Best AI Models for AMD Radeon PRO W7800 (32.0GB)
32 GB positions this hardware in the professional tier for local AI. Most popular open-source models run comfortably, and even large 70B parameter models are accessible at lower quantization levels.
This memory amount is a sweet spot for enthusiasts and professionals. You can run 13B–30B models like DeepSeek R1 Distill at Q5 or Q6 quality with smooth token generation, and 7B models at near-lossless precision. The 70B class of models (Llama 3 70B, Qwen 72B) becomes possible at Q2–Q3 quantization, though with some quality trade-off. For day-to-day use with coding assistants, chat models, and reasoning tasks, this tier delivers an excellent experience.
Runs Well
- 7B–13B models at Q6–Q8 quality
- 14B–30B models at Q4–Q5 quality
- Small models (3B–7B) at FP16 precision
- Vision-language models at good quality
Challenging
- 70B models only at Q2–Q3 (noticeable quality loss)
- Large context windows with 30B+ models
What LLMs Can AMD Radeon PRO W7800 Run?
29 models · 7 good
Showing compatibility for AMD Radeon PRO W7800
| Model | Quant | VRAM | Speed | Context | Status | Grade |
|---|---|---|---|---|---|---|
Q4_K_M·15.5 t/s tok/s·131K ctx·GOOD FIT | Q4_K_M | 20.5 GB | 15.5 t/s | 131K | GOOD FIT | A81 |
Q4_K_M·16.0 t/s tok/s·41K ctx·GOOD FIT | Q4_K_M | 19.8 GB | 16.0 t/s | 41K | GOOD FIT | A78 |
Q4_K_M·15.5 t/s tok/s·33K ctx·GOOD FIT | Q4_K_M | 20.5 GB | 15.5 t/s | 33K | GOOD FIT | A81 |
Q4_K_M·14.8 t/s tok/s·4K ctx·GOOD FIT | Q4_K_M | 21.4 GB | 14.8 t/s | 4K | GOOD FIT | A84 |
Q4_K_M·15.8 t/s tok/s·41K ctx·GOOD FIT | Q4_K_M | 20.0 GB | 15.8 t/s | 41K | GOOD FIT | A80 |
Q4_K_M·17.5 t/s tok/s·131K ctx·GOOD FIT | Q4_K_M | 18.1 GB | 17.5 t/s | 131K | GOOD FIT | A72 |
Q4_K_M·17.6 t/s tok/s·8K ctx·GOOD FIT | Q4_K_M | 18.0 GB | 17.6 t/s | 8K | GOOD FIT | A71 |
Q4_K_M·23.9 t/s tok/s·131K ctx·FAIR FIT | Q4_K_M | 13.3 GB | 23.9 t/s | 131K | FAIR FIT | B57 |
Q4_K_M·21.0 t/s tok/s·33K ctx·FAIR FIT | Q4_K_M | 15.1 GB | 21.0 t/s | 33K | FAIR FIT | B62 |
Q4_K_M·63.5 t/s tok/s·33K ctx·EASY RUN | Q4_K_M | 5.0 GB | 63.5 t/s | 33K | EASY RUN | C33 |
Q4_K_M·57.4 t/s tok/s·41K ctx·EASY RUN | Q4_K_M | 5.5 GB | 57.4 t/s | 41K | EASY RUN | C34 |
Q4_K_M·60.0 t/s tok/s·131K ctx·EASY RUN | Q4_K_M | 5.3 GB | 60.0 t/s | 131K | EASY RUN | C34 |
Q4_K_M·40.0 t/s tok/s·33K ctx·EASY RUN | Q4_K_M | 7.9 GB | 40.0 t/s | 33K | EASY RUN | C40 |
Q4_K_M·34.7 t/s tok/s·16K ctx·EASY RUN | Q4_K_M | 9.1 GB | 34.7 t/s | 16K | EASY RUN | C43 |
Q4_K_M·11.1 t/s tok/s·33K ctx·FAIR FIT | Q4_K_M | 28.6 GB | 11.1 t/s | 33K | FAIR FIT | B56 |
Q4_K_M·64.4 t/s tok/s·33K ctx·EASY RUN | Q4_K_M | 4.9 GB | 64.4 t/s | 33K | EASY RUN | C33 |
AMD Radeon PRO W7800 Specifications
- Brand
- AMD
- Architecture
- RDNA 3
- VRAM
- 32.0 GB GDDR6
- Memory Bandwidth
- 576.0 GB/s
- Stream Processors
- 4,480
- FP16 Performance
- 90.50 TFLOPS
- TDP
- 260W
- Release Date
- 2023-04-13
- MSRP
- $2,499
Get Started
GPUs to Consider Over AMD Radeon PRO W7800
Similar GPUs and upgrades with more VRAM or higher bandwidth for AI
NVIDIA GeForce RTX 5090
NVIDIA · Blackwell
AMD Instinct MI210
AMD · CDNA 2
NVIDIA A100 40GB PCIe
NVIDIA · Ampere
NVIDIA RTX 6000 Ada Generation
NVIDIA · Ada Lovelace
NVIDIA V100 SXM2 32GB
NVIDIA · Volta
AMD Radeon PRO W7900
AMD · RDNA 3
Frequently Asked Questions
- Can AMD Radeon PRO W7800 run DeepSeek R1 Distill Qwen 32B?
Yes, the AMD Radeon PRO W7800 with 32 GB can run DeepSeek R1 Distill Qwen 32B, Qwen3 32B, Qwen2.5 Coder 32B Instruct, and 1158 other models. 21 models run at excellent quality, and 237 at good quality. Check the compatibility table above for the full list with VRAM usage and estimated speed.
- Is AMD Radeon PRO W7800 good for AI?
The AMD Radeon PRO W7800 has 32 GB of GDDR6, making it excellent for running local AI models. It supports 258 models at good quality or better. With 576.0 GB/s memory bandwidth, it delivers solid token generation speeds. This is an enthusiast-grade GPU that handles most popular open-source LLMs.
- How many parameters can AMD Radeon PRO W7800 handle?
With 32 GB, the AMD Radeon PRO W7800 supports models from 3B to 30B parameters depending on quantization level. At Q4_K_M (the recommended sweet spot), you can fit roughly 53B parameters. This means 7B models at high quality (Q6/Q8) or 30B+ models at Q4.
- What quantization should I use on AMD Radeon PRO W7800?
For the best balance of quality and speed on the AMD Radeon PRO W7800, start with Q4_K_M — it preserves ~85% of the original model quality while keeping VRAM usage reasonable. With 24+ GB, you have the headroom to run 7B models at Q5_K_M or even Q6_K for noticeably better output quality. For larger 30B models, Q4_K_M remains the sweet spot.
- How fast is AMD Radeon PRO W7800 for AI inference?
With 576.0 GB/s memory bandwidth, the AMD Radeon PRO W7800 achieves approximately 70 tokens/sec on a 7B model at Q4_K_M — that's very fast, well above conversational speed. A 14B model runs at ~35 tok/s. Token generation speed scales inversely with model size — smaller models are significantly faster.
tok/s = (576 GB/s ÷ model GB) × efficiency
Smaller models = faster inference. Memory bandwidth is the main bottleneck for token generation speed.
Estimated speed on AMD Radeon PRO W7800
~16 tok/s~16 tok/s~16 tok/s~15 tok/sReal-world results typically within ±20%. Speed depends on quantization kernel, batch size, and software stack.
- What's the best model for AMD Radeon PRO W7800?
The top-rated models for the AMD Radeon PRO W7800 are DeepSeek R1 Distill Qwen 32B, Qwen3 32B, Qwen2.5 Coder 32B Instruct. The best choice depends on your use case: coding assistants benefit from code-tuned models, while general chat works well with instruction-tuned models like Llama or Qwen.