComfyUI?
In native uncompressed FP16, Flux.1 Dev (12B) requires 24GB VRAM just for weights, causing instant CUDA Out-of-Memory crashes on 16GB cards when conditioning or latent buffers are loaded. By running Flux.1 in FP8, weights reduce to ~13.5GB, allowing comfortable execution on 16GB GPUs (such as RTX 4070 Ti Super or RTX 4080) and zero-swap performance on 24GB GPUs (RTX 3090/4090).
What is the real difference between FP16, FP8, and GGUF Q4?
FP16 provides 100% full precision without weight compression. FP8 quantizes weights down to 8 bits, retaining over 98.5% visual fidelity and text coherence while cutting VRAM weight consumption by roughly 45%. GGUF Q4 (or bitsandbytes 4-bit) further reduces weight footprints down to 8–11GB, making large video and image models operable on budget 12GB GPUs with a slight trade-off in micro-texture sharpness.
Is Vast.ai or RunPod cheaper for running ComfyUI production workloads?
Vast.ai offers peer-to-peer community instances that are typically 30%–45% cheaper than RunPod (e.g., RTX 4090 at ~$0.44/hr vs $0.69/hr). However, RunPod Secure Cloud provides verified Tier-3/Tier-4 datacenter uptime, symmetrical 10Gbps fiber, and persistent network storage volumes. For production APIs, RunPod or Lambda Labs are recommended; for personal development or batch rendering, Vast.ai provides unmatched cost-efficiency.
Can I generate video using Wan 2.1 or HunyuanVideo on a single consumer GPU?
Yes, provided you utilize FP8 or GGUF quantization. Wan 2.1 (14B) and HunyuanVideo (13B) natively exceed 28GB–32GB in FP16. In FP8 with lightweight latent caching, Wan 2.1 requires ~17.5GB–22GB total VRAM, running smoothly on an RTX 4090 (24GB) or RTX 5090 (32GB) without CPU memory swapping.
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