NVIDIA GeForce RTX 3070 for local LLMs
Written by Jakub Rusinowski · Last updated
With 8 GB at 448 GB/s, the RTX 3070 runs 55 catalogued models at Q4_K_M with 8K context. The largest that fits is K2 Horizon 7B (~7.4 GB), and the top pick is Qwen 3.5 9B at 30–58 tok/s.
A popular used GPU at $150–200. 8 GB VRAM is tight but sufficient for 7–8B models at Q4. Good bandwidth for the price. Upgrade path: RTX 3090 for 3× the VRAM.
Models that run on the RTX 3070
Q4_K_M, 8K context, 8 GB usable. Ranked by quality and speed.
| Model | Memory · marker = 8 GB | VRAM | Speed |
|---|---|---|---|
| Qwen 3.5 9B Qwen 3.5 | 6.5 GB | 30–58 tok/s | |
| GLM-4 9B GLM-4.7 / GLM-Z1 | 6.2 GB | 26–50 tok/s | |
| GLM-4.6V-Flash 9B GLM-4.6V | 6.2 GB | 26–50 tok/s | |
| EuroLLM 9B EuroLLM | 6.2 GB | 26–50 tok/s | |
| InternLM 3 8B Instruct InternLM 3 | 6.5 GB | 30–58 tok/s | |
| LFM2.5-8B-A1B LFM2.5 | 5.8 GB | 71–136 tok/s | |
| Qwen 3 8B Qwen 3 | 7 GB | 28–54 tok/s | |
| Aya Expanse 8B Aya Expanse | 6.7 GB | 29–56 tok/s | |
| Ministral 8B Ministral | 6.9 GB | 29–55 tok/s | |
| Gemma 4 E4B Gemma 4 | 5.6 GB | 29–56 tok/s | |
| Cogito v1 8B Cogito v1 | 6.7 GB | 29–56 tok/s | |
| Granite 4.1 8B IBM Granite 4.1 | 5.6 GB | 29–56 tok/s |
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.
or compare on Vast.ai from $0.35/hr (typical low · varies)
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Speed vs other GPUs
Llama 3.1 8B, Q4_K_M. Estimated ranges. How this is calculated
Specifications
Specs last updated 2026-07-12.
- Memory
- 8 GB
- Memory bandwidth
- 448 GB/s
- Architecture
- Ampere GA104
- Series
- RTX 30-series
- Board power
- 220 W
- Release year
- 2020
- Launch price
- $499
- Usable for models
- 8 GB
Similar GPUs
Frequently asked questions
Can the NVIDIA GeForce RTX 3070 run local LLMs?
Yes. With 8 GB (8 GB usable by a model) it runs 55 of the catalogued models at Q4_K_M with 8K context; the largest is K2 Horizon 7B, needing about 7.4 GB.
How fast is the NVIDIA GeForce RTX 3070 for AI inference?
It is estimated to run Llama 3.1 8B at 32–61 tok/s at Q4_K_M. Llama 3.3 70B does not fit: it needs about 44 GB against 8 GB usable. These are modelled estimates from memory bandwidth, not measurements; the methodology page shows the formula.
What LLMs can I run on 8 GB?
Among the best that fit: Qwen 3.5 9B, GLM-4 9B, GLM-4.6V-Flash 9B, EuroLLM 9B, InternLM 3 8B Instruct. The quickest start is Ollama: ollama run llama3.1:8b.
Keep going
Can I run it on the RTX 3070?
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