UNIT · NVIDIA · GPU
11 GB VRAMhighReviewed June 2026

NVIDIA GeForce GTX 1080 Ti

NVIDIA GeForce GTX 1080 Ti — stylized gpu render
generated
Credit: Generated by Imagen 4 Fast — stylized brand-aware render·License: operator-owned

Pascal halo card. 11 GB GDDR5X at 484 GB/s — outperforms many newer mid-range cards on raw bandwidth. Runs 7B Q4 at ~50-65 tok/s, 13B Q4 fits comfortably at ~25-35 tok/s. The legendary 'still relevant' card for AI on a budget; used $230-280 makes it the value flagship of 2026.

Released 2017·~$250 editorial estimate · date unavailable·484 GB/s memory bandwidth
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NVIDIA GeForce GTX 1080 Ti

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RUNLOCALAI SCORE
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327/ 1000
CC-tier
Estimated
Throughput
168/ 500
VRAM-fit
80/ 200
Ecosystem
200/ 200
Efficiency
19/ 100

Sub-scores sum to 467 / 1000. Headline = 467 × 0.70 (Estimated-confidence discount) = 327. 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 484 GB/s bandwidth — 58.1 tok/s estimated. No measured benchmarks yet.

Plain-English: Best for 7B; 14B is tight — coding agent feels deliberate; vision models supported.

7B chat✓
Comfortable
14B chat~
Tight
32B chat✗
Doesn't fit
70B chat✗
Doesn't fit
Coding agent~
Tight
Vision (≤8B VLM)✓
Comfortable
Long context (32K)~
Tight
✓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
6.6/10

This card is for the operator who needs a capable local inference rig on a strict budget, and is willing to accept older architecture limitations. The GTX 1080 Ti runs 7B Q4 models at 50-65 tok/s and 13B Q4 at 25-35 tok/s, making it a strong performer for chat and code completion workloads. Its 11 GB VRAM fits 13B Q4 comfortably, and even 30B Q3 models can be squeezed in with careful quantization. However, larger models like 34B or 70B are out of reach, and the lack of FP16 tensor cores means slower performance on mixed-precision inference. CUDA support is solid, but newer features like Flash Attention may not be fully optimized. Pass on this card if you need to run 70B+ models, require FP16 throughput for training, or want the latest software compatibility. At $250 used, it's the value champion for 7B-13B inference, but expect to upgrade when larger models become your daily driver.

›Why this rating

The GTX 1080 Ti offers exceptional price-to-performance for 7B-13B inference, with high bandwidth and sufficient VRAM for its era. It loses points for lack of modern features and inability to handle larger models, but remains a top budget pick.

BLK · OVERVIEW

Overview

Pascal halo card. 11 GB GDDR5X at 484 GB/s — outperforms many newer mid-range cards on raw bandwidth. Runs 7B Q4 at ~50-65 tok/s, 13B Q4 fits comfortably at ~25-35 tok/s. The legendary 'still relevant' card for AI on a budget; used $230-280 makes it the value flagship of 2026.

Retailers we'd check:Amazon

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BLK · SPECS

Specs

VRAM11 GB
Power draw (peak)250 W
Released2017
MSRP$699
Backends
CUDA
Vulkan

Models that fit

Open-weight models small enough to run on NVIDIA GeForce GTX 1080 Ti with usable context.

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Frequently asked

What models can NVIDIA GeForce GTX 1080 Ti run?

With 11GB VRAM, the NVIDIA GeForce GTX 1080 Ti runs models up to 14B in 4-bit, or 7B at higher quantizations. See the model list below for tested combinations.

Does NVIDIA GeForce GTX 1080 Ti support CUDA?

Yes — NVIDIA GeForce GTX 1080 Ti 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 GTX 1080 Ti cost?

Editorial price estimate for NVIDIA GeForce GTX 1080 Ti: $250 (MSRP $699). 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.