whichLlmmodel
Dedicated GPU Setup

Best local text models for 32gb vram

If you are searching for the best text model for 32GB VRAM, this compatibility index displays all open-source Large Language Models (LLMs) that fit your system at a baseline context length of 8,192 tokens. Compare quantization formats (FP16, Q8, Q4) to prevent CUDA OOM crashes.

Supported GPU Configurations & Tiers:
NVIDIA RTX 5000 Ada (32GB)Dual NVIDIA RTX 4080 (32GB)Dual NVIDIA RTX 3080 16GB

Compatible Local LLMs (37)

DeepSeek16B params

DeepSeek V2 Lite

FP16CPU Offload
Q8_0N/A
Q4_K_MN/A
Details
Meta70B params

Llama-3.3-70B

FP16OOM
Q8_0CPU Offload
Q4_K_MCPU Offload
Details
Meta30B params

Muse Glimmer 30B

FP16CPU Offload
Q8_0CPU Offload
Q4_K_MFits in VRAM
Details
Meta8B params

Llama-3.1 8B (Instruct)

FP16Fits in VRAM
Q8_0Fits in VRAM
Q4_K_MFits in VRAM
Details
Meta70B params

Llama-3.1 70B

FP16OOM
Q8_0CPU Offload
Q4_K_MCPU Offload
Details
Alibaba Cloud (Qwen)27B params

Qwen3.6-27B

FP16CPU Offload
Q8_0CPU Offload
Q4_K_MFits in VRAM
Details
Alibaba Cloud (Qwen)27B params

Qwen3.8-27B

FP16CPU Offload
Q8_0CPU Offload
Q4_K_MFits in VRAM
Details
ornith-ai35B params

Ornith-1.5-35B-A3B

FP16CPU Offload
Q8_0CPU Offload
Q4_K_MFits in VRAM
Details
Alibaba Cloud (Qwen)35B params

Qwen3.6-35B-A3B

FP16CPU Offload
Q8_0CPU Offload
Q4_K_MFits in VRAM
Details
Alibaba Cloud (Qwen)32B params

Qwen2.5-Coder 32B

FP16CPU Offload
Q8_0CPU Offload
Q4_K_MFits in VRAM
Details
Mistral AI7B params

Mistral 7B v0.3

FP16Fits in VRAM
Q8_0Fits in VRAM
Q4_K_MFits in VRAM
Details
Mistral AI46.7B params

Mixtral 8x7B v0.1

FP16CPU Offload
Q8_0CPU Offload
Q4_K_MFits in VRAM
Details
Mistral AI141B params

Mixtral 8x22B v0.1

FP16OOM
Q8_0OOM
Q4_K_MCPU Offload
Details
Mistral AI22B params

Codestral 22B

FP16CPU Offload
Q8_0Fits in VRAM
Q4_K_MFits in VRAM
Details
Mistral AI3B params

Ministral 3 3B (Instruct)

FP16Fits in VRAM
Q8_0Fits in VRAM
Q4_K_MFits in VRAM
Details
Mistral AI8B params

Ministral 3 8B

FP16Fits in VRAM
Q8_0Fits in VRAM
Q4_K_MFits in VRAM
Details
Mistral AI14B params

Ministral 3 14B

FP16Fits in VRAM
Q8_0Fits in VRAM
Q4_K_MFits in VRAM
Details
Mistral AI119B params

Mistral Small 4

FP16OOM
Q8_0OOM
Q4_K_MCPU Offload
Details
Mistral AI128B params

Mistral Medium 3.5

FP16OOM
Q8_0OOM
Q4_K_MCPU Offload
Details
Google2.3B params

Gemma 4 E2B

FP16Fits in VRAM
Q8_0Fits in VRAM
Q4_K_MFits in VRAM
Details
Google4.5B params

Gemma 4 E4B

FP16Fits in VRAM
Q8_0Fits in VRAM
Q4_K_MFits in VRAM
Details
Google11.95B params

Gemma 4 12B

FP16Fits in VRAM
Q8_0Fits in VRAM
Q4_K_MFits in VRAM
Details
Google25.2B params

Gemma 4 26B A4B

FP16CPU Offload
Q8_0Fits in VRAM
Q4_K_MFits in VRAM
Details
Google30.7B params

Gemma 4 31B

FP16CPU Offload
Q8_0CPU Offload
Q4_K_MFits in VRAM
Details
Nvidia31.6B params

Nemotron-3 Nano 30B

FP16CPU Offload
Q8_0CPU Offload
Q4_K_MFits in VRAM
Details
OpenAI117B params

gpt-oss-120b

FP16CPU Offload
Q8_0N/A
Q4_K_MN/A
Details
OpenAI21B params

gpt-oss-20b

FP16Fits in VRAM
Q8_0N/A
Q4_K_MN/A
Details
ornith-ai8.2B params

Ornith-1.5-9B

FP16Fits in VRAM
Q8_0Fits in VRAM
Q4_K_MFits in VRAM
Details
Alibaba Cloud (Qwen)8.2B params

Qwen3.5-9B

FP16Fits in VRAM
Q8_0Fits in VRAM
Q4_K_MFits in VRAM
Details
Alibaba Cloud (Qwen)3.7B params

Qwen3.5-4B

FP16Fits in VRAM
Q8_0Fits in VRAM
Q4_K_MFits in VRAM
Details
Alibaba Cloud (Qwen)1.7B params

Qwen3.5-2B

FP16Fits in VRAM
Q8_0N/A
Q4_K_MN/A
Details
Cloudflare9B params

clef-flash

FP16Fits in VRAM
Q8_0N/A
Q4_K_MN/A
Details
Bespoke Labs8.21B params

Bespoke-Nimble-9B-v3

FP16Fits in VRAM
Q8_0Fits in VRAM
Q4_K_MFits in VRAM
Details
Inclusion AI7.9B params

Ling-3.0-tiny

FP16Fits in VRAM
Q8_0Fits in VRAM
Q4_K_MFits in VRAM
Details
Liquid AI24B params

LFM2.5-24B A2B

FP16CPU Offload
Q8_0Fits in VRAM
Q4_K_MFits in VRAM
Details
Openbmb34B params

MiniCPM V-4.7-35B A3B

FP16CPU Offload
Q8_0CPU Offload
Q4_K_MFits in VRAM
Details
Openbmb0.9B params

MiniCPM V-4.7-1B

FP16Fits in VRAM
Q8_0Fits in VRAM
Q4_K_MN/A
Details