AMDRDNA 4

Best AI Models for AMD Radeon RX 9060 XT 16GB (16.0GB)

VRAM:16.0 GB GDDR6·Bandwidth:320.0 GB/s·Stream Processors:2,048·TDP:160W·MSRP:$349

16 GB is a comfortable mid-range tier for local AI. Most 7B–13B models run smoothly at good quantization levels, and smaller models can run at near-full precision.

This memory tier strikes a nice balance between price and capability. Popular 7B models like Llama 3 8B, Mistral 7B, and Qwen 2.5 7B all run very well at Q4_K_M quantization with fast inference and reasonable context windows. You can also fit some larger 13B models at Q3–Q4, though you'll want to keep context lengths modest. Small models like Phi 3 Mini (3.8B) practically fly at Q8 or even FP16 quality.

Runs Well

  • 7B models at Q4–Q6 quality with good speed
  • Small models (3B–4B) at Q8 or FP16
  • 9B models (Gemma 2 9B) at Q4_K_M

Challenging

  • 13B–14B models need Q3 or lower
  • 30B+ models do not fit in VRAM
  • Long context (>8K tokens) with larger models

What LLMs Can AMD Radeon RX 9060 XT 16GB Run?

110 models · 20 excellent · 37 good

Showing compatibility for AMD Radeon RX 9060 XT 16GB

LLM models compatible with AMD Radeon RX 9060 XT 16GB — ranked by performance
ModelVRAMGrade
GPT OSS 20B21.5B
Q4_K_M·14.5 t/s tok/s·131K ctx·DECENT
13.3 GBB50
Qwen1.5 14B14.2B
Q4_K_M·18.3 t/s tok/s·33K ctx·DECENT
10.5 GBB58
Phi 414.7B
Q4_K_M·20.2 t/s tok/s·16K ctx·DECENT
9.5 GBB60
Q3_K_M·14.5 t/s tok/s·262K ctx·DECENT
13.2 GBB50
Phi 4 Reasoning14.7B
Q4_K_M·20.2 t/s tok/s·33K ctx·DECENT
9.5 GBB60
Q4_K_M·23.3 t/s tok/s·262K ctx·DECENT
8.2 GBB64
Q4_K_M·22.4 t/s tok/s·DECENT
8.6 GBB62
Gemma 3 12B IT12.2B
Q4_K_M·23.9 t/s tok/s·33K ctx·DECENT
8.0 GBB64
Gemma 4 12B12.0B
Q4_K_M·23.3 t/s tok/s·262K ctx·DECENT
8.2 GBB64
Qwen 14B Chat14.2B
Q4_K_M·20.5 t/s tok/s·8K ctx·DECENT
9.3 GBB60
Q4_K_M·23.8 t/s tok/s·131K ctx·DECENT
8.1 GBB64
Q4_K_M·22.4 t/s tok/s·DECENT
8.6 GBB62
Qwen 14B14.2B
Q4_K_M·20.5 t/s tok/s·8K ctx·DECENT
9.3 GBB60
Q4_K_M·22.4 t/s tok/s·DECENT
8.6 GBB62
Qwen3 8B8.2B
Q4_K_M·34.8 t/s tok/s·41K ctx·RUNS WELL
5.5 GBA73
Q4_K_M·22.4 t/s tok/s·DECENT
8.6 GBB62

AMD Radeon RX 9060 XT 16GB Specifications

Brand
AMD
Architecture
RDNA 4
VRAM
16.0 GB GDDR6
Memory Bandwidth
320.0 GB/s
Stream Processors
2,048
FP16 Performance
27.20 TFLOPS
TDP
160W
Release Date
2025-06-05
MSRP
$349

Get Started

Ollama (Recommended)

$curl -fsSL https://ollama.com/install.sh | sh
$ollama run llama3:8b

LM Studio

LM Studio

Download LM Studio, search for a model, and run it with one click.

Prompt Processing

Estimated for Mellum2 12B A2.5B Thinking SFT, the compute-bound phase that reads your prompt before the first reply token appears.

4,532tok/s prefill

Short chat

113 ms

512 tok prompt

Long chat

904 ms

4,096 tok prompt

Document / codebase

7.2 s

32,768 tok prompt

Prefill is compute-bound and a different number from the decode tok/s shown elsewhere on this page — how prompt processing works →

Efficiency & Value

Based on Mellum2 12B A2.5B Thinking SFT at ~25.1 tok/s decode.

Tokens per watt

0.16tok/s per W

Higher is better.

$ per tok/s (MSRP)

$13.90

MSRP-based, not street price. Lower is better.

How efficiency & value are calculated →

Performance figures are estimates calibrated as of 2026-07-30 see calibration basis →

GPUs to Consider Over AMD Radeon RX 9060 XT 16GB

Similar GPUs and upgrades with more VRAM or higher bandwidth for AI

Frequently Asked Questions

Can AMD Radeon RX 9060 XT 16GB run GPT OSS 20B?

Yes, the AMD Radeon RX 9060 XT 16GB with 16 GB can run GPT OSS 20B, Qwen1.5 14B, Phi 4, and 1440 other models. 483 models run at excellent quality, and 493 at good quality. Check the compatibility table above for the full list with VRAM usage and estimated speed.

Is AMD Radeon RX 9060 XT 16GB good for AI?

The AMD Radeon RX 9060 XT 16GB has 16 GB of GDDR6, making it very good for running local AI models. It supports 976 models at good quality or better. With 320.0 GB/s memory bandwidth, it delivers reasonable token generation speeds. This is a solid mid-range card for running 7B–14B parameter models at good quality.

How many parameters can AMD Radeon RX 9060 XT 16GB handle?

With 16 GB, the AMD Radeon RX 9060 XT 16GB supports models from 3B to 14B parameters depending on quantization level. At Q4_K_M (the recommended sweet spot), you can fit roughly 26B parameters. 7B models run at high quality (Q5/Q6), while 14B models fit comfortably at Q4.

What quantization should I use on AMD Radeon RX 9060 XT 16GB?

For the best balance of quality and speed on the AMD Radeon RX 9060 XT 16GB, start with Q4_K_M — it preserves ~85% of the original model quality while keeping VRAM usage reasonable. You can step up to Q5_K_M for 7B models to get better quality. For 14B models that just barely fit, Q4_K_M is ideal.

How fast is AMD Radeon RX 9060 XT 16GB for AI inference?

With 320.0 GB/s memory bandwidth, the AMD Radeon RX 9060 XT 16GB achieves approximately 43 tokens/sec on a 7B model at Q4_K_M — that's very fast, well above conversational speed. A 14B model runs at ~21 tok/s. Token generation speed scales inversely with model size — smaller models are significantly faster.

tok/s = (320 GB/s ÷ model GB) × efficiency

Smaller models = faster inference. Memory bandwidth is the main bottleneck for token generation speed.

Estimated speed on AMD Radeon RX 9060 XT 16GB

~15 tok/s
~18 tok/s
~20 tok/s

Real-world results typically within ±20%. Speed depends on quantization kernel, batch size, and software stack.

Learn more about tok/s estimation →

What's the best model for AMD Radeon RX 9060 XT 16GB?

The top-rated models for the AMD Radeon RX 9060 XT 16GB are GPT OSS 20B, Qwen1.5 14B, Phi 4. The best choice depends on your use case: coding assistants benefit from code-tuned models, while general chat works well with instruction-tuned models like Llama or Qwen.

What power supply and cooling does AMD Radeon RX 9060 XT 16GB need?

The AMD Radeon RX 9060 XT 16GB has a TDP of 160 W. A good rule of thumb is to provide at least double the GPU's TDP to cover the rest of the system — that means a 550 W PSU or larger. A mid-tower case with one intake and one rear exhaust is usually sufficient. Keep dust filters clean, as sustained inference generates continuous heat rather than the brief spikes typical of gaming.