TokenAssemble
Check a machineStack BuilderWorkflowsCompareMethodology

Browse stack

NVIDIA GPU

NVIDIA GeForce RTX 4080

The NVIDIA GeForce RTX 4080 has 16GB of VRAM and 716.8 GB/s of memory bandwidth. Its sweet spot tops out around gpt-oss-20b — the largest model that loads cleanly at a quality quant with llama.cpp at 8K context.

VRAM
16 GB
Memory bandwidth
716.8 GB/s
TDP
320 W
MSRP
$1,199
Backends
CUDA · Vulkan

Also good for gaming — 4K-class (estimated from FP32 compute, not a game benchmark)

Specs as of 2026-07-08 · source

Check price on Amazon

NVIDIA GeForce RTX 4080 for local AI — common questions

How much VRAM does the NVIDIA GeForce RTX 4080 have?
The NVIDIA GeForce RTX 4080 has 16GB of VRAM with 716.8 GB/s of memory bandwidth. VRAM sets which models fit; bandwidth sets how fast they feel once they do.
Is the NVIDIA GeForce RTX 4080 good for running AI models locally?
Yes, within limits. 16GB comfortably runs small and mid-size models at a quality quant, but the largest open models will not fit. The largest model it loads cleanly is gpt-oss-20b, at a quality quant with llama.cpp at 8K context.
What runtimes work with the NVIDIA GeForce RTX 4080?
It runs on CUDA · Vulkan, which covers Ollama, llama.cpp and LM Studio. Runtime choice affects speed and features, not whether a model fits.

Affiliate link — we may earn a commission. Verdicts are computed before any link is attached.

What an NVIDIA GeForce RTX 4080 can run

Every model we track, graded at its best clean-fit quant. Click any verdict for the full breakdown.

ModelBest-quant verdict · llama.cpp · 8K context
Qwen3-8BFits · A · Q8_0interactive
gemma-4-26B-A4B-itTight · C · MXFP4_MOEinteractive · offloadbeta
Qwen2.5-7B-InstructFits · A · Q8_0interactive
Qwen2.5-1.5B-InstructFits · A · Q8_0interactive
Llama-3.2-1B-InstructFits · A · Q8_0interactive
Llama-3.1-8B-InstructFits · A · Q8_0interactive
DeepSeek-R1Won't fitbeta
Qwen3.5-9BFits · B · Q8_0interactivebeta
gpt-oss-20bFits · B · MXFP4interactivebeta
Qwen3.6-35B-A3BTight · C · MXFP4_MOEinteractive · offloadbeta
Qwen2.5-3B-InstructFits · A · Q8_0interactive
Qwen3-32BTight · C · Q4_K_Musable · offloadbeta
Qwen3.6-27BTight · C · Q4_K_Musable · offloadbeta
Qwen2.5-0.5B-InstructFits · A · Q8_0interactive
Mistral-7B-Instruct-v0.3Fits · A · Q8_0interactive
gpt-oss-120bTight · C · MXFP4interactive · offloadbeta
Qwen3-14BFits · B · Q5_K_Minteractive
Qwen3-30B-A3BTight · C · Q4_K_Minteractive · offloadbeta
Qwen2.5-32B-InstructTight · C · Q4_K_Musable · offloadbeta
DeepSeek-V4-FlashWon't fitbeta
Qwen2.5-14B-InstructFits · B · Q5_K_Minteractive
Llama-3.2-3B-InstructFits · A · Q8_0interactive
gemma-3-4b-itFits · A · Q8_0interactivebeta
gemma-3-12b-itFits · B · Q6_Kinteractivebeta
Llama-3.1-70B-InstructTight · C · Q4_K_Mpainful · offloadbeta
Phi-3.5-mini-instructFits · A · Q8_0interactive
Phi-4Fits · B · Q5_K_Minteractive
DeepSeek-R1-Distill-Qwen-32BTight · C · Q4_K_Musable · offloadbeta
gemma-3-27b-itTight · C · Q4_K_Musable · offloadbeta
Llama-3.3-70B-InstructTight · C · Q4_K_Mpainful · offloadbeta
Qwen2.5-72B-InstructTight · C · Q4_K_Mpainful · offloadbeta
gemma-2-2b-itFits · A · Q8_0interactivebeta
DeepSeek-R1-Distill-Qwen-14BFits · B · Q5_K_Minteractive
DeepSeek-R1-Distill-Llama-8BFits · A · Q8_0interactive
DeepSeek-R1-Distill-Qwen-7BFits · A · Q8_0interactive
gemma-2-9b-itFits · B · Q8_0interactivebeta
Mistral-Nemo-Instruct-2407Fits · B · Q6_Kinteractive
QwQ-32BTight · C · Q4_K_Musable · offloadbeta
Mistral-Small-24B-Instruct-2501Tight · C · Q4_K_Musable · offloadbeta
gemma-2-27b-itTight · C · Q4_K_Musable · offloadbeta

Compare NVIDIA GeForce RTX 4080

Have a specific model in mind? Check it against the NVIDIA GeForce RTX 4080 at your own quant and context length.

Check with the NVIDIA GeForce RTX 4080 preselected →

Verdicts computed from published specs and measured GGUF sizes — how the math works.