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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 A16 is a virtualization-oriented Ampere GPU that packages four GA107 GPU dies on a single card with a combined 64 GB of GDDR6 memory — 16 GB per die. It was designed for virtual workstation and virtual desktop infrastructure (VDI) use cases, but its aggregate 64 GB VRAM makes it usable for large-model inference when software supports multi-die configurations. Each GPU die is a modest chip, so raw FP16 compute (78 TFLOPS combined) is lower than dedicated inference GPUs. For teams already running A16 infrastructure for VDI, it can double as an AI inference host.
Beyond LLMs
What AI tasks this GPU can handle — from text generation to image and video creation.
| Capability | Status | Representative Model | Detail |
|---|---|---|---|
| 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 | ~~4.1s per image |
| Image Gen (Flux) | Runs natively | Flux.1 Dev FP16 | ~~18.4s per image |
| Image Gen (SD 3.5) | Runs natively | SD 3.5 Large FP16 | ~~22.5s per image |
| Video Short (25f) | Runs natively | LTX Video 2B | ~~3.6s/frame |
| Video Long (100f) | Very constrained | Wan Video 14B | ~~18s/frame |
Architecture
Ampere is NVIDIA's second-generation RTX architecture, built on Samsung's 8nm process. It introduced 3rd-generation Tensor Cores with support for sparsity-accelerated INT8 operations and improved FP16 throughput over Turing.
AI Relevance
Sparsity-aware Tensor Cores can effectively double throughput for structured sparse workloads. However, the lack of FP8 support means quantized inference is less efficient than Ada Lovelace or Blackwell.
Buying advice
Excellent choice for local AI
Runs 29 of 50 top models well — a strong all-rounder for local inference.
64.0 GB
VRAM
$6,500
MSRP
$102/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 M3 Ultra 96GB (96.0 GB unified memory) is the next step up.
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 should run, but memory headroom will be limited. 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 should run, but memory headroom will be limited. Known channels: huggingface, ollama, 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, 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.
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 A16 64GB
| Model | Max Resolution | Gen Time | Grade |
|---|---|---|---|
| SD TurboImage | 512×512 | 500ms | S |
| Stable Diffusion 1.5Image | 512×768 | ~1s | S |
| Realistic Vision v5.1Image | 512×768 | ~1s | S |
| DreamShaper 8Image | 512×768 | ~1s | S |
| LCM DreamShaper v7Image | 512×768 | 300ms | S |
| PixArt-SigmaImage | 1024×1024 | ~4.1s | S |
| FramePack I2VVideo | 1280×720 | ~7.5s/frame | S |
| SDXL TurboImage | 512×512 | 500ms | S |
| SDXL LightningImage | 1024×1024 | ~1.5s | S |
| Stable Diffusion XL 1.0Image | 1024×1024 | ~4.1s | S |
| Playground v2.5Image | 1024×1024 | ~6.1s | S |
| RealVisXL v5.0Image | 1024×1024 | ~4.6s | S |
| DreamShaper XLImage | 1024×1024 | ~4.6s | S |
| Juggernaut XL v9Image | 1024×1024 | ~4.6s | S |
| Animagine XL 3.1Image | 1024×1024 | ~4.6s | S |
| Pony Diffusion V6 XLImage | 1024×1024 | ~4.6s | S |
| Animagine XL 4.0Image | 1024×1024 | ~4.6s | S |
| Illustrious XLImage | 1024×1024 | ~4.6s | S |
| Wan Video 2.1 1.3BVideo | 480×832 | ~3s/frame | S |
| Stable Diffusion 3.5 MediumImage | 1024×1024 | ~7.2s | S |
| Flux.2 Klein 4BImage | 1024×1024 | ~1.2s | S |
| LTX Video 2BVideo | 1280×720 | ~3.6s/frame | S |
| KolorsImage | 1024×1024 | ~8.2s | S |
| Stable CascadeImage | 1024×1024 | ~10.2s | S |
| AuraFlow v0.3Image | 1536×1536 | ~18.4s | S |
| Stable Diffusion 3.5 LargeImage | 1024×1024 | ~22.5s | S |
| Stable Diffusion 3.5 Large TurboImage | 1024×1024 | ~4.1s | S |
| CogVideoX 2BVideo | 720×480 | ~3.6s/frame | S |
| HunyuanVideoVideo | 720×1280 | ~7.5s/frame | S |
| ChromaImage | 1024×1024 | ~4.1s | S |
| Z-Image TurboImage | 1536×1536 | ~4.2s | S |
| Flux.1 DevImage | 1024×1024 | ~18.4s | S |
| Flux.1 SchnellImage | 1024×1024 | ~3.6s | S |
| LTX Video 13BVideo | 1280×720 | ~7.5s/frame | S |
| Flux.1 Kontext DevImage | 1024×1024 | ~20.5s | S |
| AnimateDiff v1.5.3Video | 512×768 | ~1.9s/frame | S |
| Cosmos Diffusion 7BVideo | 1024×576 | ~5.9s/frame | S |
| CogVideoX 5BVideo | 720×480 | ~5.1s/frame | S |
| Wan2.2 TI2V 5BVideo | 832×480 | ~5.1s/frame | S |
| Flux.2 Klein 9BImage | 1024×1024 | ~2s | S |
| Flux.1 Fill DevImage | 1024×1024 | ~17.4s | S |
| Mochi 1 PreviewVideo | 848×480 | ~6.8s/frame | S |
| HunyuanVideo 1.5Video | 720×1280 | ~6.3s/frame | S |
| Helios 14BVideo | 1280×720 | ~7.7s/frame | S |
| SkyReels V2 14BVideo | 1280×720 | ~7.7s/frame | S |
| Wan Video 2.1 14BVideo | 480×832 | ~7.7s/frame | A |
| Wan Video 2.2 14BVideo | 480×832 | ~7.7s/frame | A |
| Qwen ImageImage | 1024×1024 | ~6.9s | B |
| Qwen Image EditImage | 1024×1024 | ~6.9s | B |
| Flux.2 DevImage | 256×256 | ~3m 14s | B |
| MAGI-1Video | 256×256 | ~15.6s/frame | B |
| HunyuanImage 3.0Image | 256×256 | ~12.1s | F |
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
Upgrade options
Unlocks 1 additional models that do not fit on the current setup.
~$3,999 MSRP
Unlocks 7 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 98%.
~$40,000 MSRP
Unlocks 8 additional models that do not fit on the current setup.
~$2,499 MSRP
Unlocks 21 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 164%.
~$8,000 MSRP
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