UNIT · NVIDIA · GPU
8 GB VRAMhighReviewed June 2026

NVIDIA GeForce RTX 2070 Super

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

The Turing refresh that made 8 GB Turing genuinely fast. ~70-90 tok/s on 7B Q4 with ExLlamaV2. Same 8 GB ceiling as the base 2070 but more compute. Strong used-market value in 2026.

Released 2019·~$280 editorial estimate · date unavailable·448 GB/s memory bandwidth
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NVIDIA GeForce RTX 2070 Super

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RUNLOCALAI SCORE
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319/ 1000
CC-tier
Estimated
Throughput
156/ 500
VRAM-fit
80/ 200
Ecosystem
200/ 200
Efficiency
20/ 100

Sub-scores sum to 456 / 1000. Headline = 456 × 0.70 (Estimated-confidence discount) = 319. 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
4.8/10

This card is for the operator who wants to run 7B models at high speed on a budget, and is willing to accept the 8 GB VRAM ceiling. It handles 7B Q4 models at 70-90 tok/s with ExLlamaV2, and can run 13B Q4 models at 30-40 tok/s with aggressive quantization. The 8 GB limit breaks on 30B+ models, and even 13B models require careful quantization to fit. Pass if you need to run 34B+ models or want headroom for larger context windows. At ~$280 used, it's a strong value for fast 7B inference, but consider an RTX 3060 12 GB if VRAM is the priority.

Why this rating

The RTX 2070 Super offers excellent tok/s for 7B models at a low used price, but the 8 GB VRAM is a hard limit for larger models. It earns a 7.5 for its strong price-to-performance ratio in its niche, but loses points for limited future-proofing.

BLK · OVERVIEW

Overview

The Turing refresh that made 8 GB Turing genuinely fast. ~70-90 tok/s on 7B Q4 with ExLlamaV2. Same 8 GB ceiling as the base 2070 but more compute. Strong used-market value in 2026.

Retailers we'd check:Amazon

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BLK · SPECS

Specs

VRAM8 GB
Power draw (peak)215 W
Released2019
MSRP$499
Backends
CUDA
Vulkan

Models that fit

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

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Frequently asked

What models can NVIDIA GeForce RTX 2070 Super run?

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

Does NVIDIA GeForce RTX 2070 Super support CUDA?

Yes — NVIDIA GeForce RTX 2070 Super 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 Super cost?

Editorial price estimate for NVIDIA GeForce RTX 2070 Super: $280 (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.