Microsoft AI issued for Pheni-4-4 – 14b parameter open-Weight Open-Weight Open-Weight Accessing strong performance in complex consultation activities
Despite the significant development of large languages (lllms), effective operations of activities – such as analyzing mathematical problems, editing codes, or codes – model skills. Models are effective in the NLP benches that are usually lacking the ability to create a number of chains for a number of consultation or show by solving complicated problems. In addition, while growing model size can improve the ability to consult, introduce accumulating costs and cost delivery, especially the use of education, engineering and decisions for supporting decisions.
Microsoft removes the Model model of the PI-4
Microsoft has just introduced a family of poli-4 consultation, consisting of three models-Pho-4 – Reasoning, Pho-4-Reasoning-Plusbesides Where-4-mini-consult. These models are found in the poly-4 of the 4Bs (Pyrames) and specialized to treat the complex tasks of mathematics, science facilities, and solving of software related problems. One exception receives a separate trade unique between the computational function and clarification of clarity. The pho-4 – Thinking is performed well with GaiPelidiation Fine, while the pheni-4-meter-pole-plus is a major learning process, especially advanced performance in the high-quality novel.
Open Weight models are issued with information for obvious training and testing logs, including benchmark design, and handled to catch birth and community-reaching faces.
Technical formation and method development
The Models of the Pho-4 Comment forms for the phase 4 for the intended development in exemplary behavior and regime training. The decisions of the important way include:
- Organized Planning (sft): An increase of 1,4m is made to focus on charges “on the borders” in the case – problems at the edge of the depths of the depths. COMPLES was found and sewed to emphasis on a variety of thinking rather than in mind the truth, and the answers were produced with the use of O3-mini in higher thought mode.
- Chain-of-Photating Format: Facilitate formal thinking, models are trained to produce outputs
- Untilized Contact Management: The Rocken Based Frequency has been converted to support the 32K key context, allows the default solution window, compatible mainly with long or long query formats.
- Emphasizing reading (pho-4-parehensing-plus): Using the Group Actitimization Optimization (GRPO), the phillo), the pho-4-Preaming-Plus was refined with a small set of selected ~ 6,400 statistics. The reward work is made from the right, short, and orderly, while punishing the zeal, repetition, and violation of violation.
Data-Data-Datrica Training and Format supports the better use of infested infection and model in all domains, including invisible consultation problems.
Assistance of Assessment and Comparison
Across the wide range of benches, poli-4 – Reasoning and pols-4-to-show-provide competitive effects associated with higher models:
The matter-4-PLUsing-plus shows strong performance and not only in the domain examination but also uses properly in the process and problems of integration such as TSP and 3Sat, without clear training in these areas. The work benefits are also recognized in responding to – the following (Iveval) and Long-Context (flex), suggesting the chain-of-templen to improve the use of a comprehensive model.
The main, Microsoft reports full distribution of diversity in all 50 types of running the Datasets such as AIME 2025, revealed the performance of the Modes such as O3-R1-pession.
The end and consequences
The policemetic models represent a difficult effort to advance the process of smaller models for formal reasons. By combining data-centric training, organizing of properties, a minority, Microsoft indicates that 14b-scale models can match or eliminate the largest systems in the activities that require uniformity.
The availability of open weight and the obvious measurement sets an example for future development in small llms, especially from the domains used in the interpretation, expense, and honesty is very important. The future work is expected to extend the skills of the StEM, promote translation techniques, and evaluate the intensely strengthening of the long areas.
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