Best local LLM for rtx 2060
Top 7 open-source picks for rtx 2060, 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.
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.
OLMo 3 7B
Allen AI's fully open 7B model releasing weights, training data, and code under Apache 2.0. The reference choice for reproducible LLM research.
OLMoE 1B-7B Instruct
Allen AI's OLMoE is the only MoE released with weights, training data, and code fully open — 7B total with 1.3B active, matching Llama2-13B-Chat quality.
Mistral 7B Instruct
Mistral AI's breakout 7B instruct model. Still a go-to baseline for fast, low-cost inference and the most fine-tuned open-weight model in the wild.