NVIDIA GeForce RTX 5070 Ti — Local LLM Performance & Compatibility

Written by Jakub Rusinowski · Last updated July 12, 2026

Best value in the RTX 50-series. 16 GB VRAM matches RTX 5080 for model compatibility at a lower price.

Technical Specifications

VRAM16 GB
Memory Bandwidth896 GB/s
TDP300 W
ArchitectureBlackwell GB205
Release Year2025
MSRP at Launch$749
Inference Speed (Llama 3.1 8B Q4_K_M)70–145 tok/s (estimated)
Inference Speed (Llama 3.3 70B Q4_K_M)Does not fit — needs ~44 GB of 16 GB usable
Buy This HardwareNVIDIA GeForce RTX 5070 Ti 16GB — 16 GB VRAM · 300 W board powerDeploy in the Cloud NowRTX 4090 on RunPod — from $0.34/hr · rate checked 2026-07

or compare on Vast.ai from $0.35/hr (typical low · varies)

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NVIDIA GeForce RTX 5070 Ti 16GB
16 GB VRAM · 300 W board power
2026 prices are volatile — check the current listing.
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LLMs Compatible with 16 GB VRAM

All models below run comfortably in 16 GB VRAM with Q4_K_M quantization.

Llama 3.1 FamilyLlama 3.1 8B Instruct · 6 GB VRAM · Q4_K_M · ollama run llama3.1
Llama 3.2 FamilyLlama 3.2 11B Vision Instruct · 7 GB VRAM · Q4_K_M · llama-3-2
Qwen 3Qwen 3 14B · 10 GB VRAM · Q4_K_M · ollama run qwen3:14b
Gemma 3Gemma 3 12B Instruct · 8 GB VRAM · Q4_K_M · ollama run gemma3:12b
Phi-4 FamilyPhi-4 (14B) · 9 GB VRAM · Q4_K_M · ollama run phi4
Phi-4 MiniPhi-4 Mini (3.8B) · 3 GB VRAM · Q4_K_M · ollama run phi4-mini
Mistral FamilyMistral Small 3 (24B) · 15 GB VRAM · Q4_K_M · ollama run mistral-small
DeepSeek R1DeepSeek R1 Distill Qwen 14B · 9 GB VRAM · Q4_K_M · ollama run deepseek-r1:14b

Best Use Cases

Quick Start with Ollama

Install Ollama then run the recommended model for this GPU:

ollama run llama3.1:8b

FAQ

Can the NVIDIA GeForce RTX 5070 Ti run local LLMs?

Yes — the NVIDIA GeForce RTX 5070 Ti has 16 GB VRAM and runs Best value in the RTX 50-series. 16 GB VRAM matches RTX 5080 for model compatibility at a lower price.

How fast is the NVIDIA GeForce RTX 5070 Ti for AI inference?

The NVIDIA GeForce RTX 5070 Ti is estimated to run Llama 3.1 8B at 70–145 tok/s with Q4_K_M quantization. Llama 3.3 70B does not fit: it needs about 44 GB against 16 GB usable. These are modelled estimates, not measurements — see /en/methodology.

What LLMs can I run on 16 GB VRAM?

With 16 GB you can run: Llama 3.1 Family, Llama 3.2 Family, Qwen 3, Gemma 3, Phi-4 Family. Use Ollama for the easiest setup: ollama run llama3.1:8b.

Can I Run It? — NVIDIA GeForce RTX 5070 Ti

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