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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 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 price effectivity, regulatory compliance, and powerful efficiency in a compact footprint.
AFM-4.5B was one among 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 inventive writing and could 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 clients. Nevertheless, each had been solely out there by industrial licensing phrases — till now.
Acree’s chief expertise officer (CTO) Lucas Atkins additionally famous in a put up on X that extra “devoted fashions for reasoning and gear use are on the way in which,” as properly.
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“Constructing AFM-4.5B has been an enormous workforce effort, and we’re deeply grateful to everybody who supported us We will’t wait to see what you construct with it,” he wrote in one other put up. “We’re simply getting began. If in case you have suggestions or concepts, please don’t hesitate to succeed in out at any time.”
The mannequin is obtainable now for deployment throughout quite a lot of environments —from cloud to smartphones to edge {hardware}.
It’s additionally geared towards Acree’s rising checklist of enterprise clients and their wants and desires — particularly, a mannequin educated with out violating mental property.
As Acree wrote in its preliminary AFM-4.5B announcement put up final month: “Super effort was put in the direction of excluding copyrighted books and materials with unclear licensing.”
Acree notes it labored with third-party information curation agency DatologyAI to use strategies like supply mixing, embedding-based filtering, and high quality management — all aimed toward minimizing hallucinations and IP dangers.
Centered 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 price, restricted customizability, and regulatory considerations round proprietary massive language fashions (LLMs).
Over the previous 12 months, the Arcee workforce 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 targets.
In keeping with the corporate, many companies discovered mainstream LLMs — akin 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 provided extra flexibility, they launched considerations round licensing, IP provenance, and geopolitical danger.
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 will possibly function in cloud, on-premise, hybrid, and even edge environments—due to its effectivity and compatibility with open frameworks akin 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 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 circumstances throughout the identical group.
As CEO Mark McQuade defined in a VentureBeat interview final 12 months, “You don’t have to go that huge for enterprise use circumstances.” 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 help sparsification with out degrading accuracy.
Coaching adopted a three-phase method:
- 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 fulfill strict compliance and IP requirements, the mannequin was educated on almost 7 trillion tokens of information curated for cleanliness and licensing security.
A aggressive mannequin, however not a pacesetter
Regardless of its smaller dimension, AFM-4.5B performs competitively throughout a broad vary of benchmarks. The instruction-tuned model averages a rating of fifty.13 throughout analysis suites akin 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 keeping with Arcee, including help for added dialects is easy as a result 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 consumer votes and win charge, the mannequin ranks third total, trailing solely Claude Opus 4 and Gemini 2.5 Professional.
It boasts a win charge of 59.2% and the quickest latency of any high mannequin at 0.2 seconds, paired with a technology pace of 179 tokens per second.
Constructed-in help for brokers
Along with basic capabilities, AFM-4.5B comes with built-in help for perform 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 price 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 absolutely customizable, with out the compromises that always include both proprietary LLMs or open-weight SLMs.
With aggressive benchmarks, multilingual help, sturdy compliance requirements, and versatile deployment choices, the mannequin goals to satisfy enterprise wants for pace, sovereignty, and scale.
Whether or not Arcee can carve out an enduring function within the quickly shifting generative AI panorama will depend upon its skill to ship on this promise. However with AFM-4.5B, the corporate has made a assured first transfer.
