UNIT · NVIDIA · GPU
8 GB VRAMhighReviewed June 2026

NVIDIA GeForce RTX 2070

NVIDIA GeForce RTX 2070 — stylized gpu render
generated
Credit: Generated by Imagen 4 Fast — stylized brand-aware render·License: operator-owned

Turing high-tier. 8 GB VRAM, similar bandwidth to the 2060 Super, slightly more compute. Runs 7B Q4 at ~65-80 tok/s, 13B Q4 with light offload. A solid used-market choice for operators with $200-260 to spend.

Released 2018·~$240 editorial estimate · date unavailable·448 GB/s memory bandwidth
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NVIDIA GeForce RTX 2070

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RUNLOCALAI SCORE
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323/ 1000
CC-tier
Estimated
Throughput
156/ 500
VRAM-fit
80/ 200
Ecosystem
200/ 200
Efficiency
25/ 100

Sub-scores sum to 461 / 1000. Headline = 461 × 0.70 (Estimated-confidence discount) = 323. This is an algorithmic performance-tier score — distinct from, and often lower than, the editorial “Our verdict” below, which weighs value and real-world fit (especially for hardware we haven’t measured yet). How scoring works →

Extrapolated from 448 GB/s bandwidth — 53.8 tok/s estimated. No measured benchmarks yet.

Plain-English: Comfortable for 7B chat.

7B chat
Comfortable
14B chat
Doesn't fit
32B chat
Doesn't fit
70B chat
Doesn't fit
Coding agent
Doesn't fit
Vision (≤8B VLM)~
Tight
Long context (32K)
Doesn't fit
Comfortable — fits with headroom
~Tight — works, no slack
Marginal — needs aggressive quant
Doesn't fit usefully

Verdicts extrapolated from catalog VRAM + bandwidth + ecosystem flags. Hover any chip for the rationale. Want measured numbers? Submit your own run with runlocalai-bench --submit.

BLK · VERDICT

Our verdict

OP · Eruo Fredoline|VERIFIED JUN 9, 2026
5.1/10

This card is for the operator who needs a reliable, affordable entry into local inference with CUDA-only stacks, and is willing to work within an 8 GB VRAM ceiling. It handles 7B Q4 models at 50-65 tok/s and 13B Q4 with partial offload at 20-30 tok/s, making it a solid choice for chat and code completion on smaller models. The 8 GB VRAM breaks on 30B+ models and struggles with 13B Q4 fully in VRAM, requiring offloading that slows generation. Pass if you need to run 13B models entirely on GPU or plan to scale to 30B+; the 3060 12 GB offers more VRAM for similar money. At ~$240 used, this is a fair value for a CUDA-only rig that prioritizes speed on small models over capacity.

Why this rating

The RTX 2070 offers good speed for 7B models and a low used price, but its 8 GB VRAM limits model size and forces offloading for 13B. It's a competent entry-level card, not a standout for larger workloads.

BLK · OVERVIEW

Overview

Turing high-tier. 8 GB VRAM, similar bandwidth to the 2060 Super, slightly more compute. Runs 7B Q4 at ~65-80 tok/s, 13B Q4 with light offload. A solid used-market choice for operators with $200-260 to spend.

Retailers we'd check:Amazon

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BLK · SPECS

Specs

VRAM8 GB
Power draw (peak)175 W
Released2018
MSRP$499
Backends
CUDA
Vulkan

Models that fit

Open-weight models small enough to run on NVIDIA GeForce RTX 2070 with usable context.

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Frequently asked

What models can NVIDIA GeForce RTX 2070 run?

With 8GB VRAM, the NVIDIA GeForce RTX 2070 runs 7B models comfortably in Q4 quantization. See the model list below for tested combinations.

Does NVIDIA GeForce RTX 2070 support CUDA?

Yes — NVIDIA GeForce RTX 2070 is an NVIDIA card with full CUDA support, the most mature local-AI backend. llama.cpp, Ollama, vLLM, and ExLlamaV2 all run natively.

How much does NVIDIA GeForce RTX 2070 cost?

Editorial price estimate for NVIDIA GeForce RTX 2070: $240 (MSRP $499). Price check date unavailable. Verify current retailer price and availability.

Where next?

Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify hardware specifications.