# Used RTX 3090 (24GB) vs RTX 5070 Ti (16GB) for Local AI & LLMs

> **Direct Hardware Verdict**: Spend ~$680 on a tested RTX 3090 24GB if your primary goal is loading dense 27B–32B coding models and Wan 2.1 14B video checkpoints completely inside VRAM. Its 384-bit 936 GB/s bus outperforms the $799 RTX 5070 Ti's 896 GB/s bandwidth while giving +8 GB extra headroom for $119 less. Choose the factory-new RTX 5070 Ti 16GB only when warranty coverage, 300W efficiency, and native Blackwell NVFP4 acceleration on <=16GB workloads matter more than 32B model capacity.

## Contender Specifications
| Metric | NVIDIA GeForce RTX 3090 (24GB) | NVIDIA GeForce RTX 5070 Ti (16GB) |
|---|---|---|
| VRAM Capacity | 24 GB GDDR6X | 16 GB GDDR7 |
| Memory Bandwidth | 384-bit (936 GB/s) | 256-bit (896 GB/s) |
| Typical Price | ~$680 (Used) | $749 – $799 (New) |
| Estimated Throughput | ~35 tok/s (32B Q4) / ~78 tok/s (14B Q4) | ~74 tok/s (14B Q4) / OOM on 32B Q4 |

## Comparative Model Compatibility Matrix
| Model & Quantization | VRAM Demand | NVIDIA GeForce RTX 3090 | NVIDIA GeForce RTX 5070 Ti |
|---|---|---|---|
| Qwen 2.5 Coder 32B (Q4_K_M) | 23.10 GB | Fits Tight (+0.90 GB, ~35 tok/s) | Exceeds VRAM (-7.10 GB OOM) |
| Google Gemma 4 31B (Q4_K_M) | 21.44 GB | Fits Clean (+2.56 GB, ~37 tok/s) | Exceeds VRAM (-5.44 GB OOM) |
| Alibaba Wan 2.1 14B 720p (Q4 / NF4) | 18.15 GB | Runs Resident (+5.85 GB) | Overflow (-2.15 GB Block-Swap) |
| OpenAI gpt-oss 20B MoE (Q4_K_M) | 14.43 GB | Comfort Margin (+9.57 GB) | Tight Fit (+1.57 GB, FP4 Boost) |
| FLUX.1 [dev] NF4 / 4-bit | 15.46 GB | Comfort Margin (+8.54 GB) | Tight Fit (+0.54 GB, Fast NVFP4) |


## Silicon Architecture & Thermal Analysis
Comparing Ampere GA102 against Blackwell GB203 highlights why capacity beats generational shader improvements once models cross 16 GB. The RTX 3090 pairs twenty-four 1GB Micron GDDR6X packages in a double-sided clamshell layout across a wide 384-bit controller (936 GB/s), holding Qwen 2.5 Coder 32B (23.10 GB at Q4_K_M) and Google Gemma 4 31B (21.44 GB) natively without PCIe spill. By contrast, GB203 inside the RTX 5070 Ti relies on eight 2GB PAM3 28 Gbps GDDR7 chips over a 256-bit bus (896 GB/s) and adds 5th-gen Tensor Cores with hardware NVFP4 microscaling plus dual 9th-gen NVENC blocks. That silicon edge makes Blackwell dramatically faster during long-prompt prefill and 4-bit FP4 diffusion on 12B–20B models, yet the strict 16GB ceiling forces heavy CPU layer offload on every dense 32B checkpoint.

## Tier 1 Free Software Optimization ($0)
Before paying $799 for a Blackwell card or fighting thermal throttling on a used RTX 3090, run `llama-server -m model.gguf -ngl 99 -fa on -ctk q8_0 -ctv q8_0` and enforce `nvidia-smi -pl 285`. You keep 97% of 936 GB/s decode throughput while trimming junction heat and unlocking 32k context inside 24GB.

- Companion Upgrade (Thermal Grizzly PhaseSheet PTM (50x40mm)): https://www.amazon.com/dp/B0DB84CQW6?tag=sparecables-20 (rel="noopener sponsored")

## Verified Hardware & Cloud Pathways
- Shop Tested Used on eBay (~$680) ↗: https://www.ebay.com/sch/i.html?_nkw=NVIDIA%20GeForce%20RTX%203090%2024GB%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 Dual GeForce RTX 5060 Ti 16GB GDDR7 OC): https://www.amazon.com/dp/B0F4DVKSZ4?tag=sparecables-20 (rel="noopener sponsored")
- Rig Essential — Thermal Grizzly PhaseSheet PTM: https://www.amazon.com/dp/B0DB84CQW6?tag=sparecables-20 (rel="noopener sponsored")
- Rig Essential — upHere GPU Anti-Sag Bracket: https://www.amazon.com/dp/B076GYL25H?tag=sparecables-20 (rel="noopener sponsored")
- ASUS Prime GeForce RTX 5070 Ti 16GB GDDR7 OC on Amazon Prime: https://www.amazon.com/dp/B0DVGVZZYY?tag=sparecables-20 (rel="noopener sponsored")
- Rent on RunPod: https://console.runpod.io/deploy?ref=ynypzu94 (rel="noopener sponsored")
- Rent on Vast.ai: https://cloud.vast.ai/?ref_id=723130 (rel="noopener sponsored")

---
*Interactive Sizing Calculator available at: https://www.gpugarden.com/compare/rtx-3090-vs-rtx-5070-ti-16gb/*