Best Local LLM for the RTX 5070 Ti
The RTX 5070 Ti's 16 GB of GDDR7 comfortably runs 13B models at full precision and the 27B class at Q4, with Gemma 3 27B as the largest catalog fit. It is the cheapest 16 GB card in NVIDIA's current stack, which makes it our best-value pick for local AI.
Model data last verified on June 27, 2026. All VRAM figures are for the Q4 quantization Ollama serves by default.
The hardware in question
NVIDIA RTX 5070 Ti 16GB
~$999
16 GB GDDR7, 256-bit bus, 300W TDP, 8,960 CUDA cores
Best current-gen value: 16 GB GDDR7 for 7B: 34B at a mid-tier price
Full entry in the hardware guideEvery model that fits 16 GB of VRAM
12 of the 16 models in our verified catalog fit this budget at Q4, sorted with the largest fit first. Click any model for its full spec sheet, hardware cross-reference and run commands.
| Model | Params | Quant | Min VRAM | Context | Fit |
|---|---|---|---|---|---|
| Gemma 3 27B | 27B | Q4 | 15 GB | 128K | 1 GB free |
| OpenAI gpt-oss-20bHistoric first | 20B total / 3.6B active (MoE) | Q4 | 12 GB | 128K | 4 GB free |
| Gemma 4 12BBest for fine-tuning | 12B | Q4 | 8 GB | 256K | 8 GB free |
| Phi-4 14BBest small coder | 14B | Q4 | 8 GB | 16K | 8 GB free |
| Mistral Nemo 12B | 12B | Q4 | 7 GB | 128K | 9 GB free |
| Llama 3.1 8B | 8B | Q4 | 5 GB | 128K | 11 GB free |
| Qwen3 8BMost popular | 8B | Q4 | 5 GB | 128K | 11 GB free |
| DeepSeek R1 Distill 8BMost private | 8B | Q4 | 5 GB | 128K | 11 GB free |
| Mistral 7B v0.3 | 7B | Q4 | 4 GB | 32K | 12 GB free |
| Qwen 2.5 Coder 7B | 7B | Q4 | 4 GB | 128K | 12 GB free |
| Gemma 3 4B | 4B | Q4 | 3 GB | 128K | 13 GB free |
| Llama 3.2 3BFastest | 3B | Q4 | 2 GB | 128K | 14 GB free |
Run the top picks with Ollama
One command each. Ollama pulls the Q4_K_M build by default and exposes an OpenAI-compatible endpoint at localhost:11434/v1.
ollama run gemma3:27bollama run gpt-oss:20bollama run gemma4:12bFrequently asked questions
Is the RTX 5070 Ti good for local AI?
Yes, it is our best-value pick. You get 16 GB of GDDR7 at the lowest price in NVIDIA's current lineup (around $999), a moderate 300W draw, and Blackwell support for the newest FP4 quantization formats.
What is the biggest model the RTX 5070 Ti can run?
Gemma 3 27B at Q4, which needs about 15 GB. It comfortably runs 13B models at full precision and everything below that with headroom to spare.
RTX 5070 Ti or RTX 5080 for local LLMs?
Both are 16 GB, so they run the same models. The RTX 5080 (around $1,250) has more memory bandwidth, but the 5070 Ti delivers most of the real-world inference speed at a lower price and a lower 300W draw.
Can the RTX 5070 Ti run a 70B model?
No. Its 16 GB cap means 70B is out of reach without heavy offload; Llama 3.3 70B needs about 48 GB at Q4. The 27B class is the practical ceiling on this card.
Different budget or use case?
The faceted model browser combines VRAM, family, license and task filters over the same verified catalog.