NVIDIA
NVIDIA GeForce RTX 4070 Ti Super
16 GB · 672 GB/s
$779
Updated 2026-03-01
The NVIDIA GeForce RTX 4070 Ti Super with 16 GB GDDR6X VRAM can handle 12 AI models across chat, coding, ai_coding. Best performance: Llama 3.2 1B Instruct at 190 tok/s (excellent). For AI coding workflows, it supports the Capable AI Coding tier — handles single model workflows well. Current price: approximately $779.
— OwnRig methodology, data updated 2026-03-01
Builder Capability: Capable AI Coding
Runs 16-22B coding models comfortably, or 32B at reduced quality. Handles single model workflows well.
Specifications
Memory
- Capacity
- 16 GB
- Bandwidth
- 672 GB/s
- Type
- GDDR6X
Power & Form Factor
- TDP
- 285W
- Rec. PSU
- 700W
- Slots
- 2-slot
- Length
- 300mm
Compatible Models
| Model | Quant | Speed | Rating | Notes |
|---|---|---|---|---|
| Llama 3.1 8B Instruct | Q8_0 | 75 tok/s | Excellent | Higher bandwidth (672 GB/s) makes a noticeable difference vs 4060 Ti. |
| Qwen 2.5 Coder 32B Instruct | Q3_K_M | 16 tok/s | Acceptable | Same VRAM constraint as 4060 Ti but 2.3x bandwidth yields better speed. Still Q3 quality compromise. |
| DeepSeek R1 Distill Qwen 32B | Q3_K_M | 15 tok/s | Acceptable | Q3 required to fit in 16GB. Usable for reasoning with quality compromise. |
| Phi-4 14B | Q5_K_M | 42 tok/s | Good | Q5 fits with headroom. Strong reasoning performance. |
| Mistral Small 24B Instruct | Q3_K_M | 18 tok/s | Acceptable | Q3 required for 16GB. Usable with quality compromise. |
| Llama 3.2 3B Instruct | Q8_0 | 130 tok/s | Excellent | 672 GB/s bandwidth makes 3B model feel instant. Near-instant responses. |
| Llama 3.2 1B Instruct | Q8_0 | 190 tok/s | Excellent | 1B model flies on 672 GB/s. Near-instant responses. |
| Phi-4 Mini | Q8_0 | 120 tok/s | Excellent | 672 GB/s delivers excellent 3.8B speed. Near-instant reasoning. |
| Whisper Large V3 Turbo | FP16 | — | Excellent | 672 GB/s delivers fast transcription. Processing latency ~120ms. |
| Stable Diffusion 3.5 Large | FP16 | — | Excellent | 672 GB/s. FP16 at 12.5GB. ~6s per image. Excellent image gen speed. |
| Gemma 3 27B | Q3_K_M | 12 tok/s | Acceptable | Q3_K_M fits with 2.7GB headroom. Better bandwidth (672 GB/s) than 4060 Ti yields usable speed. |
| DeepSeek V3 | Q2_K | — | Not Viable | 671B MoE model requires 115GB+ at Q2_K. 16GB insufficient. Would need 128GB+ unified memory. |
Buy Used
Prices and availability vary. Inspect hardware before purchasing.
Frequently Asked Questions
- What AI models can NVIDIA GeForce RTX 4070 Ti Super run?
- The NVIDIA GeForce RTX 4070 Ti Super can run 12 AI models. Top performers include Llama 3.2 1B Instruct, Llama 3.2 3B Instruct, Phi-4 Mini. See the full compatibility table above for speeds and quality ratings.
- Is NVIDIA GeForce RTX 4070 Ti Super good for AI coding?
- Yes. With 16 GB, the NVIDIA GeForce RTX 4070 Ti Super handles single-model coding workflows well at the Capable tier.
- How much VRAM does NVIDIA GeForce RTX 4070 Ti Super have?
- The NVIDIA GeForce RTX 4070 Ti Super has 16 GB of GDDR6X VRAM with 672 GB/s bandwidth.
- Can NVIDIA GeForce RTX 4070 Ti Super run 70B models?
- 70B models can run on the NVIDIA GeForce RTX 4070 Ti Super with CPU offloading, but performance will be reduced. Consider a GPU with 48GB+ VRAM for full-speed 70B inference.
- Is NVIDIA GeForce RTX 4070 Ti Super worth it for AI?
- At $779, the NVIDIA GeForce RTX 4070 Ti Super offers 16 GB VRAM and runs 12 AI models. It's a good entry point for smaller models and experimentation.
Generation: Ada Lovelace. Last updated: 2026-03-01.