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NVIDIA GeForce RTX 3070
NVIDIA · GPU · Ampere

NVIDIA GeForce RTX 3070 — Benchmarks & Specs

8 GB VRAM220W TDP$499 MSRP2020
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*Price sourced from Amazon.com. Last updated 2026-07-22. Price and availability subject to change.

The NVIDIA GeForce RTX 3070 is a graphics card from the Ampere family released in 2020 from NVIDIA. Key on-paper specs include 8 GB of GDDR6 VRAM, 220W TDP. It launched with a $499 MSRP, though street prices typically diverge meaningfully from launch pricing — see the linked product cards below for current Amazon listings. Data on this page draws on 8+ Amazon listings, 10 synthetic benchmark results, 10 community AI inference reports, aggregated from public benchmark databases (TechPowerUp, PassMark, Geekbench, Cinebench) and the LocalLLaMA community. Read this page when shopping the NVIDIA GeForce RTX 3070, comparing it against other graphics cards in your build, or sizing it for a specific workload (gaming at 1080p/1440p/4K, productivity benchmarks, or local LLM inference).

Synthetic Benchmarks

Higher is better. Bars are scaled within each benchmark family (multi-thread, single-thread, etc.) so you can compare like-with-like at a glance.

PassMark G3D Mark via PassMark
22,123 pts
3DMark Fire Strike Extreme via KitGuru
17,115 points
3DMark Fire Strike Extreme via DigiStatement
17,115 points
3DMark Time Spy via KitGuru
14,048 points
3DMark Time Spy via DigiStatement
13,945 points
3DMark Fire Strike Ultra via Guru3D
8,749 points
3DMark Port Royal via KitGuru
8,324 points
3DMark Port Royal via DigiStatement
8,324 points
3DMark Time Spy Extreme via KitGuru
6,907 points
3DMark Time Spy Extreme via DigiStatement
6,907 points

AI Inference Performance

Tokens per second under each model + quantization. Higher = faster generation. Bars compare runs across the same model.

llama2:7b q4_0 via llama.cpp GitHub Discussion #10879
78.7 tok/s
llama3:8b q4_K_M via GPU-Benchmarks-on-LLM-Inference (GitHub/XiongjieDai)
72.8 tok/s
llama3:8b q4_K_M via GPU-Benchmarks-on-LLM-Inference (GitHub)
70.9 tok/s
llama3:8b q4_K_M via GPU-Benchmarks-on-LLM-Inference (GitHub/XiongjieDai)
70.9 tok/s
llama3:8b q4_K_M via GPU-Benchmarks-on-LLM-Inference (GitHub/XiongjieDai)
67.0 tok/s
llama3:8b q4_K_M via GPU-Benchmarks-on-LLM-Inference (GitHub/XiongjieDai)
61.6 tok/s
qwen3.5:9b q4_K_M via LocalLLM.in
57.9 tok/s
qwen3.5:9b q4_K_M via LocalLLM.in
57.7 tok/s
qwen3.5:9b q4_K_M via LocalLLM.in
56.6 tok/s
qwen3.5:9b q4_K_M via LocalLLM.in
54.9 tok/s

Products Featuring the NVIDIA GeForce RTX 3070

Full Specifications

tdp w220
vram gb8
vram typeGDDR6
cuda cores5888

NVIDIA GeForce RTX 3070 — Frequently Asked Questions

What is the NVIDIA GeForce RTX 3070 best used for?
NVIDIA GeForce RTX 3070 is positioned as a 8 GB VRAM Ampere-family graphics card. Use it for 1080p gaming and general productivity. See the synthetic + AI benchmark tables below for measured performance.
When was the NVIDIA GeForce RTX 3070 released, and what was its launch MSRP?
NVIDIA GeForce RTX 3070 launched in 2020 at a $499 MSRP. Street prices diverge from launch pricing over a product's lifetime — check the linked Amazon listings on this page for current availability.
Where do the benchmark numbers on this page come from?
Synthetic benchmarks are scraped from public databases (TechPowerUp, PassMark, Geekbench Browser, Cinebench leaderboards). AI inference numbers come from the LocalLLaMA community (Reddit threads, llama.cpp / Ollama discussion logs, and Phoronix when available). Every benchmark row carries an inline source citation — click through to verify the original number.
Can the NVIDIA GeForce RTX 3070 run local LLMs?
Yes — NVIDIA GeForce RTX 3070 has 10 AI inference benchmarks on file (see the AI Inference Performance section above for model + tokens-per-second numbers).
Where can I buy the NVIDIA GeForce RTX 3070?
Amazon listings are linked at the top of this page (in the hero CTA) and in the "Products Featuring this Hardware" section below. SpecPicks earns a small affiliate commission on qualifying purchases.

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NVIDIA GeForce RTX 3070
NVIDIA GeForce RTX 3070
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