Skip to content
Run LLM Locally

Mistral Nemo 12B Instruct on the RTX 3080

Mistral Nemo 12B Instruct at Q4_K_M needs about 9.4 GB; the RTX 3080 has 10 GB: it fits with almost no margin at 8K context. At Q8_0 it does not fit in VRAM.

ShareFacebookXWhatsAppLinkedInEmail

Mistral Nemo 12B Instruct

Q4_K_M · 8K context

Compatible with limits

The model needs about 9.4 GB (up to 10 GB) for 9.7 GB available: it fits, but with almost no margin. Use a shorter context or a smaller quantization if loading fails.

Your hardware
RTX 3080 10 GB · 64 GB RAM
Estimated memory
~9.4 GB estimate
VRAM (usable memory)
9.7 GB
GPU only
Yes
CPU/GPU offload
Not required
Generation speed
61–86 tok/s estimate
Largest context in fast memory
9K tokens
Confidence: low

Based on: memory bandwidth (760 GB/s) and model size

Memory breakdown

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

Fits entirely in VRAM · 0.2 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 RTX 3080

Mistral Nemo 12B Instruct on RTX 3080 + 64 GB RAM · 8K context
Mistral Nemo 12B Instruct Q8_08K~14.9 GB · 4–7.5 tok/s estimateCPU/GPU offload
Mistral Nemo 12B Instruct Q6_K8K~12 GB · 8–15 tok/s estimateCPU/GPU offload
Mistral Nemo 12B Instruct Q5_K_M8K~10.7 GB · 15–28 tok/s estimateCPU/GPU offload
Mistral Nemo 12B Instruct Q4_K_M8K~9.4 GB · 61–86 tok/s estimateCompatible with limits
Mistral Nemo 12B Instruct IQ4_XS8K~8.7 GB · 67–94 tok/s estimateCompatible
Mistral Nemo 12B Instruct Q3_K_M8K~8.1 GB · 72–102 tok/s estimateExcellent

Alternatives

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

Other models that fit the RTX 3080

Where to buy a RTX 3080

Prices and links follow the market you choose.

GeForce RTX 3080 (10 GB)

10 GB GDDR6X · 760 GB/s · 320 W

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

Price not available

Availability unknown

View on amazon.com

Affiliate link

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

Frequently asked questions

Can the RTX 3080 run Mistral Nemo 12B Instruct?
The model needs about 9.4 GB (up to 10 GB) for 9.7 GB available: it fits, but with almost no margin. Use a shorter context or a smaller quantization if loading fails.
Which quantization should I use on the RTX 3080?
Q4_K_M is the highest-precision quantization that fits entirely in VRAM at 8K context. ~9.4 GB / 9.7 GB.
What is the largest context on the RTX 3080?
At Q4_K_M, about 9K 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 (RTX 3080)?
We estimate 61–86 tok/s (estimate, confidence low). Based on: memory bandwidth (760 GB/s) and model size.