Chat
SQwen 3 32B
This model is a direct match for chat. It belongs to a current frontier family for local AI. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.
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VOOZH | about |
NVIDIA
Operating mode
Use this to bias workload recommendations toward responsiveness, background autonomy, lighter serving, or multi-GPU scale-out.
Current mode
Balanced
Balanced for general local use. Keeps the ranking neutral across personal and serving workflows.
The NVIDIA H800 is a China-export-compliant variant of the H100, retaining the full Hopper compute capability โ 80 GB HBM3 and Transformer Engine with FP8 โ but with NVLink bandwidth cut to approximately 400 GB/s (down from H100's 900 GB/s) and FP64 performance capped at 1 TFLOPS. For single-GPU LLM inference, H800 performance is essentially identical to H100 SXM, making it highly effective for serving 70B models at FP16. The reduced NVLink bandwidth imposes a penalty for multi-GPU tensor parallelism in large training runs, which is why it was designed to be compliant. Like the A800, it was later banned under October 2023 export controls.
Beyond LLMs
What AI tasks this GPU can handle โ from text generation to image and video creation.
| Capability | Status | Representative Model | Detail |
|---|---|---|---|
| LLM Chat (7B) | Runs natively | Llama 3.1 8B Q4 | โ |
| LLM Coding (30B) | Runs natively | Qwen 3 30B Q4 | โ |
| LLM Large (70B) |
Architecture
Hopper is NVIDIA's datacenter-focused architecture succeeding Ampere. Built on TSMC 4N, it introduces the Transformer Engine with automatic FP8/FP16 mixed-precision training, HBM3/HBM3e memory, and NVLink 4.0 for multi-GPU scaling. The H100 flagship delivers up to 3x the AI training performance of A100.
AI Relevance
The Transformer Engine automatically manages FP8 precision for optimal training speed without accuracy loss. With up to 141 GB HBM3e (H200), Hopper GPUs can hold the largest open-weight models entirely in GPU memory, making them the workhorse of AI datacenters.
Chat
SThis model is a direct match for chat. It belongs to a current frontier family for local AI. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.
Coding
SThis model is a direct match for coding. It belongs to a current frontier family for local AI. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.
Agentic Coding
SThis model is still usable for agentic-coding, but it is not the most specialized pick. It belongs to a current frontier family for local AI. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.
Just out of reach
High-quality models that need a bit more memory
Image & Video Generation
51 of 52 models can generate images or video on your NVIDIA H800 80GB
| Model | Max Resolution | Gen Time | Grade |
|---|---|---|---|
| SD TurboImage | 512ร512 | 0ms | S |
| Stable Diffusion 1.5Image | 512ร768 | 100ms | S |
| Realistic Vision v5.1Image | 512ร768 | 100ms | S |
| DreamShaper 8Image | 512ร768 | 100ms | S |
| LCM DreamShaper v7 |
Multi-GPU scaling
Scale out with multiple GPUs for larger models. NVLink provides 400 GB/s inter-GPU bandwidth with 12% overhead.
| Config | Effective memory | Models that fit | Est. bandwidth |
|---|---|---|---|
| 1ร NVIDIA | 80 GB | 350/374 | 3,000 GB/s |
| 2ร NVIDIA | 160 GB | 359/374 | 5,280 GB/s |
| 4ร NVIDIA | 320 GB | 364/374 | 10,560 GB/s |
| 8ร NVIDIA | 640 GB | 373/374 | 21,120 GB/s |
Model counts use default quantization at coding workload settings. Multi-GPU scaling factor: 0.88ร per additional GPU.
Upgrade paths
See what you unlock with more powerful hardware
Upgrade options
Unlocks 23 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 119%.
NVLink gives this scale-out path a cleaner inter-GPU story than PCIe-only builds.
~$30,000 MSRP
Unlocks 1 additional models that do not fit on the current setup.
~$3,999 MSRP
Unlocks 1 additional models that do not fit on the current setup.
~$9,999 MSRP
Unlocks 13 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 26%.
~$20,000 MSRP
Unlocks 14 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 41%.
~$8,000 MSRP
Compare with similar
| Runs natively |
| Llama 3.1 70B Q4 |
| โ |
| Image Gen (SDXL) | Runs natively | SDXL 1.0 FP16 | ~300ms per image |
| Image Gen (Flux) | Runs natively | Flux.1 Dev FP16 | ~~1.5s per image |
| Image Gen (SD 3.5) | Runs natively | SD 3.5 Large FP16 | ~~1.9s per image |
| Video Short (25f) | Runs natively | LTX Video 2B | ~300ms/frame |
| Video Long (100f) | Runs with offload | Wan Video 14B | ~900ms/frame |
Reasoning
SThis model is a direct match for reasoning. It belongs to a current frontier family for local AI. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.
RAG
SThis model is a direct match for rag. It belongs to a current frontier family for local AI. It fits natively with comfortable headroom. Known channels: huggingface, ollama, lm-studio.
| 512ร768 |
| 0ms |
| S |
| PixArt-SigmaImage | 1024ร1024 | 300ms | S |
| FramePack I2VVideo | 1280ร720 | 600ms/frame | S |
| SDXL TurboImage | 512ร512 | 0ms | S |
| SDXL LightningImage | 1024ร1024 | 100ms | S |
| Stable Diffusion XL 1.0Image | 1024ร1024 | 300ms | S |
| Playground v2.5Image | 1024ร1024 | 500ms | S |
| RealVisXL v5.0Image | 1024ร1024 | 400ms | S |
| DreamShaper XLImage | 1024ร1024 | 400ms | S |
| Juggernaut XL v9Image | 1024ร1024 | 400ms | S |
| Animagine XL 3.1Image | 1024ร1024 | 400ms | S |
| Pony Diffusion V6 XLImage | 1024ร1024 | 400ms | S |
| Animagine XL 4.0Image | 1024ร1024 | 400ms | S |
| Illustrious XLImage | 1024ร1024 | 400ms | S |
| Wan Video 2.1 1.3BVideo | 480ร832 | 200ms/frame | S |
| Stable Diffusion 3.5 MediumImage | 1024ร1024 | 600ms | S |
| Flux.2 Klein 4BImage | 1024ร1024 | 100ms | S |
| LTX Video 2BVideo | 1280ร720 | 300ms/frame | S |
| KolorsImage | 1024ร1024 | 700ms | S |
| Stable CascadeImage | 1024ร1024 | 900ms | S |
| AuraFlow v0.3Image | 1536ร1536 | ~1.5s | S |
| Stable Diffusion 3.5 LargeImage | 1024ร1024 | ~1.9s | S |
| Stable Diffusion 3.5 Large TurboImage | 1024ร1024 | 300ms | S |
| CogVideoX 2BVideo | 720ร480 | 300ms/frame | S |
| HunyuanVideoVideo | 720ร1280 | 600ms/frame | S |
| ChromaImage | 1024ร1024 | 300ms | S |
| Z-Image TurboImage | 1536ร1536 | 400ms | S |
| Flux.1 DevImage | 1024ร1024 | ~1.5s | S |
| Flux.1 SchnellImage | 1024ร1024 | 300ms | S |
| LTX Video 13BVideo | 1280ร720 | 600ms/frame | S |
| Flux.1 Kontext DevImage | 1024ร1024 | ~1.7s | S |
| AnimateDiff v1.5.3Video | 512ร768 | 200ms/frame | S |
| Cosmos Diffusion 7BVideo | 1024ร576 | 500ms/frame | S |
| CogVideoX 5BVideo | 720ร480 | 400ms/frame | S |
| Wan2.2 TI2V 5BVideo | 832ร480 | 400ms/frame | S |
| Flux.2 Klein 9BImage | 1024ร1024 | 200ms | S |
| Flux.1 Fill DevImage | 1024ร1024 | ~1.5s | S |
| Mochi 1 PreviewVideo | 848ร480 | 600ms/frame | S |
| HunyuanVideo 1.5Video | 720ร1280 | 500ms/frame | S |
| Helios 14BVideo | 1280ร720 | 600ms/frame | S |
| SkyReels V2 14BVideo | 1280ร720 | 600ms/frame | S |
| Wan Video 2.1 14BVideo | 720ร1280 | 600ms/frame | S |
| Wan Video 2.2 14BVideo | 720ร1280 | 600ms/frame | S |
| Qwen ImageImage | 1024ร1024 | 600ms | S |
| Qwen Image EditImage | 1024ร1024 | 600ms | S |
| Flux.2 DevImage | 1024ร1024 | ~16.2s | S |
| MAGI-1Video | 1280ร720 | 800ms/frame | A |
| HunyuanImage 3.0Image | 256ร256 | ~1s | F |
Image models estimated at 1024ร1024 (28 steps, FP16). Video models estimated at 768ร512 (25 frames, 30 steps, FP16). Actual performance varies with runtime and system load.
There are 5 upgrade path(s) from NVIDIA H800 80GB: NVIDIA H800 80GB, Mac Studio M2 Ultra 128GB. Upgrading would unlock larger models and faster inference speeds.
Buying advice
Excellent choice for local AI
Runs 36 of 50 top models well โ a strong all-rounder for local inference.
80.0 GB
VRAM
$30,000
MSRP
$375/GB
Cost per GB VRAM
Best models for this GPU
What will limit you first
This setup is broadly balanced for this model.
No major red flags
This recommendation has enough memory headroom and acceptable estimated speed for the selected workload.
Best upgrade itinerary
Unlocks 1 additional models that do not fit on the current setup.
Want more headroom? Mac Studio M2 Ultra 128GB (128.0 GB unified memory) is the next step up.