GeForce RTX 3070 Ti 8 GB GA102

The GeForce RTX 3070 Ti 8 GB GA102 is an NVIDIA GPU built on the Ampere architecture, released 2022-10-21. For running AI locally, the numbers that matter are its 8 GB of GDDR6X and 608.3 GB/s of memory bandwidth. VRAM decides which models fit at all; bandwidth sets how fast they generate text.

What you can run on 8 GB

At Q4_K_M quantization (the usual local default), 8 GB holds models up to roughly 12B parameters, leaving headroom for context. On this card you can run, among others:

• Darwin-9B-NEG - 9.7B parameters
• Qwen3.5 9B - 9.7B parameters
• NVIDIA-Nemotron-Nano-9B-v2 - 8.9B parameters
• LLaDA-8B-Instruct - 8B parameters
• LLaMA-Mesh - 8B parameters

Larger models need a higher-VRAM card, a second GPU, or CPU offload (which is much slower). Check any specific model with the VRAM calculator, or see the full picture on what can I run.

Local LLM speed (LLaMA 3, llama.cpp)

Single-stream token-generation throughput - estimated from memory bandwidth:

Model (quant)	Speed on GeForce RTX 3070 Ti 8 GB GA102
Llama 3 8B (Q4_K_M)	71.2 tok/s
Llama 3 8B (F16)	✗ won't fit
Llama 3 70B (Q4_K_M)	✗ won't fit

Because decode is memory-bandwidth bound, the 608.3 GB/s figure is the best single predictor of chat speed on this card. Estimates are calibrated against measured RTX-40-series cards and are typically within ~15%.

Memory and power

• VRAM: 8 GB GDDR6X (256-bit bus)
• Bandwidth: 608.3 GB/s
• TDP: 290 W - a 600 W+ power supply is recommended
• Process: 8 nm
• Interface: PCIe 4.0 x16

Quantization and context

Quantization trades a little quality for a lot of VRAM. On 8 GB you can fit roughly a 12B model at Q4_K_M, about a 6B model at the higher-quality Q8, or a smaller model at full FP16. Longer context windows also consume VRAM (the KV cache grows with context length), so leave a few GB of headroom if you plan to use large prompts or many concurrent requests. For most chat and coding use, Q4_K_M on this card is the sweet spot between speed, quality, and the 8 GB budget.

How it compares

Similar cards for local AI, by VRAM and 8B-Q4 speed:

GPU	VRAM	Bandwidth	Llama 3 8B Q4
GeForce RTX 3070 Ti 8 GB GA102	8 GB	608.3 GB/s	71.2 tok/s
AMD Radeon RX 7600	8 GB	288 GB/s	33.7 tok/s
Arc A530M	8 GB	224 GB/s	26.2 tok/s
Arc A570M	8 GB	224 GB/s	26.2 tok/s

Bottom line

The GeForce RTX 3070 Ti 8 GB GA102 is best for entry-level, budget-llm. With under 12 GB, stick to small quantized models (up to ~7B). If you need more, compare with AMD Radeon RX 7600 and Arc A530M.

Sources

• Specifications: RightNow GPU Database (TechPowerUp data)
• Benchmarks: GPU-Benchmarks-on-LLM-Inference (basis for the bandwidth estimate)

Specs and benchmarks last checked 2026-06-08. Verify current pricing before buying.