NVIDIA RTX 4070 Ti Super

The RTX 4070 Ti Super was NVIDIA's mid-range Ada Lovelace refresh that finally brought 16 GB VRAM to the $799 price point. With 672 GB/s bandwidth and 16 GB of GDDR6X, it was the best value-for-VRAM Ada GPU - and its strong second-hand market makes it a compelling option for local AI builders in 2026.

Quick verdict

If you can find an RTX 4070 Ti Super for $600-700 used, it's arguably the best value 16GB Ada card available. Performance is close to the RTX 4080 Super (~90%) for ~70% of the price. The 285W TDP makes it easier to cool than higher-end cards.

Spec breakdown

• VRAM: 16 GB GDDR6X
• Memory bandwidth: 672 GB/s (21 Gbps)
• TDP: 285 W (recommend 700W+ PSU)
• PCIe: 4.0 ×16
• Architecture: Ada Lovelace AD103-275
• CUDA cores: 8,448
• Tensor cores: 264 (4th gen)

Real-world AI inference

Model	Tokens/sec	Source
Qwen3-30B Q4_K_M	~17 tok/s	r/LocalLLaMA
Mistral Small 3 Q5_K_M	~35 tok/s	Community
Llama 3.3 70B Q3_K_M	~8 tok/s	Offload
ComfyUI SDXL (1024×1024)	~12 s/image	Community

Best models that fit

• Q4_K_M: Qwen3-30B - comfortable with context
• Q5_K_M: Mistral Small 3 - excellent fit
• Q8_0: 7B models with full precision
• Q3_K_M: Llama 3.3 70B - partial offload

Cost vs cloud

At $600-750 used, this pays back in ~12-15 months for moderate API users ($50/month). Heavy users (coding assistants, large context) break even in 6-8 months.

Where to buy

• Amazon: Button above (check for used/refurbished deals)
• eBay used: ~$600-700

Honest alternatives

• RTX 5070 Ti (~$900): Newer GDDR7, similar VRAM, ~15% faster
• RTX 4070 Super ($500-550): 12 GB - cheaper but less VRAM
• RTX 4090 used (~$1,300): 24 GB - the real upgrade path

What the community says

"Got my 4070 Ti Super used for $650. Runs Qwen3-30B at 17 tok/s all day. Best bang-for-buck Ada card for local AI without a doubt."

• u/used-gpu-hunter on r/LocalLLaMA, 167 upvotes