Quick Answer: Intel Arc Pro A40 offers 6GB VRAM and starts around current market pricing. It delivers approximately 58 tokens/sec on meta-llama/Llama-Guard-3-1B. It typically draws 50W 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 |
|---|---|---|---|
| meta-llama/Llama-Guard-3-1B | Q4 | 58.10 tok/sEstimated Auto-generated benchmark | 1GB |
| inference-net/Schematron-3B | Q4 | 57.61 tok/sEstimated Auto-generated benchmark | 2GB |
| allenai/OLMo-2-0425-1B | Q4 | 56.36 tok/sEstimated Auto-generated benchmark | 1GB |
| meta-llama/Llama-3.2-1B-Instruct | Q4 | 54.97 tok/sEstimated Auto-generated benchmark | 1GB |
| unsloth/Llama-3.2-1B-Instruct | Q4 | 54.43 tok/sEstimated Auto-generated benchmark | 1GB |
| TinyLlama/TinyLlama-1.1B-Chat-v1.0 | Q4 | 53.73 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-3-1b-it | Q4 | 53.70 tok/sEstimated Auto-generated benchmark | 1GB |
| WeiboAI/VibeThinker-1.5B | Q4 | 53.67 tok/sEstimated Auto-generated benchmark | 1GB |
| ibm-research/PowerMoE-3b | Q4 | 53.66 tok/sEstimated Auto-generated benchmark | 2GB |
| Qwen/Qwen2.5-3B | Q4 | 53.52 tok/sEstimated Auto-generated benchmark | 2GB |
| Qwen/Qwen2.5-3B-Instruct | Q4 | 53.29 tok/sEstimated Auto-generated benchmark | 2GB |
| nari-labs/Dia2-2B | Q4 | 53.03 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-1B | Q4 | 52.86 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-2b | Q4 | 52.39 tok/sEstimated Auto-generated benchmark | 1GB |
| google/embeddinggemma-300m | Q4 | 52.36 tok/sEstimated Auto-generated benchmark | 1GB |
| google-bert/bert-base-uncased | Q4 | 52.28 tok/sEstimated Auto-generated benchmark | 1GB |
| apple/OpenELM-1_1B-Instruct | Q4 | 51.82 tok/sEstimated Auto-generated benchmark | 1GB |
| google/gemma-2-2b-it | Q4 | 51.26 tok/sEstimated Auto-generated benchmark | 1GB |
| facebook/sam3 | Q4 | 51.19 tok/sEstimated Auto-generated benchmark | 1GB |
| deepseek-ai/DeepSeek-OCR | Q4 | 49.77 tok/sEstimated Auto-generated benchmark | 2GB |
| google-t5/t5-3b | Q4 | 49.75 tok/sEstimated Auto-generated benchmark | 2GB |
| unsloth/gemma-3-1b-it | Q4 | 49.43 tok/sEstimated Auto-generated benchmark | 1GB |
| unsloth/Llama-3.2-3B-Instruct | Q4 | 49.13 tok/sEstimated Auto-generated benchmark | 2GB |
| ibm-granite/granite-3.3-2b-instruct | Q4 | 48.65 tok/sEstimated Auto-generated benchmark | 1GB |
| LiquidAI/LFM2-1.2B | Q4 | 48.62 tok/sEstimated Auto-generated benchmark | 1GB |
| context-labs/meta-llama-Llama-3.2-3B-Instruct-FP16 | Q4 | 48.51 tok/sEstimated Auto-generated benchmark | 2GB |
| Qwen/Qwen3-8B-FP8 | Q4 | 48.48 tok/sEstimated Auto-generated benchmark | 4GB |
| lmstudio-community/DeepSeek-R1-0528-Qwen3-8B-MLX-8bit | Q4 | 48.48 tok/sEstimated Auto-generated benchmark | 4GB |
| deepseek-ai/DeepSeek-R1-Distill-Llama-8B | Q4 | 48.43 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen3-Embedding-4B | Q4 | 48.42 tok/sEstimated Auto-generated benchmark | 2GB |
| deepseek-ai/DeepSeek-R1-0528 | Q4 | 48.23 tok/sEstimated Auto-generated benchmark | 4GB |
| petals-team/StableBeluga2 | Q4 | 48.20 tok/sEstimated Auto-generated benchmark | 4GB |
| tencent/HunyuanOCR | Q4 | 48.18 tok/sEstimated Auto-generated benchmark | 1GB |
| distilbert/distilgpt2 | Q4 | 48.16 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen3-Embedding-8B | Q4 | 48.16 tok/sEstimated Auto-generated benchmark | 4GB |
| bigcode/starcoder2-3b | Q4 | 48.14 tok/sEstimated Auto-generated benchmark | 2GB |
| openai-community/gpt2 | Q4 | 48.09 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen3-0.6B | Q4 | 48.09 tok/sEstimated Auto-generated benchmark | 3GB |
| vikhyatk/moondream2 | Q4 | 48.05 tok/sEstimated Auto-generated benchmark | 4GB |
| deepseek-ai/deepseek-coder-1.3b-instruct | Q4 | 48.05 tok/sEstimated Auto-generated benchmark | 2GB |
| meta-llama/Llama-3.2-3B-Instruct | Q4 | 48.02 tok/sEstimated Auto-generated benchmark | 2GB |
| trl-internal-testing/tiny-Qwen2ForCausalLM-2.5 | Q4 | 47.98 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen2.5-Coder-1.5B | Q4 | 47.96 tok/sEstimated Auto-generated benchmark | 3GB |
| black-forest-labs/FLUX.2-dev | Q4 | 47.96 tok/sEstimated Auto-generated benchmark | 4GB |
| BSC-LT/salamandraTA-7b-instruct | Q4 | 47.90 tok/sEstimated Auto-generated benchmark | 4GB |
| meta-llama/Llama-3.2-3B | Q4 | 47.86 tok/sEstimated Auto-generated benchmark | 2GB |
| swiss-ai/Apertus-8B-Instruct-2509 | Q4 | 47.84 tok/sEstimated Auto-generated benchmark | 4GB |
| Qwen/Qwen3-1.7B | Q4 | 47.47 tok/sEstimated Auto-generated benchmark | 4GB |
| GSAI-ML/LLaDA-8B-Instruct | Q4 | 47.47 tok/sEstimated Auto-generated benchmark | 4GB |
| microsoft/phi-2 | Q4 | 47.39 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 |
|---|---|---|---|---|
| Qwen/Qwen2.5-7B-Instruct | FP16 | Not supported | 15.16 tok/sEstimated | 15GB (have 6GB) |
| Gensyn/Qwen2.5-0.5B-Instruct | Q4 | Fits comfortably | 42.09 tok/sEstimated | 3GB (have 6GB) |
| meta-llama/Llama-3.1-8B-Instruct | Q8 | Not supported | 28.47 tok/sEstimated | 9GB (have 6GB) |
| google/gemma-3-1b-it | Q8 | Fits comfortably | 37.40 tok/sEstimated | 1GB (have 6GB) |
| google/gemma-3-1b-it | FP16 | Fits comfortably | 20.46 tok/sEstimated | 2GB (have 6GB) |
| Qwen/Qwen3-Embedding-0.6B | Q4 | Fits comfortably | 46.96 tok/sEstimated | 3GB (have 6GB) |
| Qwen/Qwen3-Embedding-0.6B | Q8 | Fits (tight) | 31.64 tok/sEstimated | 6GB (have 6GB) |
| Qwen/Qwen2.5-3B-Instruct | Q4 | Fits comfortably | 53.29 tok/sEstimated | 2GB (have 6GB) |
| deepseek-ai/DeepSeek-R1-Distill-Qwen-32B | Q8 | Not supported | 11.83 tok/sEstimated | 33GB (have 6GB) |
| deepseek-ai/DeepSeek-R1-Distill-Qwen-32B | FP16 | Not supported | 6.30 tok/sEstimated | 66GB (have 6GB) |
| distilbert/distilgpt2 | Q4 | Fits comfortably | 48.16 tok/sEstimated | 4GB (have 6GB) |
| distilbert/distilgpt2 | Q8 | Not supported | 31.32 tok/sEstimated | 7GB (have 6GB) |
| meta-llama/Llama-3.2-1B | Q4 | Fits comfortably | 52.86 tok/sEstimated | 1GB (have 6GB) |
| meta-llama/Llama-3.2-1B | Q8 | Fits comfortably | 40.37 tok/sEstimated | 1GB (have 6GB) |
| meta-llama/Llama-3.2-1B | FP16 | Fits comfortably | 20.47 tok/sEstimated | 2GB (have 6GB) |
| meta-llama/Meta-Llama-3-8B | Q4 | Fits comfortably | 47.14 tok/sEstimated | 4GB (have 6GB) |
| meta-llama/Meta-Llama-3-8B | Q8 | Not supported | 28.62 tok/sEstimated | 9GB (have 6GB) |
| meta-llama/Meta-Llama-3-8B | FP16 | Not supported | 18.38 tok/sEstimated | 17GB (have 6GB) |
| Qwen/Qwen2.5-7B | Q4 | Fits comfortably | 41.26 tok/sEstimated | 4GB (have 6GB) |
| Qwen/Qwen2.5-7B | Q8 | Not supported | 29.66 tok/sEstimated | 7GB (have 6GB) |
| Qwen/Qwen2.5-7B | FP16 | Not supported | 15.83 tok/sEstimated | 15GB (have 6GB) |
| Qwen/Qwen2.5-0.5B-Instruct | Q4 | Fits comfortably | 47.28 tok/sEstimated | 3GB (have 6GB) |
| Qwen/Qwen2.5-0.5B-Instruct | Q8 | Fits (tight) | 28.09 tok/sEstimated | 5GB (have 6GB) |
| Qwen/Qwen2.5-0.5B-Instruct | FP16 | Not supported | 15.28 tok/sEstimated | 11GB (have 6GB) |
| Qwen/Qwen3-32B | Q4 | Not supported | 14.17 tok/sEstimated | 16GB (have 6GB) |
| Qwen/Qwen3-Next-80B-A3B-Instruct | Q4 | Not supported | 8.95 tok/sEstimated | 39GB (have 6GB) |
| Qwen/Qwen3-Next-80B-A3B-Instruct | Q8 | Not supported | 6.66 tok/sEstimated | 78GB (have 6GB) |
| microsoft/Phi-3-mini-4k-instruct | FP16 | Not supported | 16.00 tok/sEstimated | 15GB (have 6GB) |
| Qwen/Qwen3-4B | Q8 | Fits comfortably | 30.71 tok/sEstimated | 4GB (have 6GB) |
| google-t5/t5-3b | FP16 | Fits (tight) | 18.93 tok/sEstimated | 6GB (have 6GB) |
| rednote-hilab/dots.ocr | FP16 | Not supported | 17.95 tok/sEstimated | 15GB (have 6GB) |
| meta-llama/Llama-3.3-70B-Instruct | FP16 | Not supported | 5.45 tok/sEstimated | 137GB (have 6GB) |
| Qwen/Qwen3-14B | Q4 | Not supported | 35.03 tok/sEstimated | 7GB (have 6GB) |
| Qwen/Qwen3-14B | Q8 | Not supported | 25.31 tok/sEstimated | 14GB (have 6GB) |
| microsoft/phi-2 | FP16 | Not supported | 15.27 tok/sEstimated | 15GB (have 6GB) |
| meta-llama/Llama-2-7b-hf | Q4 | Fits comfortably | 46.63 tok/sEstimated | 4GB (have 6GB) |
| meta-llama/Llama-2-7b-hf | Q8 | Not supported | 30.03 tok/sEstimated | 7GB (have 6GB) |
| HuggingFaceTB/SmolLM2-135M | Q4 | Fits comfortably | 47.14 tok/sEstimated | 4GB (have 6GB) |
| HuggingFaceTB/SmolLM2-135M | Q8 | Not supported | 30.45 tok/sEstimated | 7GB (have 6GB) |
| microsoft/DialoGPT-medium | Q8 | Not supported | 33.44 tok/sEstimated | 7GB (have 6GB) |
| microsoft/DialoGPT-medium | FP16 | Not supported | 17.64 tok/sEstimated | 15GB (have 6GB) |
| MiniMaxAI/MiniMax-M2 | Q4 | Fits comfortably | 41.84 tok/sEstimated | 4GB (have 6GB) |
| MiniMaxAI/MiniMax-M2 | Q8 | Not supported | 33.83 tok/sEstimated | 7GB (have 6GB) |
| MiniMaxAI/MiniMax-M2 | FP16 | Not supported | 17.77 tok/sEstimated | 15GB (have 6GB) |
| microsoft/phi-4 | FP16 | Not supported | 17.15 tok/sEstimated | 15GB (have 6GB) |
| meta-llama/Llama-3.1-8B | Q8 | Not supported | 28.39 tok/sEstimated | 9GB (have 6GB) |
| deepseek-ai/DeepSeek-R1-0528 | Q4 | Fits comfortably | 48.23 tok/sEstimated | 4GB (have 6GB) |
| deepseek-ai/DeepSeek-R1-0528 | Q8 | Not supported | 27.86 tok/sEstimated | 7GB (have 6GB) |
| deepseek-ai/DeepSeek-R1-0528 | FP16 | Not supported | 16.57 tok/sEstimated | 15GB (have 6GB) |
| Qwen/Qwen2.5-7B-Instruct | Q8 | Not supported | 30.57 tok/sEstimated | 7GB (have 6GB) |
Note: Performance estimates are calculated. Real results may vary. Methodology · Submit real data
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