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 H100 NVL is a unique dual-H100 card that fuses two H100 GPUs on a single PCIe Gen5 board, delivering 188 GB of HBM3 and 7.8 TB/s of combined bandwidth. The two GPUs are connected by three NVLink 4 bridges at 600 GB/s bidirectional, enabling them to act as a unified pool for large model inference. It is the highest-VRAM Hopper option available in a PCIe form factor, capable of running 70B models at FP16 with substantial KV cache and approaching 405B models at Q4. Benchmarks show up to 12x improvement over A100 systems for GPT-175B inference.
Beyond LLMs
What AI tasks this GPU can handle — from text generation to image and video creation.
| Capability | Status | Representative Model |
|---|---|---|
| LLM Chat (7B) | Runs natively | Llama 3.1 8B Q4 |
| LLM Coding (30B) | Runs natively | Qwen 3 30B Q4 |
| LLM Large (70B) | Runs natively | Llama 3.1 70B Q4 |
| Image Gen (SDXL) | Runs natively | SDXL 1.0 FP16 |
| Image Gen (Flux) | Runs natively | Flux.1 Dev FP16 |
| Image Gen (SD 3.5) | Runs natively | SD 3.5 Large FP16 |
| Video Short (25f) | Runs natively | LTX Video 2B |
| Video Long (100f) | Runs natively | Wan Video 14B |
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.
購入アドバイス
ローカルAIに最適な選択
上位50モデル中40モデルを快適に実行 — ローカル推論の万能選手です。
188.0 GB
VRAM
$60,000
希望小売価格
$319/GB
GBあたりのコスト
このGPUに最適なモデル
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 4 additional models that do not fit on the current setup.
もっと余裕が欲しいですか？ AMD Instinct MI325X 256GB (256.0 GB VRAM) が次のステップアップです。
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, 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, 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, lm-studio.
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, 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, lm-studio.
Devstral 2 123B Instruct
DeepSeek V4 Flash
Qwen 3.5 122B A10BMistral Small 4 119B
GPT-OSS 120BPixtral Large 124B
Command A 111BQwen 3 235B A22BQwen 2.5 VL 72BQwen3-Coder-NextQwen3-Coder 30B A3B InstructLeanstral 119B A6BQwen 3.6 35B A3BQwen 3.5 27BQwen3-VL 30B A3B InstructQwen 3.6 27BQwen 3.5 35B A3BQwen 3 32BMagistral Small 2507Devstral Small 2 24B InstructQwen 3 30B A3BQwen 3.5 9BNemotron 3 Nano 30BQwen 3 14BDevstral Small 1.1
Phi-4-reasoning-plus 14BQwen 3 8B
Gemma 4 31BGPT-OSS 20BNemotron Cascade 2 30B A3BQwen 3.5 4B
EXAONE 4.0 32BGemma 4 26B A4BMinistral 3 14BNemotron Nano 8BPhi-4 Mini Reasoning 4B
Jina Embeddings v3DeepSeek Coder V2 236B
BGE M3Qwen 3.5 397B A17B
Kimi K2.5Kimi K2.6DeepSeek V4 Pro
GLM-5.1GLM-5DeepSeek V3.2Qwen3-Coder 480B A35B InstructDeepSeek R1 671BDeepSeek V3.1 671Bもう少しで届く
もう少しメモリがあれば動く高品質モデル
Image & Video Generation
52 of 52 models can generate images or video on your H100 NVL 188GB
| Model | Max Resolution | Gen Time | Grade |
|---|---|---|---|
| SD TurboImage | 512×512 | 0ms | S |
| Stable Diffusion 1.5Image | 512×768 | 0ms | S |
| Realistic Vision v5.1Image | 512×768 | 0ms | S |
| DreamShaper 8Image | 512×768 | 0ms | S |
| LCM DreamShaper v7Image | 512×768 | 0ms | S |
| PixArt-SigmaImage | 1024×1024 | 200ms | S |
| FramePack I2VVideo | 1280×720 | 300ms/frame | S |
| SDXL TurboImage | 512×512 | 0ms | S |
| SDXL LightningImage | 1024×1024 | 100ms | S |
| Stable Diffusion XL 1.0Image | 1024×1024 | 200ms | S |
| Playground v2.5Image | 1024×1024 | 200ms | S |
| RealVisXL v5.0Image | 1024×1024 | 200ms | S |
| DreamShaper XLImage | 1024×1024 | 200ms | S |
| Juggernaut XL v9Image | 1024×1024 | 200ms | S |
| Animagine XL 3.1Image | 1024×1024 | 200ms | S |
| Pony Diffusion V6 XLImage | 1024×1024 | 200ms | S |
| Animagine XL 4.0Image | 1024×1024 | 200ms | S |
| Illustrious XLImage | 1024×1024 | 200ms | S |
| Wan Video 2.1 1.3BVideo | 480×832 | 100ms/frame | S |
| Stable Diffusion 3.5 MediumImage | 1024×1024 | 300ms | S |
| Flux.2 Klein 4BImage | 1024×1024 | 0ms | S |
| LTX Video 2BVideo | 1280×720 | 100ms/frame | S |
| KolorsImage | 1024×1024 | 300ms | S |
| Stable CascadeImage | 1024×1024 | 400ms | S |
| AuraFlow v0.3Image | 1536×1536 | 700ms | S |
| Stable Diffusion 3.5 LargeImage | 1024×1024 | 900ms | S |
| Stable Diffusion 3.5 Large TurboImage | 1024×1024 | 200ms | S |
| CogVideoX 2BVideo | 720×480 | 100ms/frame | S |
| HunyuanVideoVideo | 720×1280 | 300ms/frame | S |
| ChromaImage | 1024×1024 | 200ms | S |
| Z-Image TurboImage | 1536×1536 | 200ms | S |
| Flux.1 DevImage | 1024×1024 | 700ms | S |
| Flux.1 SchnellImage | 1024×1024 | 100ms | S |
| LTX Video 13BVideo | 1280×720 | 300ms/frame | S |
| Flux.1 Kontext DevImage | 1024×1024 | 800ms | S |
| AnimateDiff v1.5.3Video | 512×768 | 100ms/frame | S |
| Cosmos Diffusion 7BVideo | 1024×576 | 200ms/frame | S |
| CogVideoX 5BVideo | 720×480 | 200ms/frame | S |
| Wan2.2 TI2V 5BVideo | 832×480 | 200ms/frame | S |
| Flux.2 Klein 9BImage | 1024×1024 | 100ms | S |
| Flux.1 Fill DevImage | 1024×1024 | 700ms | S |
| Mochi 1 PreviewVideo | 848×480 | 300ms/frame | S |
| HunyuanVideo 1.5Video | 720×1280 | 200ms/frame | S |
| Helios 14BVideo | 1280×720 | 300ms/frame | S |
| SkyReels V2 14BVideo | 1280×720 | 300ms/frame | S |
| Wan Video 2.1 14BVideo | 720×1280 | 300ms/frame | S |
| Wan Video 2.2 14BVideo | 720×1280 | 300ms/frame | S |
| Qwen ImageImage | 1024×1024 | 300ms | S |
| Qwen Image EditImage | 1024×1024 | 300ms | S |
| Flux.2 DevImage | 1024×1024 | ~7.4s | S |
| MAGI-1Video | 1280×720 | 400ms/frame | S |
| HunyuanImage 3.0Image | 1024×1024 | 500ms | B |
Image models estimated at 1024×1024 (28 steps, FP16). Video models estimated at 768×512 (25 frames, 30 steps, FP16). Actual performance varies with runtime and system load.
Upgrade paths
See what you unlock with more powerful hardware
アップグレードオプション
Unlocks 4 additional models that do not fit on the current setup.
〜$20,000 MSRP
Unlocks 5 additional models that do not fit on the current setup.
〜$8,000 MSRP
H100 NVL 188GB (188 GB VRAM) can run these top models: Devstral 2 123B Instruct (score: 96/100), DeepSeek V4 Flash (score: 96/100), Qwen 3.5 122B A10B (score: 95/100). See the full compatibility list above.
H100 NVL 188GB has 188 GB of VRAM available for AI model inference. This determines which models and quantization levels you can run locally.
Yes, H100 NVL 188GB is excellent for running LLMs locally with top compatibility scores above 80/100.
For coding on H100 NVL 188GB, we recommend Devstral 2 123B Instruct. It achieves 91.6 tokens per second with 256K context window. This 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, lm-studio.
There are 2 upgrade path(s) from H100 NVL 188GB: AMD Instinct MI325X 256GB, AMD Instinct MI350X 288GB. Upgrading would unlock larger models and faster inference speeds.
Yes, H100 NVL 188GB with 188 GB of usable memory can run Flux.1 Dev at FP16 natively. Flux is a 12B parameter diffusion transformer that produces high-quality images. You can also run the Schnell variant for faster generation.
H100 NVL 188GB (188 GB VRAM) can handle various AI generation tasks beyond LLMs. For image generation, SDXL and Stable Diffusion 3.5 run well. Flux.1 Dev also runs natively for state-of-the-art image quality. For video, LTX Video 2.3 can generate short clips. Check the AI Capability Matrix above for detailed compatibility.
H100 NVL 188GB is excellent for AI image generation. With 188 GB of usable memory, it runs all major diffusion models including Flux.1, SDXL, and Stable Diffusion 3.5 at full precision. You can generate high-resolution images quickly and even handle video generation models.
Yes, H100 NVL 188GB with 188 GB of usable memory can run Qwen 3.5 27B at Q8 (near-lossless, ~28.9 GB) or even FP16 (~55.4 GB) depending on your context needs. This setup provides an excellent experience with this model. Use Ollama or vLLM for best results.
With 188 GB VRAM on H100 NVL 188GB, use Q8_0 for most models — it is near-lossless and you have the memory for it. For 70B+ models, Q6_K offers excellent quality. Reserve Q4_K_M for 100B+ models or when you need maximum context length.
H100 NVL 188GB already has strong memory bandwidth, so the next limit is often memory capacity and context headroom rather than raw decode speed. For local LLMs, fit first and bandwidth second is the right mental model.
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