AMDRDNA 4

Best AI Models for AMD Radeon RX 9070 XT (16.0GB)

VRAM:16.0 GB GDDR6·Bandwidth:640.0 GB/s·Stream Processors:4,096·TDP:304W·MSRP:$599

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 9070 XT Run?

92 models · 15 good

Showing compatibility for AMD Radeon RX 9070 XT

LLM models compatible with AMD Radeon RX 9070 XT — ranked by performance
ModelVRAMGrade
Yi 6B6.1B
Q4_K_M·86.5 t/s tok/s·4K ctx·EASY RUN
4.1 GBC40
Phi 22.8B
Q4_K_M·133.3 t/s tok/s·2K ctx·EASY RUN
2.6 GBC34
Q4_K_M·166.0 t/s tok/s·131K ctx·EASY RUN
2.1 GBC32
Qwen2.5 Coder 3B3.1B
Q4_K_M·157.8 t/s tok/s·33K ctx·EASY RUN
2.2 GBC32
SmolLM3 3B3.1B
Q4_K_M·153.0 t/s tok/s·66K ctx·EASY RUN
2.3 GBC32
Q4_K_M·429.3 t/s tok/s·131K ctx·EASY RUN
0.8 GBD28
Phi 4 Mini Reasoning3.8B
Q4_K_M·122.6 t/s tok/s·131K ctx·EASY RUN
2.9 GBC34
Q4_K_M·140.2 t/s tok/s·131K ctx·EASY RUN
2.5 GBC33
Q4_K_M·203.5 t/s tok/s·8K ctx·EASY RUN
1.7 GBC31
Q4_K_M·348.5 t/s tok/s·2K ctx·EASY RUN
1.0 GBD28
Starcoder2 3B3.0B
Q4_K_M·161.5 t/s tok/s·16K ctx·EASY RUN
2.2 GBC32
Gemma 3 1B IT1000M
Q4_K_M·533.3 t/s tok/s·33K ctx·EASY RUN
0.7 GBD27
Phi 3.5 MoE Instruct41.9B
IQ2_M·23.9 t/s tok/s·131K ctx·POOR FIT
14.7 GBC44
Qwen3 32B32.8B
Q3_K_S·23.5 t/s tok/s·41K ctx·POOR FIT
15.0 GBC36
Q4_K_M·1955.6 t/s tok/s·EASY RUN
0.2 GBD26
Q4_K_M·23.7 t/s tok/s·33K ctx·POOR FIT
14.9 GBC40

AMD Radeon RX 9070 XT Specifications

Brand
AMD
Architecture
RDNA 4
VRAM
16.0 GB GDDR6
Memory Bandwidth
640.0 GB/s
Stream Processors
4,096
FP16 Performance
48.70 TFLOPS
TDP
304W
Release Date
2025-03-06
MSRP
$599

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.

GPUs to Consider Over AMD Radeon RX 9070 XT

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

Frequently Asked Questions

Can AMD Radeon RX 9070 XT run Phi 4?

Yes, the AMD Radeon RX 9070 XT with 16 GB can run Phi 4, Qwen1.5 14B, GPT OSS 20B, and 1192 other models. 4 models run at excellent quality, and 178 at good quality. Check the compatibility table above for the full list with VRAM usage and estimated speed.

Is AMD Radeon RX 9070 XT good for AI?

The AMD Radeon RX 9070 XT has 16 GB of GDDR6, making it very good for running local AI models. It supports 182 models at good quality or better. With 640.0 GB/s memory bandwidth, it delivers solid 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 9070 XT handle?

With 16 GB, the AMD Radeon RX 9070 XT 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 9070 XT?

For the best balance of quality and speed on the AMD Radeon RX 9070 XT, 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 9070 XT for AI inference?

With 640.0 GB/s memory bandwidth, the AMD Radeon RX 9070 XT achieves approximately 78 tokens/sec on a 7B model at Q4_K_M — that's very fast, well above conversational speed. A 14B model runs at ~39 tok/s. Token generation speed scales inversely with model size — smaller models are significantly faster.

tok/s = (640 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 9070 XT

~37 tok/s
~34 tok/s
~27 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 9070 XT?

The top-rated models for the AMD Radeon RX 9070 XT are Phi 4, Qwen1.5 14B, GPT OSS 20B. 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 9070 XT need?

The AMD Radeon RX 9070 XT has a TDP of 304 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 650 W PSU or larger. At this power level, a high-airflow case matters: aim for at least two front intake fans and one rear exhaust, with tidy cabling so hot air isn't trapped around the card. LLM inference sustains full GPU load continuously — longer and more consistently than most gaming workloads — so also make sure your CPU cooler can keep up under combined load.