Graphics cards

Which AI models run on the RTX 2070 (8 GB)?

The RTX 2070 (8 GB) has 8 GB of memory, about 7.0 GB of it usable for a model, and 448 GB/s of memory bandwidth. 32 of the 110 models in our catalog run on it at 4-bit or better.

Data as of 2 November 2026

Compare with other machines
8 GBmemory ~7.0 GB usable for a model
448 GB/sbandwidth, sets the speed
32models run at 4-bit or better
Our pick for this machine Nemotron Nano 9B v2 Q4_K_M · 6.6 of 7.0 GB · ~45 tok/s our est. The largest model on our shortlist of current models that runs at 4-bit or better and 10 tok/s or more.

Models that run on it

ModelBest buildMemorySpeed
Nemotron Nano 9B v29BQ4_K_M6.6 GB~45 tok/s our est.
Qwen2.5 7B Instruct7BQ4_K_M6.6 GB~63 tok/s ModelFit est.
Gemma 3 4B Instruct4BQ8_05.0 GB~66 tok/s ModelFit est.
Ornith 1.0 9B9BQ4_K_M6.7 GB~58 tok/s ModelFit est.
MiMo-V2.6-Distill-Qwen-9B9BQ4_K_M6.9 GB~56 tok/s ModelFit est.
Jebadiah 9B9BQ4_K_M6.9 GB~56 tok/s ModelFit est.
Granite 4.2 8B8.8BQ4_K_M6.1 GB~51 tok/s ModelFit est.
MiniCPM-V 4.5 8B8.7BQ4_K_M6.8 GB~56 tok/s ModelFit est.
LFM2.5 8B-A1B8.3B MoEQ4_K_M6.6 GB~153 tok/s ModelFit est.
Granite 4.1 8B Instruct8BQ4_K_M6.6 GB~49 tok/s ModelFit est.
Mistral 7B Instruct7BQ5_K_M5.9 GB~53 tok/s ModelFit est.
Qwen2.5 Coder 7B7BQ4_K_M6.6 GB~63 tok/s ModelFit est.
DeepSeek-R1 Distill Qwen 7B7BQ4_K_M6.6 GB~63 tok/s ModelFit est.
Gemma 4 E4B4.5BQ4_K_M5.1 GB~81 tok/s ModelFit est.
Qwen3.5 4B Instruct4BQ8_05.4 GB~63 tok/s ModelFit est.
Phi-3 Mini 3.8B3.8BQ4_K_M4.3 GB~77 tok/s our est.
Phi-4 Mini 3.8B3.8BQ8_04.9 GB~63 tok/s ModelFit est.
Granite 4.2 3B3.7BQ4_K_M3.2 GB~111 tok/s ModelFit est.
Ministral 3 3B3.4BQ4_K_M4.1 GB~83 tok/s ModelFit est.
Qwen2.5 3B Instruct3BQ4_K_M3.6 GB~127 tok/s ModelFit est.
Llama 3.2 3B Instruct3BQ4_K_M3.6 GB~108 tok/s ModelFit est.
Granite 4.1 3B Instruct3BQ4_K_M3.0 GB~111 tok/s ModelFit est.
Gemma 4 E2B2.3BQ8_05.7 GB~127 tok/s ModelFit est.
Gemma 2 2B Instruct2BQ4_K_M2.8 GB~123 tok/s ModelFit est.
Qwen3.5 2B Instruct2BQ4_K_M2.8 GB~128 tok/s ModelFit est.
LFM3 1.7B1.73BQ4_K_M2.1 GB~203 tok/s ModelFit est.
Qwen2.5 1.5B Instruct1.5BQ4_K_M2.5 GB~209 tok/s ModelFit est.
Llama 3.2 1B Instruct1BQ4_K_M2.0 GB~234 tok/s ModelFit est.
Gemma 3 1B Instruct1BQ8_02.0 GB~210 tok/s ModelFit est.
Qwen3.5 0.8B Instruct0.8BQ4_K_M1.8 GB~249 tok/s ModelFit est.
Qwen2.5 0.5B Instruct0.5BQ4_K_M1.8 GB~369 tok/s ModelFit est.
SmolLM2 360M0.36BQ4_K_M1.5 GB~242 tok/s ModelFit est.

Speeds come from ModelFit's estimates (CC BY 4.0) where it covers the model, otherwise from our bandwidth formula. Method

Too big for this machine

Ministral 3 8B (7.1 GB), GLM-4-9B-Chat (7.5 GB), Granite Switch 4.1 8B (7.6 GB), Llama 3.1 8B Instruct (7.7 GB), Qwen3 8B (7.7 GB), Gemma 2 9B Instruct (8.2 GB), Qwen3.5 9B Instruct (8.2 GB), NVIDIA Nemotron 3.5 Bolt E4B (9.1 GB), Gemma 4 12B (9.2 GB), Mellum2.1 12B-A2.5B Thinking (9.3 GB), Ministral 3 14B (10.3 GB), Mistral Nemo 12B (10.7 GB) and more.

Questions

What is the best AI model for the RTX 2070 (8 GB)?

Nemotron Nano 9B v2 at Q4_K_M: the largest model on our shortlist of current models that runs at 4-bit or better at a usable speed (about 45 tok/s, our est.).

How much memory can a model use on the RTX 2070 (8 GB)?

About 7.0 GB of the 8 GB.

How fast is the RTX 2070 (8 GB) for local LLMs?

Decode speed is limited by memory bandwidth: 448 GB/s. A model that reads 10 GB per token runs at under 45 tokens per second.