gpullm-inferenceimage-gen

RTX A5500 Mobile

Updated Jun 8, 2026
VRAM
16 GB
Bandwidth
512 GB/s
TDP
165 W
MSRP
-
Category
gpu

RTX A5500 Mobile

The RTX A5500 Mobile is an NVIDIA GPU built on the Ampere architecture, released 2022-03-22. For running AI locally, the numbers that matter are its 16 GB of GDDR6 and 512 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:

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 RTX A5500 Mobile
Llama 3 8B (Q4_K_M)59.9 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 512 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 (256-bit bus)
  • Bandwidth: 512 GB/s
  • TDP: 165 W
  • Process: 8 nm
  • Interface: PCIe 4.0 x16

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:

GPUVRAMBandwidthLlama 3 8B Q4
RTX A5500 Mobile16 GB512 GB/s59.9 tok/s
AMD Radeon RX 7600 XT16 GB288 GB/s33.7 tok/s
AMD Radeon RX 7800 XT16 GB624 GB/s73 tok/s
AMD Radeon RX 907016 GB512 GB/s59.9 tok/s

Bottom line

The RTX A5500 Mobile 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

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 RTX A5500 Mobile have?

The RTX A5500 Mobile has 16 GB of VRAM with 512 GB/s memory bandwidth.

What local AI models can run on the RTX A5500 Mobile?

The RTX A5500 Mobile 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 RTX A5500 Mobile good for local AI inference?

RTX A5500 Mobile is best for llm-inference, image-gen. With ample VRAM it handles most open models well.

Where can I buy the RTX A5500 Mobile?

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 RTX A5500 Mobile compare to other GPUs?

RTX A5500 Mobile has 16 GB VRAM and 512 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 RTX A5500 Mobile?

The RTX A5500 Mobile has a TDP of 165W. 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

Comments coming soon

Configure NEXT_PUBLIC_GISCUS_REPO_ID and NEXT_PUBLIC_GISCUS_CATEGORY_ID at giscus.app to enable.