AMDRDNA 3

Best AI Models for AMD Radeon RX 7800 XT (16.0GB)

VRAM:16.0 GB GDDR6·Bandwidth:624.0 GB/s·Stream Processors:3,840·TDP:263W·MSRP:$499

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 7800 XT Run?

110 models · 46 excellent · 28 good

Showing compatibility for AMD Radeon RX 7800 XT

LLM models compatible with AMD Radeon RX 7800 XT — ranked by performance
ModelVRAMGrade
Q4_K_M·53.2 t/s tok/s·RUNS WELL
7.0 GBA81
Q4_K_M·48.9 t/s tok/s·131K ctx·RUNS WELL
7.7 GBA79
Q4_K_M·48.9 t/s tok/s·131K ctx·RUNS WELL
7.7 GBA79
Q4_K_M·43.6 t/s tok/s·RUNS WELL
8.6 GBA77
Qwen3 8B8.2B
Q4_K_M·67.8 t/s tok/s·41K ctx·RUNS GREAT
5.5 GBS85
Q4_K_M·60.3 t/s tok/s·262K ctx·RUNS WELL
6.2 GBA84
Falcon 11B11.1B
Q4_K_M·51.1 t/s tok/s·8K ctx·RUNS WELL
7.3 GBA80
Q4_K_M·61.4 t/s tok/s·8K ctx·RUNS WELL
6.1 GBA84
DeepSeek R1 0528 Qwen3 8B8.2B
Q4_K_M·67.8 t/s tok/s·131K ctx·RUNS GREAT
5.5 GBS85
Q4_K_M·70.6 t/s tok/s·131K ctx·RUNS GREAT
5.3 GBS86
Q4_K_M·70.4 t/s tok/s·131K ctx·RUNS GREAT
5.3 GBS86
Qwen1.5 7B7.7B
Q4_K_M·62.3 t/s tok/s·33K ctx·RUNS WELL
6.0 GBA84
Q4_K_M·75.0 t/s tok/s·33K ctx·RUNS GREAT
5.0 GBS86
Q4_K_M·65.1 t/s tok/s·66K ctx·RUNS WELL
5.8 GBA84
Q4_K_M·76.1 t/s tok/s·33K ctx·RUNS GREAT
4.9 GBS87
Hermes 3 Llama 3.1 8B8.0B
Q4_K_M·69.5 t/s tok/s·131K ctx·RUNS GREAT
5.4 GBS86

AMD Radeon RX 7800 XT Specifications

Brand
AMD
Architecture
RDNA 3
VRAM
16.0 GB GDDR6
Memory Bandwidth
624.0 GB/s
Stream Processors
3,840
FP16 Performance
74.70 TFLOPS
TDP
263W
Release Date
2023-09-06
MSRP
$499

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 GigaChat 20B A3B Base, the compute-bound phase that reads your prompt before the first reply token appears.

2,737.2tok/s prefill

Short chat

187 ms

512 tok prompt

Long chat

1.5 s

4,096 tok prompt

Document / codebase

12.0 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 GigaChat 20B A3B Base at ~29.9 tok/s decode.

Tokens per watt

0.11tok/s per W

Higher is better.

$ per tok/s (MSRP)

$16.69

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 7800 XT

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

Frequently Asked Questions

Can AMD Radeon RX 7800 XT run Phi 4?

Yes, the AMD Radeon RX 7800 XT with 16 GB can run Phi 4, Qwen1.5 14B, GPT OSS 20B, and 1440 other models. 891 models run at excellent quality, and 301 at good quality. Check the compatibility table above for the full list with VRAM usage and estimated speed.

Is AMD Radeon RX 7800 XT good for AI?

The AMD Radeon RX 7800 XT has 16 GB of GDDR6, making it very good for running local AI models. It supports 1192 models at good quality or better. With 624.0 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 7800 XT handle?

With 16 GB, the AMD Radeon RX 7800 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 7800 XT?

For the best balance of quality and speed on the AMD Radeon RX 7800 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 7800 XT for AI inference?

With 624.0 GB/s memory bandwidth, the AMD Radeon RX 7800 XT achieves approximately 83 tokens/sec on a 7B model at Q4_K_M — that's very fast, well above conversational speed. A 14B model runs at ~42 tok/s. Token generation speed scales inversely with model size — smaller models are significantly faster.

tok/s = (624 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 7800 XT

~39 tok/s
~36 tok/s
~28 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 7800 XT?

The top-rated models for the AMD Radeon RX 7800 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 7800 XT need?

The AMD Radeon RX 7800 XT has a TDP of 263 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.