Can I Run HunyuanVideo 13B on RTX 5060 Ti 16GB? GGUF & TeaCache Sizing
Model weights, initial KV-cache, and CUDA context buffers.
Available safety margin for OS compositing and context expansion.
Throughput determined by memory bus bandwidth.
Hardware Physics & Bottleneck Analysis
Tencent HunyuanVideo 13B combines 20 dual-stream MMDiT blocks and 40 single-stream transformer blocks with a heavyweight multimodal text encoder (`llava-llama-3-8b-v1_1` taking ~8.5 GB in FP8) and `CLIP-ViT-L/14`, followed by a 3D CausalConv VAE. On a 16GB RTX 5060 Ti, attempting to keep the 8B LLaVA text encoder and 13B DiT resident simultaneously triggers an immediate allocation overflow. However, ComfyUI's GGUF loader (`hunyuan-video-t2v-720p-Q4_K_M.gguf`, `~7.9 GB` weights) stages the 8B LLaVA encoder in VRAM first, computes prompt embeddings, purges the encoder back to system DDR5 RAM, and then streams the 13B quantized DiT across the RTX 5060 Ti's 448 GB/s GDDR7 bus alongside a 4.2 GB spatio-temporal activation workspace.
Use `ComfyUI-GGUF` with `hunyuan-video-t2v-720p-Q4_K_M.gguf`, wire `HunyuanVideo TeaCache` (`rel_l1_thresh = 0.16` for a `2.1x` speedup), and always route latents through `VAE Decode (Tiled)` with `tile_size = 256` so 544x960 or 720p 61-frame renders never exceed 14.6 GB VRAM.
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Frequently Asked Questions
Can an 8GB RTX 5060 Ti or 12GB RTX 5070 run HunyuanVideo 13B smoothly?
An 8GB card fails or stalls at <0.02 steps/sec due to heavy PCIe thrashing. A 12GB card requires offloading 15–20 transformer blocks to system RAM on every step, making the 16GB RTX 5060 Ti significantly faster despite fewer raw CUDA cores.
How much system DDR5 RAM do I need alongside an RTX 5060 Ti 16GB for HunyuanVideo?
At least 32GB of system DDR5 RAM (64GB recommended) is required because ComfyUI offloads the ~8.5 GB LLaVA-Llama-3 text encoder and 3D VAE weights into host memory while the 16GB GPU executes the 13B DiT denoising pass.
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