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Can the AMD Radeon RX 7900 XTX run Phi-3 Medium (14B)?

74 ptsGreat (A) · 74 of 100 points: Model quality 20.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 13.5/15

Yes, it runs well

Runs well. At Q6_K it needs about 14.1 GB of 24.0 GB usable, with an estimated speed of 50.4 tok/s.

Best quant
Q6_K
Generation speed
50.4 tok/s
Prompt processing
5,454 tok/s
First token (1K prompt)
0.3 s
Largest safe context
4K

Download Phi-3 Medium (14B)

Recommended for the AMD Radeon RX 7900 XTX: Q6_K. Every other quantization has its own download link in the table below.

Quickest · Ollama

One command downloads a ready-to-run version and starts a chat.

ollama run phi3:14b-medium-4k-instruct-q6_K

Get Ollama at ollama.com/download (opens in a new tab) · model page (opens in a new tab)

Quantized files · GGUF

Works in LM Studio, llama.cpp, Jan and Ollama. No sign-in needed.

Download the Q6_K file (opens in a new tab)

huggingface.co/bartowski/Phi-3-medium-4k-instruct-GGUF (opens in a new tab)

ollama run hf.co/bartowski/Phi-3-medium-4k-instruct-GGUF:Q6_K

Original weights · Hugging Face

Full-precision files from Microsoft, for fine-tuning, vLLM, Transformers.

huggingface.co/microsoft/Phi-3-medium-4k-instruct (opens in a new tab)

No sign-in needed.

Official repo · GitHub

Reference code, inference scripts and docs from Microsoft. The weights themselves download from Hugging Face.

github.com/microsoft/PhiCookBook (opens in a new tab)

git clone https://github.com/microsoft/PhiCookBook

Microsoft’s official Phi cookbook: setup, inference and fine-tuning guides.

How the A grade is scored

Every result gets up to 100 points from four parts. The points decide the letter grade.

Model qualityEditorial quality tier of the model, scaled by the quantization or precision used.20.5 / 45
Memory fitFull marks when everything sits in GPU or unified memory; fewer when part spills to system RAM.25.0 / 25
SpeedGeneration speed against a 40 tokens/s target for LLMs, or render time against a target for image and video.15.0 / 15
Memory useRewards using the memory you have, so a bigger, better variant beats a tiny one that leaves most memory idle.13.5 / 15
Total74.0 / 10074 ptsGreat (A) · 74 of 100 points: Model quality 20.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 13.5/15

Grade scale: S 85+ · A 72+ · B 58+ · C 42+ · D 25+ · F under 25 points.

Every quantization on the AMD Radeon RX 7900 XTX

Quant Memory needed Available Speed Fit Grade · points Download
Q2_K 8.2 GB 24.0 GB 119 tok/s Runs well 62 ptsGood (B) · 62 of 100 points: Model quality 14.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 7.9/15 GGUF (opens in a new tab)
Q3_K_M 9.5 GB 24.0 GB 94.0 tok/s Runs well 66 ptsGood (B) · 66 of 100 points: Model quality 17.4/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 9.1/15 GGUF (opens in a new tab)
Q4_K_M 11.2 GB 24.0 GB 72.7 tok/s Runs well 70 ptsGood (B) · 70 of 100 points: Model quality 19.7/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 10.7/15 GGUF (opens in a new tab)
Q5_K_M 12.6 GB 24.0 GB 60.1 tok/s Runs well 72 ptsGreat (A) · 72 of 100 points: Model quality 20.1/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 12.1/15 GGUF (opens in a new tab)
Q6_K 14.1 GB 24.0 GB 50.4 tok/s Runs well 74 ptsGreat (A) · 74 of 100 points: Model quality 20.5/45, Memory fit 25.0/25, Speed 15.0/15, Memory use 13.5/15 GGUF (opens in a new tab)
Q8_0 17.4 GB 24.0 GB 37.0 tok/s Runs well 75 ptsGreat (A) · 75 of 100 points: Model quality 20.7/45, Memory fit 25.0/25, Speed 14.4/15, Memory use 15.0/15 GGUF (opens in a new tab)
F16 30.6 GB 24.0 GB 4.6 tok/s Runs with offload 50 ptsUsable (C) · 50 of 100 points: Model quality 20.7/45, Memory fit 10.0/25, Speed 5.1/15, Memory use 15.0/15 Original weights (opens in a new tab)

Memory figures assume 4K of context. Longer conversations or documents grow the KV cache.

Other hardware that runs it

Estimates come from published hardware specs and our open formulas, not from running the model on your machine. Real speed varies with runtime, drivers and settings. Numbers marked “Measured” come from a linked benchmark.