What is Falcon 40B?
Falcon 40B is an open 40-billion-parameter large language model from the Technology Innovation Institute (TII) in Abu Dhabi. On release it was among the strongest openly available LLMs, topping open leaderboards, and it arrived with a genuinely permissive Apache 2.0 licence at a time when many strong open models had restrictive terms. Trained on TII's carefully filtered RefinedWeb dataset, Falcon demonstrated that high-quality web data plus efficient architecture could rival much larger or more restricted models.
How it was built
Falcon is a decoder-only transformer with architectural efficiencies (such as multi-query attention) that improve inference speed and scalability. Its standout ingredient is data: RefinedWeb, a large corpus built by aggressively filtering and deduplicating web text, which TII showed could produce excellent models with less reliance on curated sources. The family spans 7B, 40B and the larger 180B, each with base and Instruct (chat-tuned) variants, giving options across capability and hardware budgets.
What it is good at
Falcon 40B is a capable general-purpose model for text generation, summarisation, question answering, reasoning and some code, with the Instruct variant tuned for assistant-style chat. Its permissive licence made it especially attractive for commercial products and fine-tuning, and it has been used as a base for many downstream models. The smaller 7B is a popular lightweight option, while 40B targets stronger quality on a single multi-GPU setup.
Licensing & access
Falcon is released under Apache 2.0 — fully permissive for research and commercial use — with weights on Hugging Face and standard Transformers support. The 40B model needs substantial GPU memory (multi-GPU or quantisation), while the 7B runs on a single consumer GPU. Both base and Instruct variants are available, and the permissive licence means you can build and ship on top of it without restrictive conditions.
Practical considerations
For chat, use the Instruct variant; the base model is for completion and fine-tuning. At 40B you need real GPU memory, so budget multi-GPU hardware or use quantised builds. As an earlier-generation model, Falcon 40B has been surpassed on many benchmarks by newer open LLMs (Llama 3, Mistral, Qwen), and its context window is modest — weigh a newer model if you need top reasoning or long context. It can also hallucinate, so verify outputs.
How it compares
Falcon competed directly with Llama 2 and models like MPT and BLOOM. Its differentiators were a fully permissive Apache 2.0 licence and the RefinedWeb data approach, which made it a favourite for commercial builders. Against Llama 2 it traded blows on quality while offering a cleaner licence; against BLOOM it was stronger on English benchmarks. For a permissive, well-known open base — especially the efficient 7B — Falcon remains a solid choice.
Getting started
Load Falcon (start with Falcon-7B-Instruct to prototype, or 40B-Instruct for more quality) from Hugging Face with Transformers and prompt it; use the Instruct variant for chat and the base for fine-tuning. Run quantised builds to fit available GPUs, and given its permissive Apache 2.0 licence, build commercial applications freely — while benchmarking against newer open models such as Llama 3 or Mistral if you genuinely need the strongest possible quality for your use case.
