gpullm-inferenceimage-gen

RTX A5500 Max-Q

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

RTX A5500 Max-Q

The RTX A5500 Max-Q 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 448 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 Max-Q
Llama 3 8B (Q4_K_M)52.4 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 448 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: 448 GB/s
  • TDP: 80 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 Max-Q16 GB448 GB/s52.4 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 Max-Q 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 Max-Q have?

The RTX A5500 Max-Q has 16 GB of VRAM with 448 GB/s memory bandwidth.

What local AI models can run on the RTX A5500 Max-Q?

The RTX A5500 Max-Q 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 Max-Q good for local AI inference?

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

Where can I buy the RTX A5500 Max-Q?

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 Max-Q compare to other GPUs?

RTX A5500 Max-Q has 16 GB VRAM and 448 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 Max-Q?

The RTX A5500 Max-Q has a TDP of 80W. 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

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