All LLM Models
Browse 1475 LLM models with VRAM requirements, quantization options, and hardware compatibility.
Understanding LLM VRAM Requirements
How much VRAM you need depends on the model size and quantization level. Quantization reduces the precision of model weights, trading small quality losses for significantly lower VRAM usage. For example, a 7B parameter model needs ~14 GB at FP16 but only ~4 GB at Q4_K_M quantization.
Model List
Instella MoE 16B A3B Think
amd · 15.9B · runs from 7.5 GB
3.1K
179Instella MoE 16B A3B Think is a 15.9B-parameter open language model from amd. It supports a context window of up to 32,768 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
YuE2 3B OrbitQuant W4A4
WaveCut · 2.2B · runs from 5.0 GB
YuE2 3B OrbitQuant W4A4 is a 2.2B-parameter open language model from WaveCut. It supports a context window of up to 24,576 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Qwen3.8 27B EXL3 3.5bpw
Mia-AiLab · 7.7B · runs from 16.1 GB
Qwen3.8 27B EXL3 3.5bpw is a 7.7B-parameter open language model from Mia-AiLab in the Qwen 3.8 family. It supports a context window of up to 262,144 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Qwen3.8 Flash Next MTPLX Bare Speed
Youssofal · 126.2B · runs from 54.0 GB
Qwen3.8 Flash Next MTPLX Bare Speed is a 126.2B-parameter open language model from Youssofal in the Qwen 3.8 family. It supports a context window of up to 262,144 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Solar Open2 250B
Upstage · 250.3B · runs from 501.1 GB
Solar Open2 250B is a 250.3B-parameter open language model from Upstage in the Solar family. It supports a context window of up to 1,048,576 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
BitCPM CANN 8B
OpenBMB · 8B · runs from 3.8 GB
BitCPM-CANN-8B is OpenBMB's 8-billion-parameter ternary (1.58-bit) quantization-aware variant of its MiniCPM4-8B model, produced by the first publicly reported end-to-end 1.58-bit training system built natively for Huawei's Ascend NPU stack, integrating quantization-aware training into Megatron-LM with MindSpeed acceleration. Against its full-precision MiniCPM4-8B counterpart across 11 benchmarks it retains about 95.7% of performance, and the ternary training approach itself adds only a few percent training overhead on Ascend 910B hardware. This particular checkpoint ships in a "pseudo-quantized" format, with ternary values stored as ordinary floating-point weights, so despite the ternary training it loads and runs exactly like the full-precision 8B model rather than at reduced memory, and needs the same hardware as a dense 8B model to run locally. Context length is 32,768 tokens. It is released under the Apache 2.0 license, permitting unrestricted commercial and research use, and was published in May 2026, alongside smaller 0.5B, 1B, and 3B siblings in the same BitCPM-CANN family.
BAAR2 150M
aixk · 168M · runs from 0.4 GB
BAAR2 150M is a 168M-parameter open language model from aixk. It supports a context window of up to 512 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
OxCoder 9B
OrionLLM · 9.4B · runs from 19.4 GB
OxCoder 9B is a 9.4B-parameter open language model from OrionLLM. It supports a context window of up to 262,144 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
AI21 Jamba Reasoning 3B
AI21 Labs · 3.2B · runs from 1.7 GB
AI21 Jamba Reasoning 3B is a 3.2B-parameter open language model from AI21 Labs in the Jamba family. It supports a context window of up to 262,144 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Qwen3.8 Flash Coder 85gb BF16
Jab1718 · 42.6B · runs from 85.6 GB
Qwen3.8 Flash Coder 85gb BF16 is a 42.6B-parameter open language model from Jab1718 in the Qwen 3.8 family. It supports a context window of up to 262,144 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Qwen3 VL 8B Heretic 1.3.0
DreamFast · 8.8B · runs from 4.3 GB
Qwen3 VL 8B Heretic 1.3.0 is a 8.8B-parameter open language model from DreamFast in the Qwen 3 family. It supports a context window of up to 262,144 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Mellum2 12B A2.5B Base
JetBrains · 12.1B · runs from 24.7 GB
Mellum2 12B A2.5B Base is a 12.1B-parameter open language model from JetBrains in the Mellum family. It supports a context window of up to 131,072 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
OUI 1
thesysdev · 25.8B · runs from 52.3 GB
OUI 1 is a 25.8B-parameter open language model from thesysdev. It supports a context window of up to 262,144 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
OpenThinker3 1.5B
open-thoughts · 1.5B · runs from 1.0 GB
OpenThinker3 1.5B is a 1.5B-parameter open language model from open-thoughts. It supports a context window of up to 32,768 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Mistral Nemo 2407 12B Thinking Claude Gemini GPT5.2 Uncensored HERETIC
DavidAU · 12.2B · runs from 5.9 GB
Mistral Nemo 2407 12B Thinking Claude Gemini GPT5.2 Uncensored HERETIC is a 12.2B-parameter open language model from DavidAU in the Mistral family. It supports a context window of up to 1,024,000 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Qwen35B Agent R2
hotdogs · 34.7B · runs from 15.1 GB
Qwen35B Agent R2 is a 34.7B-parameter open language model from hotdogs in the Qwen family. It supports a context window of up to 262,144 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
SpatialLM1.1 Qwen 0.5B
manycore-research · 604M · runs from 1.5 GB
SpatialLM1.1 Qwen 0.5B is a 604M-parameter open language model from manycore-research in the Qwen family. It supports a context window of up to 32,768 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
INTELLECT 3
PrimeIntellect · 106.9B · runs from 45.8 GB
INTELLECT 3 is a 106.9B-parameter open language model from PrimeIntellect. It supports a context window of up to 131,072 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Qwen3.5 2B Claude 4.6 Opus Reasoning Distilled
Jackrong · 2.3B · runs from 1.4 GB
Qwen3.5 2B Claude 4.6 Opus Reasoning Distilled is a 2.3B-parameter open language model from Jackrong in the Qwen 3.5 family. It supports a context window of up to 262,144 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Thinkless 1.5B RL DeepScaleR
Vinnnf · 1.8B · runs from 1.1 GB
Thinkless 1.5B RL DeepScaleR is a 1.8B-parameter open language model from Vinnnf. It supports a context window of up to 32,768 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
LFM2 1.2B Extract
Liquid AI · 1.2B · runs from 0.9 GB
LFM2 1.2B Extract is a 1.2B-parameter open language model from Liquid AI in the LFM2 family. It supports a context window of up to 128,000 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Qwen3.5 4B Safety Thinking
MerlinSafety · 4.2B · runs from 2.3 GB
Qwen3.5 4B Safety Thinking is a 4.2B-parameter open language model from MerlinSafety in the Qwen 3.5 family. It supports a context window of up to 262,144 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
UltiMerge
OliviaRossi · 34.7B · runs from 69.7 GB
UltiMerge is a 34.7B-parameter open language model from OliviaRossi. It supports a context window of up to 262,144 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Bonsai 2 27B Mtp
decent-jawfish · 27B · runs from 12.6 GB
Bonsai 2 27B Mtp is a 27B-parameter open language model from decent-jawfish. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Qwen3.5 4B Claude 4.6 Opus Reasoning Distilled
Jackrong · 4.7B · runs from 2.5 GB
Qwen3.5 4B Claude 4.6 Opus Reasoning Distilled is a 4.7B-parameter open language model from Jackrong in the Qwen 3.5 family. It supports a context window of up to 262,144 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
OmniSVG1.1 8B
OmniSVG · 8B · runs from 16.4 GB
OmniSVG1.1 8B is a 8B-parameter open language model from OmniSVG. It supports a context window of up to 128,000 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
MiniMax Text 01
MiniMax · 456.1B · runs from 913.0 GB
MiniMax Text 01 is a 456.1B-parameter open language model from MiniMax in the MiniMax family. It supports a context window of up to 10,240,000 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Codegemma 7B IT
Google · 8.5B · runs from 4.0 GB
Codegemma 7B IT is a 8.5B-parameter open language model from Google in the Gemma family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Qwythos 9B v2
empero-ai · 9.7B · runs from 19.9 GB
Qwythos 9B v2 is a 9.7B-parameter open language model from empero-ai. It supports a context window of up to 1,048,576 tokens. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.
Gemma4 12B Mtp Assistant
sjakek · 12B · runs from 5.6 GB
Gemma4 12B Mtp Assistant is a 12B-parameter open language model from sjakek in the Gemma 4 family. See its VRAM requirements by quantization and which GPUs and Macs can run it locally below.