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Run LLM Locally

Mistral Nemo 12B Instruct on the RX 9070

With 16 GB of VRAM, the RX 9070 runs Mistral Nemo 12B Instruct at Q4_K_M entirely on the GPU with an 8K context (about 9.5 GB needed). At Q8_0 it fits entirely.

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Mistral Nemo 12B Instruct

Q4_K_M · 8K context

Excellent

The model needs about 9.5 GB and fits in the 15.5 GB available, with 6 GB to spare.

Your hardware
RX 9070 16 GB · 64 GB RAM
Estimated memory
~9.5 GB estimate
VRAM (usable memory)
15.5 GB
GPU only
Yes
CPU/GPU offload
Not required
Generation speed
46–66 tok/s estimate
Largest context in fast memory
44K tokens
Confidence: low

Based on: memory bandwidth (640 GB/s) and model size

Memory breakdown

~9.5 GB (9 GB–10 GB) needed · estimate

Fits entirely in VRAM · 6 GB left

  • Model weights7 GB
  • KV cache1.3 GB
  • Runtime overhead0.8 GB
  • Safety margin0.5 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 9070

Mistral Nemo 12B Instruct on RX 9070 + 64 GB RAM · 8K context
Mistral Nemo 12B Instruct Q8_08K~14.9 GB · 29–41 tok/s estimateCompatible with limits
Mistral Nemo 12B Instruct Q6_K8K~12 GB · 36–52 tok/s estimateExcellent
Mistral Nemo 12B Instruct Q5_K_M8K~10.7 GB · 40–58 tok/s estimateExcellent
Mistral Nemo 12B Instruct Q4_K_M8K~9.5 GB · 46–66 tok/s estimateExcellent
Mistral Nemo 12B Instruct IQ4_XS8K~8.8 GB · 49–72 tok/s estimateExcellent
Mistral Nemo 12B Instruct Q3_K_M8K~8.1 GB · 53–78 tok/s estimateExcellent

Alternatives

GPUs that run Mistral Nemo 12B Instruct Q4_K_M entirely in VRAM

Other models that fit the RX 9070

Where to buy a RX 9070

Prices and links follow the market you choose.

Radeon RX 9070

16 GB GDDR6 · 640 GB/s · 220 W

ExcellentRuns Mistral Nemo 12B Instruct Q4_K_M entirely in memory

Price not available

Availability unknown

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Frequently asked questions

Can the RX 9070 run Mistral Nemo 12B Instruct?
The model needs about 9.5 GB and fits in the 15.5 GB available, with 6 GB to spare.
Which quantization should I use on the RX 9070?
Q8_0 is the highest-precision quantization that fits entirely in VRAM at 8K context. ~14.9 GB / 15.5 GB.
What is the largest context on the RX 9070?
At Q4_K_M, about 44K tokens fit entirely in VRAM with an f16 KV cache. A q8_0 KV cache roughly doubles that.
How fast is Mistral Nemo 12B Instruct (RX 9070)?
We estimate 46–66 tok/s (estimate, confidence low). Based on: memory bandwidth (640 GB/s) and model size.