UNIT · NVIDIA · GPU
22 GB VRAMmidReviewed October 2026

NVIDIA RTX 2080 Ti 22GB (China-mod)

No editorial image yet — generic vendor mark shown. Credentials in spec table below.

Chinese third-party modification of the stock RTX 2080 Ti, replacing the 11 GB GDDR6 with 22 GB. The TU102 chip, 352-bit memory bus, and 616 GB/s bandwidth are unchanged — only VRAM density doubles. The community uses these cards in multi-card stacks (8× cards × 22 GB = 176 GB on a single chassis for an under-$3,000 budget). Trade-off: Turing architecture is two generations behind; no FP8 support, no transformer-engine kernels, AWQ-INT4 inference works but expect lower tok/s than a modern card per GB of VRAM.

Released 2023·616 GB/s memory bandwidth
RUNLOCALAI SCORE
See full leaderboard →
405/ 1000
CC-tier
Estimated
Throughput
214/ 500
VRAM-fit
140/ 200
Ecosystem
200/ 200
Efficiency
24/ 100

Sub-scores sum to 578 / 1000. Headline = 578 × 0.70 (Estimated-confidence discount) = 405. 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 616 GB/s bandwidth — 73.9 tok/s estimated. No measured benchmarks yet.

Plain-English: Workable at 32B, comfortable at 14B and below — snappy enough for a coding agent; vision models supported.

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

Overview

Chinese third-party modification of the stock RTX 2080 Ti, replacing the 11 GB GDDR6 with 22 GB. The TU102 chip, 352-bit memory bus, and 616 GB/s bandwidth are unchanged — only VRAM density doubles. The community uses these cards in multi-card stacks (8× cards × 22 GB = 176 GB on a single chassis for an under-$3,000 budget). Trade-off: Turing architecture is two generations behind; no FP8 support, no transformer-engine kernels, AWQ-INT4 inference works but expect lower tok/s than a modern card per GB of VRAM. Same caveats as any aftermarket mod: no NVIDIA warranty, sourcing from Taobao requires shipping logistics, kernel maturity for old architectures has thinned over time.

Retailers we'd check:Amazon

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BLK · SPECS

Specs

VRAM22 GB
Power draw (peak)250 W
Released2023
Backends
CUDA
Vulkan

Models that fit

Open-weight models small enough to run on NVIDIA RTX 2080 Ti 22GB (China-mod) with usable context.

Frequently asked

What models can NVIDIA RTX 2080 Ti 22GB (China-mod) run?

With 22GB VRAM, the NVIDIA RTX 2080 Ti 22GB (China-mod) runs models up to ~32B in 4-bit, with room for context. See the model list below for tested combinations.

Does NVIDIA RTX 2080 Ti 22GB (China-mod) support CUDA?

Yes — NVIDIA RTX 2080 Ti 22GB (China-mod) is an NVIDIA card with full CUDA support, the most mature local-AI backend. llama.cpp, Ollama, vLLM, and ExLlamaV2 all run natively.

Where next?

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