# Used RTX 4070 Ti Super vs RTX 5070 Ti (16GB) for Local AI

> **Direct Hardware Verdict**: Paying ~$720 for a secondhand RTX 4070 Ti Super makes poor financial sense when a factory-new $799 RTX 5070 Ti costs only $79 more (+11%) while delivering +33.3% higher memory bandwidth (896 vs 672 GB/s). Both share 16GB capacity, so identical checkpoints fit on each card—yet Blackwell streams Qwen 2.5 14B Q4_K_M at ~74 vs ~56 tok/s, adds native FP4 Tensor Cores, upgrades NVENC to dual 9th-gen engines, and carries a full manufacturer warranty.

## Contender Specifications
| Metric | NVIDIA GeForce RTX 4070 Ti Super (16GB) | NVIDIA GeForce RTX 5070 Ti (16GB) |
|---|---|---|
| VRAM Capacity | 16 GB GDDR6X | 16 GB GDDR7 |
| Memory Bandwidth | 256-bit (672 GB/s) | 256-bit (896 GB/s) |
| Typical Price | ~$720 (Used) | ~$799 (New) |
| Estimated Throughput | ~56 tok/s (14B Q4) / ~39 tok/s (20B MoE) | ~74 tok/s (14B Q4) / ~52 tok/s (20B MoE) |

## Comparative Model Compatibility Matrix
| Model & Quantization | VRAM Demand | NVIDIA GeForce RTX 4070 Ti Super | NVIDIA GeForce RTX 5070 Ti |
|---|---|---|---|
| Qwen 2.5 14B Instruct (Q4_K_M) | 12.08 GB | Comfort Margin (~56 tok/s) | Comfort Margin (~74 tok/s) |
| OpenAI gpt-oss 20B MoE (Q4_K_M) | 14.43 GB | Tight Fit (+1.57 GB, ~39 tok/s) | Tight Fit (+1.57 GB, ~52 tok/s) |
| Google Gemma 4 12B Multimodal (Q4_K_M) | 9.55 GB | Comfort Margin (~68 tok/s) | Comfort Margin (~91 tok/s) |
| FLUX.1 [dev] NF4 / 4-bit | 15.46 GB | Tight Fit (+0.54 GB, Ada FP8) | Tight Fit (+0.54 GB, NVFP4) |
| Mistral Small 24B (Q4_K_M) | 17.82 GB | Exceeds VRAM (-1.82 GB OOM) | Exceeds VRAM (-1.82 GB OOM) |


## Silicon Architecture & Thermal Analysis
Both GPUs deploy 256-bit memory controllers, making this one of NVIDIA's cleanest generational bandwidth leaps inside an identical VRAM tier. Ada Lovelace's harvested AD103 chip on the RTX 4070 Ti Super pairs 8,448 CUDA cores and 48 MB of L2 cache with 21 Gbps GDDR6X (672 GB/s) over PCIe 4.0 x16 at 285W TDP. Blackwell's GB203 silicon on the RTX 5070 Ti upgrades to 8,960 cores, PCIe 5.0 x16, and PAM3 28 Gbps GDDR7 chips to unlock 896 GB/s at 300W. Crucially for 2026 quantizations, Ada 4th-gen Tensor Cores top out at E4M3 FP8—requiring shader dequantization loops for 4-bit weights—whereas Blackwell's 5th-gen Tensor Cores compute hardware microscaling NVFP4 and MXFP4 natively, noticeably lowering FLUX image generation times and gpt-oss 20B prompt latency.

## Tier 1 Free Software Optimization ($0)
Already own an RTX 4070 Ti Super? Squeeze peak efficiency out of its 48 MB L2 cache and 672 GB/s bus using `llama-server -m model.gguf -ngl 99 -fa on -ctk q8_0 -ctv q8_0`, or launch `vllm --kv-cache-dtype fp8` so Ada's FP8 Tensor Cores halve KV-cache footprint cleanly.

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## Verified Hardware & Cloud Pathways
- Shop Tested Used on eBay (~$720) ↗: https://www.ebay.com/sch/i.html?_nkw=NVIDIA%20GeForce%20RTX%204070%20Ti%20Super%2016GB%20GPU&LH_BIN=1&mkcid=1&mkrid=711-53200-19255-0&siteid=0&campid=5339245689&toolid=10001&mkevt=1&customid=gpugarden_programmatic_md (rel="noopener sponsored")
- Compare New Prime GPUs on Amazon (ASUS Prime GeForce RTX 5070 Ti 16GB GDDR7 OC): https://www.amazon.com/dp/B0DVGVZZYY?tag=sparecables-20 (rel="noopener sponsored")
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- ASUS Prime GeForce RTX 5070 Ti 16GB GDDR7 OC on Amazon Prime: https://www.amazon.com/dp/B0DVGVZZYY?tag=sparecables-20 (rel="noopener sponsored")
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*Interactive Sizing Calculator available at: https://www.gpugarden.com/compare/rtx-4070-ti-super-vs-rtx-5070-ti-16gb/*