Best CPU-only LLM
Last updated 2026-05-26 · Page updated 2026-07-13
Top 7 open-source picks for running without a GPU, ranked by benchmark performance and real-world fit. Updated monthly.
Granite 4.0 H-Tiny 7B-A1B
IBM's edge-class hybrid MoE with 7B total and only 1B active parameters — Apache 2.0 licensed and built for embedded and low-cost serving.
Lucie 7B
A French-sovereign 7B model from OpenLLM-France, backed by CNRS and LINAGORA, with a fully transparent and auditable training corpus.
DeepSeek R1 Distill 7B
A 7B DeepSeek model distilled from R1 671B with explicit chain-of-thought reasoning. Surprisingly strong on AIME and MATH for its size.
Qwen 2.5 VL 7B
A 7B vision-language model from Alibaba with state-of-the-art results in its class, scoring 95.7 on DocVQA. Handles hour-long video, bounding-box grounding, and multilingual OCR.
Qwen 2.5 Omni 7B
Alibaba's first true omni-modal open model — text, image, audio, and video in, with text and speech out. A research-grade preview rather than a production-ready release.
Phi-4 Multimodal 5.6B
Microsoft's 5.6B multimodal model — text, image, and audio in, text out — using a Mixture-of-LoRAs design. Accepts roughly 2.8 hours of audio per request.
Pleias-RAG 1B
A 1.2B RAG-specialized model from PleIAs with built-in citation and grounding behavior. Beats most sub-4B small language models on HotPotQA.
Which GPU should you buy to run Granite 4.0 H-Tiny 7B-A1B?
To run Granite 4.0 H-Tiny 7B-A1B locally at Q4, you need ~4 GB of VRAM. The best value for this is a RTX 5060 (8 GB VRAM).
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Frequently asked questions
What is the best local LLM for running without a GPU?
Granite 4.0 H-Tiny 7B-A1B tops this ranking — a 7B model, licensed under Apache 2.0, needing about 4 GB of VRAM at Q4 quantization. See the full list below for the runner-ups and how they compare.
How much VRAM do I need to run Granite 4.0 H-Tiny 7B-A1B?
At Q4 quantization, Granite 4.0 H-Tiny 7B-A1B needs about 4 GB of VRAM and fits comfortably on a single 24 GB GPU.
Which of these models fit an 8 GB GPU?
At Q4 quantization, Granite 4.0 H-Tiny 7B-A1B, Lucie 7B, DeepSeek R1 Distill 7B, Qwen 2.5 VL 7B, Qwen 2.5 Omni 7B and 2 more fit within 8 GB of VRAM.
Are the models on this running without a GPU list free for commercial use?
Licenses across this list include Apache 2.0, MIT. Check the specific license of each model on its catalog page before deploying commercially, as terms vary by author.
What context window do these models support?
Context windows on this list range from 2k to 125k tokens, depending on the model.