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AMD Radeon RX 7800 XT for local LLMs

Written by Jakub Rusinowski · Last updated

With 16 GB at 624 GB/s, the RX 7800 XT runs 75 catalogued models at Q4_K_M with 8K context. The largest that fits is OLMo 2 13B Instruct (~15.8 GB), and the top pick is EuroLLM 22B at 16–34 tok/s.

16 GB VRAM at an excellent AMD price point. Works via ROCm on Linux or Vulkan/DirectML on Windows.

Models that run on the RX 7800 XT

Q4_K_M, 8K context, 16 GB usable. Ranked by quality and speed.

ModelVRAMSpeed
EuroLLM 22B
EuroLLM
14.1 GB16–34 tok/s
GPT-OSS 20B
GPT-OSS
13.8 GB66–137 tok/s
InternLM 3 20B Instruct
InternLM 3
12.9 GB17–36 tok/s
Cosmos 3 Nano
Cosmos 3
10.5 GB34–71 tok/s
StarCoder 2 15B
StarCoder 2
10.8 GB23–48 tok/s
Qwen 3 14B
Qwen 3
11.1 GB23–47 tok/s
Phi-4 (14B)
Phi-4 Family
10.9 GB23–47 tok/s
Cogito v1 14B
Cogito v1
10.9 GB23–48 tok/s
Ministral 3 14B
Ministral 3
9.3 GB23–49 tok/s
DeepSeek R1 Distill Qwen 14B
DeepSeek R1
10.6 GB24–49 tok/s
Gemma 4 12B (Unified)
Gemma 4
8 GB26–55 tok/s
Bielik PL 11B v3.0 Instruct
Bielik
7.4 GB28–59 tok/s
Showing 12 of 75

Buy it or rent the same memory

Buy the card, or rent a GPU with the same memory by the hour to try models first.

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AMD Radeon RX 7800 XT 16GB
16 GB VRAM · 263 W board power
2026 prices are volatile — check the current listing.

Speed vs other GPUs

Llama 3.1 8B, Q4_K_M. Estimated ranges. How this is calculated

Specifications

Specs last updated 2026-09-29.

Memory
16 GB
Memory bandwidth
624 GB/s
Architecture
RDNA 3 Navi 32
Series
RX 7000-series
Board power
263 W
Release year
2023
Launch price
$499
Usable for models
16 GB
Best for14B modelsAMD mid-rangeprice/performance
Recommended first model (Ollama)

Similar GPUs

Frequently asked questions

Can the AMD Radeon RX 7800 XT run local LLMs?

Yes. With 16 GB (16 GB usable by a model) it runs 75 of the catalogued models at Q4_K_M with 8K context; the largest is OLMo 2 13B Instruct, needing about 15.8 GB.

How fast is the AMD Radeon RX 7800 XT for AI inference?

It is estimated to run Llama 3.1 8B at 39–81 tok/s at Q4_K_M. Llama 3.3 70B does not fit: it needs about 44 GB against 16 GB usable. These are modelled estimates from memory bandwidth, not measurements; the methodology page shows the formula.

What LLMs can I run on 16 GB?

Among the best that fit: EuroLLM 22B, GPT-OSS 20B, InternLM 3 20B Instruct, Cosmos 3 Nano, StarCoder 2 15B. The quickest start is Ollama: ollama run qwen3:14b.