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Memory tier - verified

Open models that fit in 128 GB

42 open-weight models of 63 in this directory fit in 128 GB of memory, sorted by total parameters, largest first.

42 models

Total params, largest first
42 open-weight models that fit in 128 GB, by total parameters, largest first
CommercialOllama
Mistral Medium 3.5 128Bmistralai/Mistral-Medium-3.5-128BMistral AI127.7B74.9 GBQ4_K_M GGUF262KCommercial use: Conditionsmistral-medium-3.5:128b
Devstral 2 123B Instruct 2512mistralai/Devstral-2-123B-Instruct-2512Mistral AI125B70.3 GB4bit MLX262KCommercial use: Conditionsdevstral-2:123b
NVIDIA Nemotron 3.5 Super VL 120B-A12Bnvidia/NVIDIA-Nemotron-3.5-Super-VL-120B-A12B-BF16NVIDIA124.5B12B active71.8 GBQ4_0 GGUF1.05MCommercial use: Yesnemotron-3.5-super:120b
Mistral Small 4 119B (2603)mistralai/Mistral-Small-4-119B-2603Mistral AI119.4B6.5B active67.8 GB4bit MLX262KCommercial use: Yes-No Ollama tag
gpt-oss-120bopenai/gpt-oss-120bOpenAI116.8B5.1B active62.3 GBMXFP4-Q4 MLX131KCommercial use: Yesgpt-oss:120b
Cohere Command A (03-2025)CohereLabs/c4ai-command-a-03-2025Cohere111.1B62.5 GB4bit MLX262KCommercial use: Nocommand-a:111b
GLM-4.5-Airzai-org/GLM-4.5-AirZ.ai110.5B12B active60.1 GB4bit MLX131KCommercial use: Yes-No Ollama tag
Llama 4 Scout 17B-16E Instructmeta-llama/Llama-4-Scout-17B-16E-InstructMeta108.6B17B active61.1 GB4bit MLX10MCommercial use: Conditionsllama4:scout
GLM-4.6Vzai-org/GLM-4.6VZ.ai107.7B61.9 GB4bit MLX128KCommercial use: Yes-No Ollama tag
Qwen3-Coder-NextQwen/Qwen3-Coder-NextAlibaba Cloud (Qwen)79.7B3B active44.8 GB4bit MLX262KCommercial use: Yesqwen3-coder-next
NVIDIA Nemotron 3.5 Bolt 74B-A9Bnvidia/NVIDIA-Nemotron-3.5-Bolt-74B-A9B-BF16NVIDIA74.9B9B active22.0 GB24GB (native 2-bit) GGUF262KCommercial use: Yesnemotron-3.5-bolt:74b-a9b
AI21 Jamba2 Miniai21labs/AI21-Jamba2-MiniAI21 Labs51.6B12B active31.2 GBQ4_K_M GGUF262KCommercial use: Yes-No Ollama tag
Qwen3.6-35B-A3BQwen/Qwen3.6-35B-A3BAlibaba Cloud (Qwen)36B3B active20.4 GB4bit MLX262KCommercial use: Yesqwen3.6:35b
Cohere Aya Expanse 32BCohereLabs/aya-expanse-32bCohere32.3B19.8 GBQ4_K_M GGUF131KCommercial use: Noaya-expanse:32b
Ai2 Olmo 3.1 32B Thinkallenai/Olmo-3.1-32B-ThinkAi232.2B18.1 GB4bit MLX66KCommercial use: Yesolmo-3.1:32b-think
NVIDIA Nemotron 3.5 Lightning 30B-A3Bnvidia/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-BF16NVIDIA31.6B3B active17.8 GB4bit MLX1.05MCommercial use: Yesnemotron-3.5-lightning:30b
Gemma 4 31Bgoogle/gemma-4-31B-itGoogle31.3B17.7 GBQ4_0 (QAT) GGUF262KCommercial use: Yesgemma4:31b
IBM Granite 4.2 30Bibm-granite/granite-4.2-30bIBM29.3B16.5 GB4bit MLX131KCommercial use: Yesgranite4.2:30b
Qwen3.8-27BQwen/Qwen3.8-27BAlibaba Cloud (Qwen)27.8B16.1 GB4bit MLX262KCommercial use: Yesqwen3.8:27b
Gemma 4 26B A4Bgoogle/gemma-4-26B-A4B-itGoogle25.8B3.8B active14.4 GBQ4_0 (QAT) GGUF262KCommercial use: Yesgemma4:26b
Devstral Small 2 24B Instruct 2512mistralai/Devstral-Small-2-24B-Instruct-2512Mistral AI24B14.3 GBQ4_K_M GGUF262KCommercial use: Yesdevstral-small-2:24b
Liquid AI LFM2.5-24B-A2BLiquidAI/LFM2.5-24B-A2BLiquid AI24B2.5B active13.6 GB4bit MLX131KCommercial use: Conditionslfm2.5:24b
gpt-oss-20bopenai/gpt-oss-20bOpenAI20.9B3.6B active11.2 GBMXFP4-Q4 MLX131KCommercial use: Yesgpt-oss:20b
Phi-4-reasoning-vision-15Bmicrosoft/Phi-4-reasoning-vision-15BMicrosoft15.1B30.2 GBOfficial BF1616KCommercial use: Yes-No Ollama tag
Phi-4microsoft/phi-4Microsoft14.7B8.2 GB4bit MLX16KCommercial use: Yesphi4:14b
Phi-4-reasoning-plusmicrosoft/Phi-4-reasoning-plusMicrosoft14.7B9.1 GBQ4_K_M GGUF33KCommercial use: Yesphi4-reasoning:plus
Ministral 3 14B Instruct 2512mistralai/Ministral-3-14B-Instruct-2512Mistral AI13.9B8.2 GBQ4_K_M GGUF262KCommercial use: Yesministral-3:14b
Gemma 4 12Bgoogle/gemma-4-12B-itGoogle12B6.7 GB4bit MLX262KCommercial use: Yesgemma4:12b
Qwen3.5-9BQwen/Qwen3.5-9BAlibaba Cloud (Qwen)9.7B5.7 GBQ4_K_M GGUF262KCommercial use: Yesqwen3.5:9b
Ministral 3 8B Instruct 2512mistralai/Ministral-3-8B-Instruct-2512Mistral AI8.9B5.2 GBQ4_K_M GGUF262KCommercial use: Yesministral-3:8b
IBM Granite 4.2 8Bibm-granite/granite-4.2-8bIBM8.8B4.9 GB4bit MLX131KCommercial use: Yesgranite4.2:8b
Cohere Command R7B (12-2024)CohereLabs/c4ai-command-r7b-12-2024Cohere8B4.5 GB4bit MLX131KCommercial use: Nocommand-r7b:7b
Gemma 4 E4Bgoogle/gemma-4-E4B-itGoogle8B5.0 GBQ4_K_M GGUF131KCommercial use: Yesgemma4:e4b
Ai2 Olmo Hybrid Instruct DPO 7Ballenai/Olmo-Hybrid-Instruct-DPO-7BAi27.4B14.9 GBOfficial BF1633KCommercial use: Yes-No Ollama tag
Gemma 4 E2Bgoogle/gemma-4-E2B-itGoogle5.1B3.1 GBQ4_K_M GGUF131KCommercial use: Yesgemma4:e2b
Qwen3.5-4BQwen/Qwen3.5-4BAlibaba Cloud (Qwen)4.7B2.7 GBQ4_K_M GGUF262KCommercial use: Yesqwen3.5:4b
Ministral 3 3B Instruct 2512mistralai/Ministral-3-3B-Instruct-2512Mistral AI3.8B2.1 GBQ4_K_M GGUF262KCommercial use: Yesministral-3:3b
Phi-4-mini-instructmicrosoft/Phi-4-mini-instructMicrosoft3.8B2.2 GB4bit MLX131KCommercial use: Yesphi4-mini:3.8b
Phi-4-mini-reasoningmicrosoft/Phi-4-mini-reasoningMicrosoft3.8B2.2 GB4bit MLX131KCommercial use: Yesphi4-mini-reasoning:3.8b
Liquid AI LFM2.5-2.6BLiquidAI/LFM2.5-2.6BLiquid AI2.7B1.6 GB4bit MLX131KCommercial use: Conditions-No Ollama tag
Qwen3.5-2BQwen/Qwen3.5-2BAlibaba Cloud (Qwen)2.3B1.3 GBQ4_K_M GGUF262KCommercial use: Yesqwen3.5:2b
Qwen3.5-0.8BQwen/Qwen3.5-0.8BAlibaba Cloud (Qwen)0.9B0.5 GBQ4_K_M GGUF262KCommercial use: Yesqwen3.5:0.8b

More memory? See what fits in 256 GB or browse every local model.

FAQ

How many open models fit in 128 GB?

42 of 63 models in this directory have a listed download of 108.8 GB or less, 85% of 128 GB.

What is the largest model that fits in 128 GB?

By total parameters, Mistral Medium 3.5 128B (127.7B), whose smallest listed download is 74.9 GB, the Q4_K_M GGUF build from unsloth/Mistral-Medium-3.5-128B-GGUF. Largest is a size, not a quality ranking.

Which of these can I use commercially?

34 of the 42 ship under licenses that allow commercial use outright. The license column shows the rest: some allow it with conditions and some do not.

Why 85% of 128 GB?

The download is only the weights. Running a model also needs memory for the context (the KV cache grows with every token you keep) and for the operating system and other apps, so this site leaves 15% free as a rule of thumb. A short context needs less; a long one can need more.

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