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Run LLM Locally

Mistral Nemo 12B Instruct on the A100 80GB

With 80 GB of VRAM, the A100 80GB runs Mistral Nemo 12B Instruct at Q4_K_M entirely on the GPU with an 8K context (about 9.4 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 9.4 GB and fits in the 77.6 GB available, with 68.2 GB to spare.

Your hardware
A100 80GB · 64 GB RAM
Estimated memory
~9.4 GB estimate
VRAM (usable memory)
77.6 GB
GPU only
Yes
CPU/GPU offload
Not required
Generation speed
127–198 tok/s estimate
Largest context in fast memory
128K tokens
Confidence: low

Based on: memory bandwidth (1,935 GB/s) and model size

Memory breakdown

~9.4 GB (9 GB–10 GB) needed · estimate

Fits entirely in VRAM · 68.2 GB left

  • Model weights7 GB
  • KV cache1.3 GB
  • Runtime overhead0.8 GB
  • Safety margin0.4 GB
Assumptions: context 8K tokens · KV cache f16 · llama.cpp (CUDA) · 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 A100 80GB

Mistral Nemo 12B Instruct on A100 80GB + 64 GB RAM · 8K context
Mistral Nemo 12B Instruct Q8_08K~14.9 GB · 87–126 tok/s estimateExcellent
Mistral Nemo 12B Instruct Q6_K8K~12 GB · 104–156 tok/s estimateExcellent
Mistral Nemo 12B Instruct Q5_K_M8K~10.7 GB · 115–175 tok/s estimateExcellent
Mistral Nemo 12B Instruct Q4_K_M8K~9.4 GB · 127–198 tok/s estimateExcellent
Mistral Nemo 12B Instruct IQ4_XS8K~8.7 GB · 136–214 tok/s estimateExcellent
Mistral Nemo 12B Instruct Q3_K_M8K~8.1 GB · 145–231 tok/s estimateExcellent

Alternatives

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

Other models that fit the A100 80GB

Hardware that runs Mistral Nemo 12B Instruct Q4_K_M entirely in memory

Prices and links follow the market you choose.

GeForce RTX 2080 Ti

NVIDIA

CompatibleRuns Mistral Nemo 12B Instruct Q4_K_M entirely in memory

Price not available

Availability unknown

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Affiliate link

Radeon RX 7600 XT

AMD

ExcellentRuns Mistral Nemo 12B Instruct Q4_K_M entirely in memory

Price not available

Availability unknown

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AMD Ryzen AI Max+ 395

Unified memory PC

ExcellentRuns Mistral Nemo 12B Instruct Q4_K_M entirely in memory

Price not available

Availability unknown

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GeForce RTX 3080 (10 GB)

Lowest memory tier

Compatible with limitsRuns Mistral Nemo 12B Instruct Q4_K_M entirely in memory

Price not available

Availability unknown

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No current offer imported for this market: the link opens a marketplace search.

Frequently asked questions

Can the A100 80GB run Mistral Nemo 12B Instruct?
The model needs about 9.4 GB and fits in the 77.6 GB available, with 68.2 GB to spare.
Which quantization should I use on the A100 80GB?
Q8_0 is the highest-precision quantization that fits entirely in VRAM at 8K context. ~14.9 GB / 77.6 GB.
What is the largest context on the A100 80GB?
At Q4_K_M, about 128K 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 (A100 80GB)?
We estimate 127–198 tok/s (estimate, confidence low). Based on: memory bandwidth (1,935 GB/s) and model size.