Best larger-system route
Team 32
The smallest system in the range that reaches this model's preferred working allowance.
Explore Team 32Tencent model
HunyuanVideo 1.5 Hardware Requirements & Fit
Tencent documents a 14GB minimum with model offloading. Every product clears that floor. Team 32 is suitable for a pilot; larger single-GPU products reduce offload pressure and can support more demanding quality or queue targets.
- Model version
tencent/HunyuanVideo-1.5- Family and variant
- HunyuanVideo 1.5 · HunyuanVideo-1.5
- Source version
9b49404b3f5d- Source updated
- 25 December 2025
Tencent HunyuanVideo 1.5
tencent/HunyuanVideo-1.5 - Minimum GPU memory
- 14GB VRAM with model offloading
- Recommended hardware
- 32GB or more for a less constrained pilot
- Licence
- Tencent Hunyuan Community Licence
- Useful for
- Video generation
Buyer verdict
Where HunyuanVideo 1.5 is a sensible fit
HunyuanVideo 1.5 suits local creative and research teams that need both text-to-video and image-to-video, 480p or 720p generation and a documented consumer-GPU route.
These figures apply to the named model version. Quantisation, fine-tuning, context length, image resolution, batch size and serving software can materially change the hardware needed.
Hardware requirements
- Minimum
- 14GB VRAM with model offloading
- Recommended
- 32GB or more for a less constrained pilot
Tencent states this measured minimum and notes additional CPU-memory use.
Higher resolution, no-offload operation and queues may justify 96GB or several workers.
Technical specification
HunyuanVideo 1.5 model and hardware facts
Specifications shown for source version
9b49404b3f5df2a8f0b31df27a0c7ab872e7b038, updated
25 December 2025.
- Parameters
- 8.3B
- Tasks
- Text-to-video + image-to-video
- Official minimum
- 14GB VRAM with offloading
- Resolution
- 480p or 720p, optional 1080p SR
- Default length
- 121 frames
- Licence
- Tencent Hunyuan Community
Product compatibility
HunyuanVideo 1.5 compatibility across all 11 GPU systems
- Systems that fit without model splitting
- 11
- Systems needing multi-GPU validation
- 0
A system is listed as fitting when its GPU memory meets the requirement shown above. Speed, usable context, batch size and concurrent users still need testing with the final model and software configuration.
sme workstation
Team 32
- Per GPU
- 32GB
- Total GPU memory
- 32GB
- GPU count
- 1
Also meets this model page's recommended working allowance.
Available GPU memory exceeds the model developer's published requirement. Confirm speed, context, batch size and concurrent users before purchase.
sme workstation
Company 64
- Per GPU
- 32GB
- Total GPU memory
- 64GB
- GPU count
- 2
Also meets this model page's recommended working allowance.
Available GPU memory exceeds the model developer's published requirement. Confirm speed, context, batch size and concurrent users before purchase.
sme workstation
Studio 96
- Per GPU
- 96GB
- Total GPU memory
- 96GB
- GPU count
- 1
Also meets this model page's recommended working allowance.
Available GPU memory exceeds the model developer's published requirement. Confirm speed, context, batch size and concurrent users before purchase.
sme workstation
Studio 192
- Per GPU
- 96GB
- Total GPU memory
- 192GB
- GPU count
- 2
Also meets this model page's recommended working allowance.
Available GPU memory exceeds the model developer's published requirement. Confirm speed, context, batch size and concurrent users before purchase.
pcie rack
Value Rack 128
- Per GPU
- 32GB
- Total GPU memory
- 128GB
- GPU count
- 4
Also meets this model page's recommended working allowance.
Available GPU memory exceeds the model developer's published requirement. Confirm speed, context, batch size and concurrent users before purchase.
pcie rack
Value Rack 256
- Per GPU
- 32GB
- Total GPU memory
- 256GB
- GPU count
- 8
Also meets this model page's recommended working allowance.
Available GPU memory exceeds the model developer's published requirement. Confirm speed, context, batch size and concurrent users before purchase.
pcie rack
Enterprise 384
- Per GPU
- 96GB
- Total GPU memory
- 384GB
- GPU count
- 4
Also meets this model page's recommended working allowance.
Available GPU memory exceeds the model developer's published requirement. Confirm speed, context, batch size and concurrent users before purchase.
pcie rack
Enterprise 768
- Per GPU
- 96GB
- Total GPU memory
- 768GB
- GPU count
- 8
Also meets this model page's recommended working allowance.
Available GPU memory exceeds the model developer's published requirement. Confirm speed, context, batch size and concurrent users before purchase.
pcie rack
H200 1.1TB
- Per GPU
- 141GB
- Total GPU memory
- 1,128GB
- GPU count
- 8
Also meets this model page's recommended working allowance.
Available GPU memory exceeds the model developer's published requirement. Confirm speed, context, batch size and concurrent users before purchase.
frontier partner
Frontier Native 2.3TB
- Per GPU
- 288GB
- Total GPU memory
- 2,304GB
- GPU count
- 8
Also meets this model page's recommended working allowance.
Available GPU memory exceeds the model developer's published requirement. Confirm speed, context, batch size and concurrent users before purchase.
frontier partner
Frontier Rack 20TB
- Per GPU
- 288GB
- Total GPU memory
- 20,736GB
- GPU count
- 72
Also meets this model page's recommended working allowance.
Available GPU memory exceeds the model developer's published requirement. Confirm speed, context, batch size and concurrent users before purchase.
Deployment reality
Strengths, limits and runtime route
What it is good at
- Official 14GB minimum with offloading.
- 8.3B architecture, substantially smaller than the original HunyuanVideo release.
- 480p and 720p workflows with optional 1080p super-resolution.
- Distilled 8 or 12-step 480p image-to-video option.
Where to be cautious
- The low-memory route increases CPU-memory demand and can reduce speed.
- Prompt rewriting may call a separate model or external endpoint unless disabled.
- The Tencent community licence needs review for the intended commercial use.
- Generation quality and speed vary materially by resolution, steps, offload and attention backend.
Serving software
- HunyuanVideo 1.5 reference code
- Diffusers
- ComfyUI
- LightX2V
Before installation
- Decide whether prompt rewriting is local, external or disabled before handling sensitive inputs.
- Record resolution, 121-frame default, steps, super-resolution, batch, latency and peak VRAM.
- For the 14GB route, record CPU RAM and offload settings as well as GPU memory.
- Use the exact T2V or I2V checkpoint and distilled variant in the workload test.
System requirements
- GPU layout
- The minimum can fit on one GPU; multiple GPUs may still be useful for replicas or throughput.
- Context and cache
- The model context ceiling is not a guaranteed serving target. KV cache, batch size and concurrent sessions need separate capacity tests.
- System RAM
- Size system memory for model loading, runtime overhead, preprocessing and any CPU offload used by the final configuration.
- Storage
- Allow space for the pinned checkpoint, runtime images, caches, logs and at least one rollback version.
- Serving software
- Validate the exact checkpoint with HunyuanVideo 1.5 reference code, Diffusers, ComfyUI, LightX2V before acceptance.
- Representative workload
- Benchmark representative prompts or media at the required context, quality, latency and concurrency.
Performance: speed, usable context and concurrency depend on the selected system, software and workload. No benchmark is quoted on this page.
Commercial and legal boundary
Tencent Hunyuan Community Licence
Commercial use: conditional
Review Tencent's model-specific licence and any use-scale or territory conditions before commercial deployment.
Always retain the applicable notices and recheck the live terms for the intended organisation, territory, use and distribution route. Obtain legal advice where required; the official licence governs use.
Read the official licenceTechnical questions
HunyuanVideo 1.5 deployment FAQ
Can Team 32 run HunyuanVideo 1.5?
Yes by the published memory requirement. Its 32GB GPU exceeds Tencent's 14GB offload minimum, but speed and CPU-memory use still need measurement.
Does it generate 1080p directly?
The documented workflow generates 480p or 720p and can apply a separate super-resolution stage to reach 1080p.
Does prompt rewriting send data outside the server?
It can if configured to use an external endpoint. The deployment must make the rewrite route explicit or disable it.
What a complete HunyuanVideo 1.5 deployment needs
GPU memory is only one part of the system. Storage, data access, serving software, monitoring and administrator handover also affect a reliable deployment.
