Top 10 Open Source LLMs

The multimodal MoE powerhouse. Llama 4 Scout offers an unprecedented 10M token context, while Maverick delivers GPT-4o class performance. Native image + text understanding sets the new open-source standard.

GPT-5 level reasoning at 100x lower cost. DeepSeek V3.2-Speciale achieves gold-medal performance in IMO, IOI, and ICPC 2025. The new Sparse Attention mechanism revolutionizes long-context efficiency.

The efficiency king. 24B parameters that outperform 70B models while running 3x faster. Apache 2.0 licensed, multimodal, and runs on a single RTX 4090 or Mac with 32GB RAM.

The multilingual reasoning master. Qwen 3's hybrid "thinking" mode rivals o1-level reasoning, while supporting 119 languages. Context extends to 1M+ tokens for massive document analysis.

OpenAI's entry into open weights. The 120B parameter MoE model (5.1B active) is optimized for agentic workflows with native tool use, running on a single H100 GPU.

Google's multimodal open gem. Native image + text understanding with 140+ language support. The 27B model runs on consumer GPUs while rivaling much larger models.

Small but mighty. Phi-4 punches way above its weight class, delivering exceptional reasoning and coding capabilities that run efficiently on consumer hardware.

The massive MoE. With 314B parameters, Grok-1 is a beast of a model known for its "spicy" personality and strong general knowledge. A unique option for those with the compute.

A strong bilingual contender. Yi-1.5 (34B) offers a great balance of performance and size, excelling in both English and Chinese tasks with improved coding skills.

The RAG specialist. Optimized for retrieval-augmented generation and tool use, Command R+ is the go-to open model for building complex, data-driven enterprise assistants.