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Llama 3.1 8B Instruct on the RX 7900 XT

With 20 GB of VRAM, the RX 7900 XT runs Llama 3.1 8B Instruct at Q4_K_M entirely on the GPU with an 8K context (about 6.7 GB needed). At Q8_0 it fits entirely.

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Llama 3.1 8B Instruct

Q4_K_M · 8K context

Excellent

The model needs about 6.7 GB and fits in the 19.4 GB available, with 12.7 GB to spare.

Your hardware
RX 7900 XT 20 GB · 64 GB RAM
Estimated memory
~6.7 GB estimate
VRAM (usable memory)
19.4 GB
GPU only
Yes
CPU/GPU offload
Not required
Generation speed
78–118 tok/s estimate
Largest context in fast memory
104K tokens
Confidence: low

Based on: memory bandwidth (800 GB/s) and model size

Memory breakdown

~6.7 GB (6.3 GB–7.2 GB) needed · estimate

Fits entirely in VRAM · 12.7 GB left

  • Model weights4.6 GB
  • KV cache1 GB
  • Runtime overhead0.8 GB
  • Safety margin0.3 GB
Assumptions: context 8K tokens · KV cache f16 · llama.cpp (ROCm) · flash attention on · weights = real file size

EstimateData updated 24 days agoSource: Run LLM Locally engine, Hugging Face config.json + model card

What makes this estimate less reliable

  • no benchmark for this hardware and model yet

Other quantizations on the RX 7900 XT

Llama 3.1 8B Instruct on RX 7900 XT + 64 GB RAM · 8K context
Llama 3.1 8B Instruct Q8_08K~10.2 GB · 52–75 tok/s estimateExcellent
Llama 3.1 8B Instruct Q6_K8K~8.3 GB · 63–93 tok/s estimateExcellent
Llama 3.1 8B Instruct Q5_K_M8K~7.5 GB · 70–104 tok/s estimateExcellent
Llama 3.1 8B Instruct Q4_K_M8K~6.7 GB · 78–118 tok/s estimateExcellent
Llama 3.1 8B Instruct IQ4_XS8K~6.2 GB · 83–127 tok/s estimateExcellent
Llama 3.1 8B Instruct Q3_K_M8K~5.9 GB · 89–137 tok/s estimateExcellent

Alternatives

GPUs that run Llama 3.1 8B Instruct Q4_K_M entirely in VRAM

Other models that fit the RX 7900 XT

Where to buy a RX 7900 XT

Prices and links follow the market you choose.

Radeon RX 7900 XT

20 GB GDDR6 · 800 GB/s · 315 W

ExcellentRuns Llama 3.1 8B Instruct Q4_K_M entirely in memory

Price not available

Availability unknown

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Frequently asked questions

Can the RX 7900 XT run Llama 3.1 8B Instruct?
The model needs about 6.7 GB and fits in the 19.4 GB available, with 12.7 GB to spare.
Which quantization should I use on the RX 7900 XT?
Q8_0 is the highest-precision quantization that fits entirely in VRAM at 8K context. ~10.2 GB / 19.4 GB.
What is the largest context on the RX 7900 XT?
At Q4_K_M, about 104K tokens fit entirely in VRAM with an f16 KV cache. A q8_0 KV cache roughly doubles that.
How fast is Llama 3.1 8B Instruct (RX 7900 XT)?
We estimate 78–118 tok/s (estimate, confidence low). Based on: memory bandwidth (800 GB/s) and model size.