Arcee.ai, a startup centered on growing small AI fashions for industrial and enterprise use, is opening up its personal AFM-4.5B mannequin for restricted free utilization by small corporations — posting the weights on Hugging Face and permitting enterprises that make lower than $1.75 million in annual income to make use of it with out cost underneath a customized “Arcee Mannequin License.“
Designed for real-world enterprise use, the 4.5-billion-parameter mannequin — a lot smaller than the tens of billions to trillions of main frontier fashions — combines value effectivity, regulatory compliance, and powerful efficiency in a compact footprint.
AFM-4.5B was one in all a two half launch made by Arcee final month, and is already “instruction tuned,” or an “instruct” mannequin, which is designed for chat, retrieval, and inventive writing and might be deployed instantly for these use circumstances in enterprises. One other base mannequin was additionally launched on the time that was not instruction tuned, solely pre-trained, permitting extra customizability by prospects. Nevertheless, each had been solely out there via industrial licensing phrases — till now.
Arcee’s chief know-how officer (CTO) Lucas Atkins additionally famous in a submit on X that extra “dedicated models for reasoning and tool use are on the way,” as properly.
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“Building AFM-4.5B has been a huge team effort, and we’re deeply grateful to everyone who supported us We can’t wait to see what you build with it,” he wrote in one other submit. “We’re just getting started. If you have feedback or ideas, please don’t hesitate to reach out at any time.”
The mannequin is obtainable now for deployment throughout a wide range of environments —from cloud to smartphones to edge {hardware}.
It’s additionally geared towards Arcee’s rising listing of enterprise prospects and their wants and desires — particularly, a mannequin educated with out violating mental property.
Arcee notes it labored with third-party knowledge curation agency DatologyAI to use methods like supply mixing, embedding-based filtering, and high quality management — all geared toward minimizing hallucinations and IP dangers.
Targeted on enterprise buyer wants
AFM-4.5B is Arcee.ai’s response to what it sees as main ache factors in enterprise adoption of generative AI: excessive value, restricted customizability, and regulatory issues round proprietary giant language fashions (LLMs).
Over the previous yr, the Arcee staff held discussions with greater than 150 organizations, starting from startups to Fortune 100 corporations, to know the constraints of present LLMs and outline their very own mannequin targets.
Based on the corporate, many companies discovered mainstream LLMs — comparable to these from OpenAI, Anthropic, or DeepSeek — too costly and troublesome to tailor to industry-specific wants. In the meantime, whereas smaller open-weight fashions like Llama, Mistral, and Qwen provided extra flexibility, they launched issues round licensing, IP provenance, and geopolitical threat.
AFM-4.5B was developed as a “no-trade-offs” various: customizable, compliant, and cost-efficient with out sacrificing mannequin high quality or usability.
AFM-4.5B is designed with deployment flexibility in thoughts. It may function in cloud, on-premise, hybrid, and even edge environments—due to its effectivity and compatibility with open frameworks comparable to Hugging Face Transformers, llama.cpp, and (pending launch) vLLM.
The mannequin helps quantized codecs, permitting it to run on lower-RAM GPUs and even CPUs, making it sensible for functions with constrained sources.
Firm imaginative and prescient secures backing
Arcee.ai’s broader technique focuses on constructing domain-adaptable, small language fashions (SLMs) that may energy many use circumstances inside the similar group.
As CEO Mark McQuade defined in a VentureBeat interview final yr, “You don’t need to go that big for business use cases.” The corporate emphasizes quick iteration and mannequin customization as core to its providing.
This imaginative and prescient gained investor backing with a $24 million Sequence A spherical again in 2024.
Inside AFM-4.5B’s structure and coaching course of
The AFM-4.5B mannequin makes use of a decoder-only transformer structure with a number of optimizations for efficiency and deployment flexibility.
It incorporates grouped question consideration for sooner inference and ReLU² activations instead of SwiGLU to help sparsification with out degrading accuracy.
Coaching adopted a three-phase strategy:
Pretraining on 6.5 trillion tokens of normal knowledge
Midtraining on 1.5 trillion tokens emphasizing math and code
Instruction tuning utilizing high-quality instruction-following datasets and reinforcement studying with verifiable and preference-based suggestions
To fulfill strict compliance and IP requirements, the mannequin was educated on almost 7 trillion tokens of knowledge curated for cleanliness and licensing security.
A aggressive mannequin, however not a pacesetter
Regardless of its smaller measurement, AFM-4.5B performs competitively throughout a broad vary of benchmarks. The instruction-tuned model averages a rating of fifty.13 throughout analysis suites comparable to MMLU, MixEval, TriviaQA, and Agieval—matching or outperforming similar-sized fashions like Gemma-3 4B-it, Qwen3-4B, and SmolLM3-3B.
Multilingual testing exhibits the mannequin delivers robust efficiency throughout greater than 10 languages, together with Arabic, Mandarin, German, and Portuguese.
Based on Arcee, including help for extra dialects is simple attributable to its modular structure.
AFM-4.5B has additionally proven robust early traction in public analysis environments. In a leaderboard that ranks conversational mannequin high quality by consumer votes and win charge, the mannequin ranks third general, trailing solely Claude Opus 4 and Gemini 2.5 Professional.
It boasts a win charge of 59.2% and the quickest latency of any prime mannequin at 0.2 seconds, paired with a technology pace of 179 tokens per second.
Constructed-in help for brokers
Along with normal capabilities, AFM-4.5B comes with built-in help for operate calling and agentic reasoning.
These options intention to simplify the method of constructing AI brokers and workflow automation instruments, decreasing the necessity for advanced immediate engineering or orchestration layers.
This performance aligns with Arcee’s broader technique of enabling enterprises to construct customized, production-ready fashions sooner, with decrease complete value of possession (TCO) and simpler integration into enterprise operations.
What’s subsequent for Arcee?
AFM-4.5B represents Arcee.ai’s push to outline a brand new class of enterprise-ready language fashions: small, performant, and absolutely customizable, with out the compromises that always include both proprietary LLMs or open-weight SLMs.
With aggressive benchmarks, multilingual help, robust compliance requirements, and versatile deployment choices, the mannequin goals to fulfill enterprise wants for pace, sovereignty, and scale.
Whether or not Arcee can carve out a long-lasting function within the quickly shifting generative AI panorama will rely upon its skill to ship on this promise. However with AFM-4.5B, the corporate has made a assured first transfer.
Correction: This piece initially misspelled Arcee’s identify in a number of locations. We’ve since up to date the article to appropriate it and remorse the errors.
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