Arcee.ai, a startup targeted on creating 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 beneath a customized “Acree 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 Acree final month, and is already “instruction tuned,” or an “instruct” mannequin, which is designed for chat, retrieval, and artistic writing and may be deployed instantly for these use instances in enterprises. One other base mannequin was additionally launched on the time that was not instruction tuned, solely pre-trained, permitting extra customizability by clients. Nonetheless, each had been solely accessible by industrial licensing phrases — till now.
Acree’s chief know-how officer (CTO) Lucas Atkins additionally famous in a put up on X that extra “dedicated models for reasoning and tool use are on the way,” as nicely.
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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 put up. “We’re just getting started. If you have feedback or ideas, please don’t hesitate to reach out at any time.”
The mannequin is out there now for deployment throughout a wide range of environments —from cloud to smartphones to edge {hardware}.
It’s additionally geared towards Acree’s rising record of enterprise clients and their wants and desires — particularly, a mannequin skilled with out violating mental property.
Acree notes it labored with third-party information 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 12 months, the Arcee group held discussions with greater than 150 organizations, starting from startups to Fortune 100 corporations, to grasp the constraints of current LLMs and outline their very own mannequin objectives.
In accordance with the corporate, many companies discovered mainstream LLMs — similar to these from OpenAI, Anthropic, or DeepSeek — too costly and tough to tailor to industry-specific wants. In the meantime, whereas smaller open-weight fashions like Llama, Mistral, and Qwen supplied extra flexibility, they launched issues round licensing, IP provenance, and geopolitical threat.
AFM-4.5B was developed as a “no-trade-offs” different: customizable, compliant, and cost-efficient with out sacrificing mannequin high quality or usability.
AFM-4.5B is designed with deployment flexibility in thoughts. It might probably function in cloud, on-premise, hybrid, and even edge environments—because of its effectivity and compatibility with open frameworks similar 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 purposes with constrained assets.
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 instances inside the similar group.
As CEO Mark McQuade defined in a VentureBeat interview final 12 months, “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 quicker inference and ReLU² activations instead of SwiGLU to assist sparsification with out degrading accuracy.
Coaching adopted a three-phase strategy:
Pretraining on 6.5 trillion tokens of basic information
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 satisfy strict compliance and IP requirements, the mannequin was skilled on almost 7 trillion tokens of knowledge curated for cleanliness and licensing security.
A aggressive mannequin, however not a frontrunner
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 similar 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 sturdy efficiency throughout greater than 10 languages, together with Arabic, Mandarin, German, and Portuguese.
In accordance with Arcee, including assist for added dialects is easy on account of its modular structure.
AFM-4.5B has additionally proven sturdy early traction in public analysis environments. In a leaderboard that ranks conversational mannequin high quality by person votes and win fee, the mannequin ranks third general, trailing solely Claude Opus 4 and Gemini 2.5 Professional.
It boasts a win fee of 59.2% and the quickest latency of any high mannequin at 0.2 seconds, paired with a era velocity of 179 tokens per second.
Constructed-in assist for brokers
Along with basic capabilities, AFM-4.5B comes with built-in assist for operate calling and agentic reasoning.
These options purpose to simplify the method of constructing AI brokers and workflow automation instruments, lowering 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 quicker, with decrease complete value of possession (TCO) and simpler integration into enterprise operations.
What’s subsequent for Acree?
AFM-4.5B represents Arcee.ai’s push to outline a brand new class of enterprise-ready language fashions: small, performant, and totally customizable, with out the compromises that usually include both proprietary LLMs or open-weight SLMs.
With aggressive benchmarks, multilingual assist, sturdy compliance requirements, and versatile deployment choices, the mannequin goals to fulfill enterprise wants for velocity, sovereignty, and scale.
Whether or not Arcee can carve out an enduring position within the quickly shifting generative AI panorama will rely upon its capability to ship on this promise. However with AFM-4.5B, the corporate has made a assured first transfer.
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