Chat
SQwen 3 30B A3B
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.
AMD
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 Radeon Pro W7800 32GB is a high-end RDNA 3 workstation GPU with 32 GB of ECC GDDR6 VRAM and full workstation ROCm support. It competes with the NVIDIA RTX A6000 in positioning — targeting professional visualization and AI inference workloads where ECC and driver certification matter. The 32 GB enables 70B Q4 and 34B FP16 models, making it one of the more capable single-card local inference options in the AMD ecosystem.
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) | Won’t fit | 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) | Won't fit | Wan Video 14B |
Architecture
RDNA 3 is AMD's chiplet-based GPU architecture, combining a 5nm Graphics Compute Die (GCD) with 6nm Memory Cache Dies (MCDs). It introduces AI accelerators and a new unified compute unit design.
AI Relevance
ROCm support for RDNA 3 is maturing but lags behind NVIDIA's CUDA ecosystem. AI accelerator units provide some inference acceleration, but lack the dedicated Tensor Core equivalent found in NVIDIA GPUs.
Buying advice
Excellent choice for local AI
Runs 27 of 50 top models well — a strong all-rounder for local inference.
32.0 GB
VRAM
$2,499
MSRP
$78/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 11 additional models that do not fit on the current setup.
Want more headroom? MacBook Pro M1 Max 64GB (64.0 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 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 should run, but memory headroom will be limited. Known channels: huggingface, ollama, lm-studio.
Just out of reach
High-quality models that need a bit more memory
Image & Video Generation
43 of 52 models can generate images or video on your Radeon Pro W7800 32GB
| Model | Max Resolution | Gen Time | Grade |
|---|---|---|---|
| SD TurboImage | 512×512 | ~1.2s | S |
| Stable Diffusion 1.5Image | 512×768 | ~2.3s | S |
| Realistic Vision v5.1Image | 512×768 | ~2.3s | S |
| DreamShaper 8Image | 512×768 | ~2.3s | S |
| LCM DreamShaper v7Image | 512×768 | 700ms | S |
| PixArt-SigmaImage | 1024×1024 | ~9.4s | S |
| FramePack I2VVideo | 256×256 | ~17.2s/frame | S |
| SDXL TurboImage | 512×512 | ~1.2s | S |
| SDXL LightningImage | 1024×1024 | ~3.5s | S |
| Stable Diffusion XL 1.0Image | 1024×1024 | ~9.4s | S |
| Playground v2.5Image | 1024×1024 | ~14.1s | S |
| RealVisXL v5.0Image | 1024×1024 | ~10.6s | S |
| DreamShaper XLImage | 1024×1024 | ~10.6s | S |
| Juggernaut XL v9Image | 1024×1024 | ~10.6s | S |
| Animagine XL 3.1Image | 1024×1024 | ~10.6s | S |
| Pony Diffusion V6 XLImage | 1024×1024 | ~10.6s | S |
| Animagine XL 4.0Image | 1024×1024 | ~10.6s | S |
| Illustrious XLImage | 1024×1024 | ~10.6s | S |
| Wan Video 2.1 1.3BVideo | 480×832 | ~6.9s/frame | S |
| Stable Diffusion 3.5 MediumImage | 1024×1024 | ~16.4s | S |
| Flux.2 Klein 4BImage | 1024×1024 | ~2.8s | S |
| LTX Video 2BVideo | 1280×720 | ~8.2s/frame | S |
| KolorsImage | 1024×1024 | ~18.8s | S |
| Stable CascadeImage | 1024×1024 | ~23.5s | S |
| AuraFlow v0.3Image | 1536×1536 | ~42.3s | S |
| Stable Diffusion 3.5 LargeImage | 1024×1024 | ~51.6s | S |
| Stable Diffusion 3.5 Large TurboImage | 1024×1024 | ~9.4s | S |
| CogVideoX 2BVideo | 720×480 | ~8.2s/frame | S |
| HunyuanVideoVideo | 256×256 | ~17.2s/frame | S |
| ChromaImage | 1024×1024 | ~9.4s | S |
| Z-Image TurboImage | 1536×1536 | ~9.7s | S |
| Flux.1 DevImage | 256×256 | ~1m 14s | S |
| Flux.1 SchnellImage | 256×256 | ~14.4s | S |
| LTX Video 13BVideo | 256×256 | ~17.2s/frame | S |
| Flux.1 Kontext DevImage | 256×256 | ~1m 22s | S |
| AnimateDiff v1.5.3Video | 512×768 | ~4.3s/frame | S |
| Cosmos Diffusion 7BVideo | 1024×576 | ~13.5s/frame | A |
| CogVideoX 5BVideo | 720×480 | ~11.8s/frame | A |
| Wan2.2 TI2V 5BVideo | 832×480 | ~11.8s/frame | A |
| Flux.2 Klein 9BImage | 1024×1024 | ~4.7s | A |
| Flux.1 Fill DevImage | 256×256 | ~1m 10s | B |
| Mochi 1 PreviewVideo | 256×256 | ~27.9s/frame | D |
| HunyuanVideo 1.5Video | 256×256 | ~26.8s/frame | D |
| Helios 14BVideo | 256×256 | ~17.8s/frame | F |
| SkyReels V2 14BVideo | 256×256 | ~17.8s/frame | F |
| Wan Video 2.1 14BVideo | 256×256 | ~17.8s/frame | F |
| Wan Video 2.2 14BVideo | 256×256 | ~17.8s/frame | F |
| Qwen ImageImage | 256×256 | ~15.8s | F |
| Qwen Image EditImage | 256×256 | ~15.8s | F |
| Flux.2 DevImage | 256×256 | ~7m 24s | F |
| MAGI-1Video | 256×256 | ~22s/frame | F |
| HunyuanImage 3.0Image | 256×256 | ~27.8s | 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 11 additional models that do not fit on the current setup.
~$2,499 MSRP
Unlocks 13 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 26%.
~$3,999 MSRP
Unlocks 26 additional models that do not fit on the current setup.
~$2,499 MSRP
Unlocks 39 additional models that do not fit on the current setup.
Lifts average decode speed across fitting models by about 215%.
~$8,000 MSRP
Radeon Pro W7800 32GB (32 GB VRAM) can run these top models: Qwen3-Coder 30B A3B Instruct (score: 98/100), Qwen3-VL 30B A3B Instruct (score: 97/100), Qwen 3 30B A3B (score: 96/100). See the full compatibility list above.
Radeon Pro W7800 32GB has 32 GB of VRAM available for AI model inference. This determines which models and quantization levels you can run locally.
Yes, Radeon Pro W7800 32GB is excellent for running LLMs locally with top compatibility scores above 80/100.
For coding on Radeon Pro W7800 32GB, we recommend Qwen 3.6 27B. It achieves 16.9 tokens per second with 187K 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 4 upgrade path(s) from Radeon Pro W7800 32GB: MacBook Pro M1 Max 64GB, Radeon PRO W7900 DS 48GB. Upgrading would unlock larger models and faster inference speeds.
Yes, Radeon Pro W7800 32GB with 32 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.
Radeon Pro W7800 32GB (32 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.
Radeon Pro W7800 32GB is excellent for AI image generation. With 32 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, Radeon Pro W7800 32GB with 32 GB of usable memory can run Qwen 3.5 27B at Q4_K_M (~16.5 GB) with ~7 GB headroom for context and runtime. Quality at Q4 is very close to full precision for most tasks. Run it with: ollama run qwen3.5:27b
With 32 GB on Radeon Pro W7800 32GB, Q4_K_M is the sweet spot for 27B-35B models, Q6_K for 14B models, and Q8_0 for 8B-9B models. The general rule: use the highest quantization that fits with at least 2-3 GB headroom for KV cache and runtime.
Radeon Pro W7800 32GB has enough memory for many local LLMs, but bandwidth still matters a lot for real speed. Once a model fits, a faster-memory GPU can feel significantly better than a slower setup with similar capacity.
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