Arc Pro B50
Arc Pro B50
The Arc Pro B50 is an Intel GPU built on the Xe2-HPG architecture, released 2025-09-05. For running AI locally, the numbers that matter are its 16 GB of GDDR6 and 224 GB/s of memory bandwidth. VRAM decides which models fit at all; bandwidth sets how fast they generate text.
What you can run on 16 GB
At Q4_K_M quantization (the usual local default), 16 GB holds models up to roughly 25B parameters, leaving headroom for context. On this card you can run, among others:
- gpt-oss-20b - 21.5B parameters
- Qwen2.5-14B-Instruct - 14.8B parameters
- Qwen2.5-Coder-14B-Instruct - 14.8B parameters
- Phi-4 - 14B parameters
- Qwen3 14B - 14B parameters
Larger models need a higher-VRAM card, a second GPU, or CPU offload (which is much slower). Check any specific model with the VRAM calculator, or see the full picture on what can I run.
Local LLM speed (LLaMA 3, llama.cpp)
Single-stream token-generation throughput - estimated from memory bandwidth:
| Model (quant) | Speed on Arc Pro B50 |
|---|---|
| Llama 3 8B (Q4_K_M) | 26.2 tok/s |
| Llama 3 8B (F16) | ✗ won't fit |
| Llama 3 70B (Q4_K_M) | ✗ won't fit |
Because decode is memory-bandwidth bound, the 224 GB/s figure is the best single predictor of chat speed on this card. Estimates are calibrated against measured RTX-40-series cards and are typically within ~15%.
Memory and power
- VRAM: 16 GB GDDR6 (128-bit bus)
- Bandwidth: 224 GB/s
- TDP: 70 W - a 250 W+ power supply is recommended
- Process: 5 nm
- Interface: PCIe 5.0 x8
Quantization and context
Quantization trades a little quality for a lot of VRAM. On 16 GB you can fit roughly a 25B model at Q4_K_M, about a 13B model at the higher-quality Q8, or a smaller model at full FP16. Longer context windows also consume VRAM (the KV cache grows with context length), so leave a few GB of headroom if you plan to use large prompts or many concurrent requests. For most chat and coding use, Q4_K_M on this card is the sweet spot between speed, quality, and the 16 GB budget.
How it compares
Similar cards for local AI, by VRAM and 8B-Q4 speed:
| GPU | VRAM | Bandwidth | Llama 3 8B Q4 |
|---|---|---|---|
| Arc Pro B50 | 16 GB | 224 GB/s | 26.2 tok/s |
| AMD Radeon RX 7600 XT | 16 GB | 288 GB/s | 33.7 tok/s |
| AMD Radeon RX 7800 XT | 16 GB | 624 GB/s | 73 tok/s |
| AMD Radeon RX 9070 | 16 GB | 512 GB/s | 59.9 tok/s |
Bottom line
The Arc Pro B50 is best for llm-inference, image-gen. Its 16 GB suits 7B-14B models and image generation well. If you need more, compare with AMD Radeon RX 7600 XT and AMD Radeon RX 7800 XT.
Sources
- Specifications: RightNow GPU Database (TechPowerUp data)
- Benchmarks: GPU-Benchmarks-on-LLM-Inference (basis for the bandwidth estimate)
Specs and benchmarks last checked 2026-06-08. Verify current pricing before buying.
Frequently asked
Quick answers to common questions
How much VRAM does the Arc Pro B50 have?
The Arc Pro B50 has 16 GB of VRAM with 224 GB/s memory bandwidth.
What local AI models can run on the Arc Pro B50?
The Arc Pro B50 with 16 GB VRAM can run many models depending on quantization. Models up to ~24B params may fit at Q4_K_M. Use our VRAM calculator to check specific models.
Is the Arc Pro B50 good for local AI inference?
Arc Pro B50 is best for llm-inference, image-gen. With ample VRAM it handles most open models well.
Where can I buy the Arc Pro B50?
Check our buy links above for the best current prices on Amazon, Newegg, and B&H. Prices vary by retailer and availability.
How does the Arc Pro B50 compare to other GPUs?
Arc Pro B50 has 16 GB VRAM and 224 GB/s bandwidth. It is a mid-to-high-range card capable of running most 7B–30B models. Browse our hardware directory for side-by-side comparisons.
What power supply do I need for the Arc Pro B50?
The Arc Pro B50 has a TDP of 70W. A standard quality PSU of 650W+ should suffice. Always check the manufacturer's recommendations for your specific build.
Nearby options
Similar hardware and models that fit
Similar hardware
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