Quick Answer: AMD Radeon Pro W7800 offers 32GB VRAM and starts around $2497.96. It delivers approximately 117 tokens/sec on ibm-granite/granite-3.3-2b-instruct. It typically draws 260W under load.
This GPU offers reliable throughput for local AI workloads. Pair it with the right model quantization to hit your desired tokens/sec, and monitor prices below to catch the best deal.
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| Model | Quantization | Tokens/sec | VRAM used |
|---|---|---|---|
| ibm-granite/granite-3.3-2b-instruct | Q4 | 116.90 tok/sEstimated Auto-generated benchmark | 1GB |
| Qwen/Qwen2.5-3B-Instruct | Q4 | 116.47 tok/sEstimated Auto-generated benchmark | 2GB |
| nari-labs/Dia2-2B | Q4 | 116.26 tok/sEstimated Auto-generated benchmark | 2GB |
| unsloth/Llama-3.2-1B-Instruct | Q4 | 115.83 tok/sEstimated Auto-generated benchmark | 1GB |
| google-bert/bert-base-uncased | Q4 | 114.83 tok/sEstimated Auto-generated benchmark | 1GB |
| apple/OpenELM-1_1B-Instruct | Q4 | 114.79 tok/sEstimated Auto-generated benchmark | 1GB |
| tencent/HunyuanOCR | Q4 | 114.60 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-2b | Q4 | 113.62 tok/sEstimated Auto-generated benchmark | 1GB |
| Qwen/Qwen2.5-3B | Q4 | 113.58 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-3B-Instruct | Q4 | 113.48 tok/sEstimated Auto-generated benchmark | 2GB |
| google/gemma-3-1b-it | Q4 | 113.18 tok/sEstimated Auto-generated benchmark | 1GB |
| google-t5/t5-3b | Q4 | 112.49 tok/sEstimated Auto-generated benchmark | 2GB |
| unsloth/gemma-3-1b-it | Q4 | 111.83 tok/sEstimated Auto-generated benchmark | 1GB |
| LiquidAI/LFM2-1.2B | Q4 | 111.41 tok/sEstimated Auto-generated benchmark | 1GB |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q4 | 110.81 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-2-2b-it | Q4 | 110.60 tok/sEstimated Auto-generated benchmark | 1GB |
| allenai/OLMo-2-0425-1B | Q4 | 109.94 tok/sEstimated Auto-generated benchmark | 1GB |
| unsloth/Llama-3.2-3B-Instruct | Q4 | 108.54 tok/sEstimated Auto-generated benchmark | 2GB |
| deepseek-ai/DeepSeek-OCR | Q4 | 108.42 tok/sEstimated Auto-generated benchmark | 2GB |
| deepseek-ai/deepseek-coder-1.3b-instruct | Q4 | 107.71 tok/sEstimated Auto-generated benchmark | 2GB |
| context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16 | Q4 | 106.82 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-3B | Q4 | 106.74 tok/sEstimated Auto-generated benchmark | 2GB |
| inference-net/Schematron-3B | Q4 | 104.25 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-Guard-3-1B | Q4 | 104.04 tok/sEstimated Auto-generated benchmark | 1GB |
| WeiboAI/VibeThinker-1.5B | Q4 | 103.65 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-1B | Q4 | 103.19 tok/sEstimated Auto-generated benchmark | 1GB |
| ibm-research/PowerMoE-3b | Q4 | 101.79 tok/sEstimated Auto-generated benchmark | 2GB |
| facebook/sam3 | Q4 | 101.28 tok/sEstimated Auto-generated benchmark | 1GB |
| openai-community/gpt2-xl | Q4 | 98.30 tok/sEstimated Auto-generated benchmark | 4GB |
| BSC-LT/salamandraTA-7b-instruct | Q4 | 98.29 tok/sEstimated Auto-generated benchmark | 4GB |
| meta-llama/Llama-3.2-3B-Instruct | Q4 | 98.20 tok/sEstimated Auto-generated benchmark | 2GB |
| Alibaba-NLP/gte-Qwen2-1.5B-instruct | Q4 | 98.19 tok/sEstimated Auto-generated benchmark | 3GB |
| meta-llama/Llama-3.2-1B-Instruct | Q4 | 97.89 tok/sEstimated Auto-generated benchmark | 1GB |
| bigcode/starcoder2-3b | Q4 | 97.82 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.1-8B-Instruct | Q4 | 97.69 tok/sEstimated Auto-generated benchmark | 4GB |
| zai-org/GLM-4.6-FP8 | Q4 | 97.29 tok/sEstimated Auto-generated benchmark | 4GB |
| google/embeddinggemma-300m | Q4 | 96.81 tok/sEstimated Auto-generated benchmark | 1GB |
| EleutherAI/gpt-neo-125m | Q4 | 96.81 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen3-8B | Q4 | 96.33 tok/sEstimated Auto-generated benchmark | 4GB |
| unsloth/Meta-Llama-3.1-8B-Instruct-bnb-4bit | Q4 | 96.13 tok/sEstimated Auto-generated benchmark | 4GB |
| microsoft/DialoGPT-small | Q4 | 96.11 tok/sEstimated Auto-generated benchmark | 4GB |
| trl-internal-testing/tiny-random-LlamaForCausalLM | Q4 | 96.09 tok/sEstimated Auto-generated benchmark | 4GB |
| microsoft/Phi-3.5-vision-instruct | Q4 | 95.81 tok/sEstimated Auto-generated benchmark | 4GB |
| GSAI-ML/LLaDA-8B-Base | Q4 | 95.81 tok/sEstimated Auto-generated benchmark | 4GB |
| bigscience/bloomz-560m | Q4 | 95.63 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen3-Embedding-0.6B | Q4 | 95.56 tok/sEstimated Auto-generated benchmark | 3GB |
| skt/kogpt2-base-v2 | Q4 | 95.51 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen3-4B-Thinking-2507 | Q4 | 95.43 tok/sEstimated Auto-generated benchmark | 2GB |
| Qwen/Qwen3-8B-FP8 | Q4 | 95.03 tok/sEstimated Auto-generated benchmark | 4GB |
| sshleifer/tiny-gpt2 | Q4 | 94.95 tok/sEstimated Auto-generated benchmark | 4GB |
Note: Performance estimates are calculated. Real results may vary. Methodology · Submit real data
| Model | Quantization | Verdict | Estimated speed | VRAM needed |
|---|---|---|---|---|
| deepseek-ai/DeepSeek-R1 | FP16 | Fits comfortably | 31.15 tok/sEstimated | 15GB (have 32GB) |
| Qwen/Qwen3-30B-A3B | Q4 | Fits comfortably | 45.98 tok/sEstimated | 15GB (have 32GB) |
| google/gemma-2-2b-it | Q4 | Fits comfortably | 110.60 tok/sEstimated | 1GB (have 32GB) |
| openai-community/gpt2-xl | Q4 | Fits comfortably | 98.30 tok/sEstimated | 4GB (have 32GB) |
| Qwen/Qwen3-4B-Instruct-2507 | Q8 | Fits comfortably | 63.05 tok/sEstimated | 4GB (have 32GB) |
| trl-internal-testing/tiny-Qwen2ForCausalLM-2.5 | Q4 | Fits comfortably | 81.02 tok/sEstimated | 4GB (have 32GB) |
| trl-internal-testing/tiny-Qwen2ForCausalLM-2.5 | Q8 | Fits comfortably | 58.54 tok/sEstimated | 7GB (have 32GB) |
| trl-internal-testing/tiny-Qwen2ForCausalLM-2.5 | FP16 | Fits comfortably | 32.02 tok/sEstimated | 15GB (have 32GB) |
| Qwen/Qwen3-4B-Instruct-2507 | Q4 | Fits comfortably | 80.51 tok/sEstimated | 2GB (have 32GB) |
| mistralai/Mistral-7B-Instruct-v0.2 | Q4 | Fits comfortably | 90.47 tok/sEstimated | 4GB (have 32GB) |
| mistralai/Mistral-7B-Instruct-v0.2 | Q8 | Fits comfortably | 67.48 tok/sEstimated | 7GB (have 32GB) |
| deepseek-ai/DeepSeek-R1-Distill-Qwen-32B | Q8 | Not supported | 20.17 tok/sEstimated | 33GB (have 32GB) |
| deepseek-ai/DeepSeek-R1-Distill-Qwen-32B | FP16 | Not supported | 12.17 tok/sEstimated | 66GB (have 32GB) |
| distilbert/distilgpt2 | Q4 | Fits comfortably | 91.64 tok/sEstimated | 4GB (have 32GB) |
| distilbert/distilgpt2 | Q8 | Fits comfortably | 61.28 tok/sEstimated | 7GB (have 32GB) |
| distilbert/distilgpt2 | FP16 | Fits comfortably | 35.54 tok/sEstimated | 15GB (have 32GB) |
| RedHatAI/Llama-3.3-70B-Instruct-FP8-dynamic | Q4 | Not supported | 33.57 tok/sEstimated | 34GB (have 32GB) |
| RedHatAI/Llama-3.3-70B-Instruct-FP8-dynamic | Q8 | Not supported | 20.55 tok/sEstimated | 68GB (have 32GB) |
| Qwen/Qwen2.5-0.5B | FP16 | Fits comfortably | 34.53 tok/sEstimated | 11GB (have 32GB) |
| meta-llama/Llama-2-7b-hf | FP16 | Fits comfortably | 35.07 tok/sEstimated | 15GB (have 32GB) |
| deepseek-ai/DeepSeek-R1-Distill-Llama-8B | Q4 | Fits comfortably | 84.11 tok/sEstimated | 4GB (have 32GB) |
| deepseek-ai/DeepSeek-R1-Distill-Llama-8B | Q8 | Fits comfortably | 62.99 tok/sEstimated | 9GB (have 32GB) |
| deepseek-ai/DeepSeek-R1-Distill-Llama-8B | FP16 | Fits comfortably | 36.31 tok/sEstimated | 17GB (have 32GB) |
| microsoft/DialoGPT-medium | FP16 | Fits comfortably | 31.86 tok/sEstimated | 15GB (have 32GB) |
| MiniMaxAI/MiniMax-M2 | Q4 | Fits comfortably | 91.48 tok/sEstimated | 4GB (have 32GB) |
| deepseek-ai/DeepSeek-V3.1 | Q8 | Fits comfortably | 56.85 tok/sEstimated | 7GB (have 32GB) |
| deepseek-ai/DeepSeek-R1-0528 | Q4 | Fits comfortably | 84.06 tok/sEstimated | 4GB (have 32GB) |
| deepseek-ai/DeepSeek-R1-0528 | Q8 | Fits comfortably | 65.16 tok/sEstimated | 7GB (have 32GB) |
| HuggingFaceTB/SmolLM-135M | FP16 | Fits comfortably | 33.73 tok/sEstimated | 15GB (have 32GB) |
| trl-internal-testing/tiny-random-LlamaForCausalLM | Q4 | Fits comfortably | 96.09 tok/sEstimated | 4GB (have 32GB) |
| trl-internal-testing/tiny-random-LlamaForCausalLM | Q8 | Fits comfortably | 61.32 tok/sEstimated | 7GB (have 32GB) |
| trl-internal-testing/tiny-random-LlamaForCausalLM | FP16 | Fits comfortably | 36.77 tok/sEstimated | 15GB (have 32GB) |
| Qwen/Qwen3-Coder-30B-A3B-Instruct | Q4 | Fits comfortably | 45.78 tok/sEstimated | 15GB (have 32GB) |
| IlyaGusev/saiga_llama3_8b | Q8 | Fits comfortably | 64.63 tok/sEstimated | 9GB (have 32GB) |
| meta-llama/Llama-Guard-3-1B | Q4 | Fits comfortably | 104.04 tok/sEstimated | 1GB (have 32GB) |
| lmstudio-community/Qwen3-4B-Thinking-2507-MLX-6bit | Q8 | Fits comfortably | 56.59 tok/sEstimated | 4GB (have 32GB) |
| lmstudio-community/Qwen3-4B-Thinking-2507-MLX-6bit | FP16 | Fits comfortably | 32.16 tok/sEstimated | 9GB (have 32GB) |
| hmellor/tiny-random-LlamaForCausalLM | Q4 | Fits comfortably | 85.79 tok/sEstimated | 4GB (have 32GB) |
| Qwen/Qwen2.5-72B-Instruct | Q8 | Not supported | 12.28 tok/sEstimated | 70GB (have 32GB) |
| Qwen/Qwen2.5-72B-Instruct | FP16 | Not supported | 7.13 tok/sEstimated | 141GB (have 32GB) |
| ibm-granite/granite-3.3-2b-instruct | Q4 | Fits comfortably | 116.90 tok/sEstimated | 1GB (have 32GB) |
| Qwen/Qwen2.5-32B | FP16 | Not supported | 11.14 tok/sEstimated | 66GB (have 32GB) |
| Qwen/Qwen3-4B-Thinking-2507-FP8 | Q4 | Fits comfortably | 93.10 tok/sEstimated | 2GB (have 32GB) |
| Qwen/Qwen3-4B-Thinking-2507-FP8 | Q8 | Fits comfortably | 57.74 tok/sEstimated | 4GB (have 32GB) |
| Qwen/Qwen3-4B-Thinking-2507-FP8 | FP16 | Fits comfortably | 36.02 tok/sEstimated | 9GB (have 32GB) |
| lmstudio-community/Qwen3-Coder-30B-A3B-Instruct-MLX-8bit | Q4 | Fits comfortably | 51.03 tok/sEstimated | 15GB (have 32GB) |
| GSAI-ML/LLaDA-8B-Base | FP16 | Fits comfortably | 35.31 tok/sEstimated | 17GB (have 32GB) |
| HuggingFaceM4/tiny-random-LlamaForCausalLM | Q8 | Fits comfortably | 61.04 tok/sEstimated | 7GB (have 32GB) |
| meta-llama/Llama-3.1-8B-Instruct | FP16 | Fits comfortably | 26.50 tok/sEstimated | 17GB (have 32GB) |
| Qwen/Qwen2.5-0.5B | Q8 | Fits comfortably | 68.04 tok/sEstimated | 5GB (have 32GB) |
Note: Performance estimates are calculated. Real results may vary. Methodology · Submit real data
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