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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 underneath 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 robust efficiency in a compact footprint.
AFM-4.5B was one in every of 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 prospects. Nonetheless, each have been solely out there by means of industrial licensing phrases — till now.
Acree’s chief know-how officer (CTO) Lucas Atkins additionally famous in a publish on X that extra “devoted fashions for reasoning and gear use are on the best way,” as effectively.
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“Constructing AFM-4.5B has been an enormous crew effort, and we’re deeply grateful to everybody who supported us We are able to’t wait to see what you construct with it,” he wrote in one other publish. “We’re simply getting began. In case you have suggestions or concepts, please don’t hesitate to achieve out at any time.”
The mannequin is out there now for deployment throughout quite a lot of environments —from cloud to smartphones to edge {hardware}.
It’s additionally geared towards Acree’s rising record of enterprise prospects and their wants and needs — particularly, a mannequin educated with out violating mental property.
As Acree wrote in its preliminary AFM-4.5B announcement publish final month: “Super effort was put in direction of excluding copyrighted books and materials with unclear licensing.”
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.
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 value, restricted customizability, and regulatory considerations round proprietary massive language fashions (LLMs).
Over the previous 12 months, the Arcee crew held discussions with greater than 150 organizations, starting from startups to Fortune 100 corporations, to know the restrictions of present LLMs and outline their very own mannequin targets.
Based on 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 may function in cloud, on-premise, hybrid, and even edge environments—because of 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 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 have to go that massive for enterprise use instances.” The corporate emphasizes quick iteration and mannequin customization as core to its providing.
This imaginative and prescient gained investor backing with a $24 million Collection 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 assist sparsification with out degrading accuracy.
Coaching adopted a three-phase strategy:
- Pretraining on 6.5 trillion tokens of normal 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 practically 7 trillion tokens of knowledge 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 robust efficiency throughout greater than 10 languages, together with Arabic, Mandarin, German, and Portuguese.
Based on Arcee, including assist for added dialects is simple because of 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 high mannequin at 0.2 seconds, paired with a era velocity of 179 tokens per second.
Constructed-in assist for brokers
Along with normal capabilities, AFM-4.5B comes with built-in assist for operate calling and agentic reasoning.
These options goal 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 sooner, 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, robust compliance requirements, and versatile deployment choices, the mannequin goals to satisfy enterprise wants for velocity, 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 means to ship on this promise. However with AFM-4.5B, the corporate has made a assured first transfer.
