Can I Run LLM Model Locally?

Qwen3.6 35B A3B

Alibaba · 36.0B · runs from 10.3 GB

6.0M 2.4K

Qwen3.6 35B A3B is a 36.0B-parameter open language model from Alibaba in the Qwen 3.6 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.

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Qwen3.6 27B

Alibaba · 27.8B · runs from 8.4 GB

5.2M 2.0K

Qwen3.6 27B is a 27.8B-parameter open language model from Alibaba in the Qwen 3.6 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.

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Qwen2.5 7B Instruct

Alibaba · 7.6B · runs from 2.7 GB

11.5M 1.4K

Qwen2.5 7B Instruct is a 7.6-billion parameter instruction-tuned model from Alibaba Cloud's Qwen 2.5 series. It supports a 128K token context window and is fine-tuned for conversational AI, instruction following, and general assistant tasks. Its efficient size makes it well-suited for local deployment on consumer GPUs with 8GB or more of VRAM. The model delivers strong performance for its parameter class across reasoning, multilingual understanding, and coding tasks. It benefits from the improved pretraining data and techniques of the Qwen 2.5 generation. Released under the Apache 2.0 license and widely supported by inference frameworks such as llama.cpp, vLLM, and Ollama.

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Gemma 4 26B A4B IT

Google · 26.5B · runs from 8.0 GB

13.2M 1.3K

Gemma 4 26B A4B IT is a 26.5B-parameter open language model from Google in the Gemma 4 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.

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Gemma 4 31B IT

Google · 32.7B · runs from 10.6 GB

12.0M 3.3K

Gemma 4 31B IT is a 32.7B-parameter open language model from Google in the Gemma 4 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.

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Llama 3.2 1B Instruct

Meta · 1.2B · runs from 0.4 GB

9.8M 1.5K

Meta Llama 3.2 1B Instruct is a 1-billion parameter instruction-tuned model from Meta, the smallest in the Llama 3.2 family. It is designed for ultra-lightweight deployment scenarios where minimal hardware resources are available, supporting a 128K token context window despite its compact size. This model is suitable for basic conversational tasks, text summarization, and simple instruction following. It can run on virtually any modern GPU and even on CPU-only setups with acceptable performance. Released under the Llama 3.2 Community License.

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