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NVIDIA GeForce RTX 3080 Ti for local LLMs

Written by Jakub Rusinowski · Last updated

With 12 GB of GDDR6X at 912 GB/s, the RTX 3080 Ti runs 76 catalogued models at Q4_K_M with 8K context. The largest that fits is Qwen 3 14B (~11.1 GB), and the top pick is Cosmos 3 Nano at 51–99 tok/s.

12 GB at 912 GB/s — unusually high bandwidth for the capacity, which suits models that fit in 12 GB and are bandwidth-bound. Used-market only.

Models that run on the RTX 3080 Ti

Q4_K_M, 8K context, 12 GB usable. Ranked by quality and speed.

ModelVRAMSpeed
Cosmos 3 Nano
Cosmos 3
10.5 GB51–99 tok/s
Ministral 3 14B
Ministral 3
9.3 GB35–67 tok/s
DeepSeek R1 Distill Qwen 14B
DeepSeek R1
10.6 GB35–67 tok/s
Mellum2.1 12B Thinking
Mellum2.1
9 GB134–257 tok/s
Gemma 4 12B (Unified)
Gemma 4
8.7 GB42–82 tok/s
Mistral NeMo 12B
Mistral Family
9.4 GB39–76 tok/s
Gemma 3 12B Instruct
Gemma 3
9.1 GB41–78 tok/s
Bielik PL 11B v3.0 Instruct
Bielik
7.4 GB42–81 tok/s
Llama 3.2 Vision 11B
Llama 3.2 Vision
8.5 GB43–83 tok/s
Llama 3.2 11B Vision Instruct
Llama 3.2 Family
8.5 GB43–83 tok/s
Falcon 3 10B Instruct
Falcon 3
8.4 GB44–84 tok/s
Qwen 3.5 9B
Qwen 3.5
6.6 GB55–106 tok/s
Showing 12 of 76

Buy it or rent the same memory

Buy the card, or rent a GPU with the same memory by the hour to try models first.

Speed vs other GPUs

Llama 3.1 8B, Q4_K_M. Estimated ranges. How this is calculated

Specifications

Specs last updated 2026-09-19.

Memory
12 GB GDDR6X
Memory bandwidth
912 GB/s
Memory bus
384-bit
Architecture
Ampere GA102
Series
RTX 30-series
Board power
350 W
Release year
2021
Launch price
$1,199
Compute backends
CUDA
Usable for models
12 GB
Best forused 12 GBvalue inferencehigh bandwidth per pound

Similar GPUs

Frequently asked questions

Can the NVIDIA GeForce RTX 3080 Ti run local LLMs?

Yes. With 12 GB (12 GB usable by a model) it runs 76 of the catalogued models at Q4_K_M with 8K context; the largest is Qwen 3 14B, needing about 11.1 GB.

How fast is the NVIDIA GeForce RTX 3080 Ti for AI inference?

It is estimated to run Llama 3.1 8B at 59–112 tok/s at Q4_K_M. Llama 3.3 70B does not fit: it needs about 44 GB against 12 GB usable. These are modelled estimates from memory bandwidth, not measurements; the methodology page shows the formula.

What LLMs can I run on 12 GB?

Among the best that fit: Cosmos 3 Nano, Ministral 3 14B, DeepSeek R1 Distill Qwen 14B, Mellum2.1 12B Thinking, Gemma 4 12B (Unified).