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Small Language Model (SLM) Market worth $5.45 billion by 2032- Exclusive Report by MarketsandMarkets™

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DELRAY BEACH, Fla., March 26, 2025 /PRNewswire/ — The Small Language Model Market is slated to expand from USD 0.93 billion in 2025 to USD 5.45 billion by 2032, at a substantial CAGR of 28.7% over the forecast period, according to a new report by MarketsandMarkets™.

 

Browse in-depth TOC on “Small Language Model Market”

200 – Tables
50 – Figures
250 – Pages

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Scope of the Report

Report Metrics

Details

Market size available for years

2020–2032

Base year considered

2024

Forecast period

2025–2032

Forecast units

USD (Billion)

Segments covered

Offering, Deployment Mode, Application, Data Modality, Model Size, End User, and Region

Geographies covered

North America, Europe, Asia Pacific, Middle East & Africa, and Latin America

Companies covered

Microsoft (US), IBM (US), Infosys (India), Mistral AI (France), AWS (US), Meta (US), Anthropic (US), Cohere (Canada), OpenAI (US), Alibaba (China), Arcee AI (US), Deepseek (China), Upstage AI (US), AI21 Labs (Israel), Krutrim (India), Stability AI (UK), Together AI (US), Lamini AI (US), Groq (US), Malted.ai (UK), Predibase (US), Cerebras (US), Ollama (US), Fireworks AI (US), Snowflake (US), and Prem AI (Switzerland).

With the growing demand for domain-specific AI that prioritizes performance over computational complexity, the Small Language Model (SLM) market is gaining momentum. In contrast to Large Language Models (LLMs), SLMs are tailored for deployment on low-power devices, facilitating real-time processing and improved data privacy without a heavy dependency on cloud infrastructure. Efforts and accuracy in model compression techniques such as pruning, quantization or knowledge distillation are further growing the market. Additionally, the rising demand for privacy-focused AI models and specialized applications in sectors like healthcare, finance, manufacturing, and legal industries is driving adoption. OpenAI, Microsoft, Meta, and Cohere are among the leading technology providers that have invested heavily in scalable, flexible SLMs tailored to specific business needs. This is exacerbated by the growing demand for model training and fine-tuning services, as companies aim to improve model performance without sacrificing efficiency. Small language models are expected to experience significant growth as the industry continues to evolve in architecture optimization, deployment frameworks, and fine-tuning techniques. As businesses prioritize efficiency, privacy, and adaptability, the uptake of SLMs is expected to increase across diverse industries and applications.

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By model size, SLMs less than 2 billion parameters to register fastest growth rate during the forecast period, driven by high energy efficiency and domain-specific precision on edge device deployments

Due to their efficiency, cost-effectiveness, and flexibility, small language models with less than 2 billion parameters are expected to grow the fastest among all models. Unlike larger models that demand significant computational power and memory, SLMs with parameters under 2 billion are designed for deployment on edge devices like smartphones, IoT devices, and embedded systems, allowing for real-time processing without relying on cloud services. Their smaller size allows faster training, fine-tuning, and inference, which significantly reduces operational costs and energy consumption. Industries that prioritize data privacy and compliance, such as healthcare, finance sector, and legal industry, are especially attracted to these models because they offer on-device processing which reduces the risk of data breaches. Furthermore, companies are increasingly opting for smaller models for domain-specific tasks, where precision and efficiency are more important than general-purpose capabilities. Progress in model compression techniques, including pruning, quantization, and knowledge distillation, has also propelled the emergence of powerful but compact models. Their adoption is being bolstered by the availability of tools that are easy to use for training and fine-tuning smaller models. With businesses increasingly relying on AI to achieve optimal performance, accuracy, and cost, SLMs priced below 2 billion are expected to experience significant growth.

Increasing demand for multilingual text generation for NLP and widespread adoption of text-based AI tools has text segment as the largest data modality by market share in 2025

Text is expected to be the largest data modality in the Small Language Model (SLM) market by market share due to its foundational role in natural language processing (NLP) and the widespread demand for text-based AI applications. Unlike other data types like images, audio, or video, text is the most commonly used form of communication across industries, including healthcare, finance, legal, customer service, and education. The most significant advantages of SLMs are their specialized areas, such as summarization, translation, sentiment analysis and sentiment modeling, information retrieval, question-answering, and chatbots. The rising demand for domain-specific models trained on proprietary text data enhances their accuracy and relevance, reinforcing the importance of text. Moreover, the vast amount of textual data from websites, documents, emails, reports, and social media makes it a useful resource for training SLMs. Techniques for model compression, including pruning, quantization, and knowledge distillation, have allowed for the deployment of efficient SLMs that can process text data in real-time on low-power devices. Also, text-based models are easily adjustable and can be tailored according to industry needs, which may lead to their widespread adoption. As industries increasingly integrate AI-driven text analysis tools to boost productivity, efficiency, and decision-making, text will remain a dominant force in the SLM market.

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Asia Pacific is set to become the fastest growing region over the forecast period, fueled by rising uptake of localized SMLs, and increasing demand for cost-effective AI models

Due to rapid digital transformation, increased investments in AI, and strong government support for AI development, the SLM market in Asia Pacific is expected to grow rapidly within 2025 to 2032. Countries such as China, India, Japan, and South Korea are vigorously advancing AI technologies to boost productivity across healthcare, finance, manufacturing, and customer service sectors. The region’s large population and diverse languages offer a unique opportunity for the development of localized, domain-specific SLMs that cater to regional needs. Furthermore, the rising demand for efficient, privacy-preserving AI solutions in compliance-driven industries, like healthcare and finance, is accelerating adoption. The development of edge-compatible models that work well on low-power devices is becoming increasingly important in Asia Pacific, with companies focusing on improving efficiency and decreasing reliance on cloud infrastructure.  Market expansion is also being driven by government-sponsored initiatives that promote AI research, funding and strategic partnerships with private companies. Moreover, the cost-effectiveness and scalability of SLMs are especially attractive to small and medium-sized enterprises (SMEs) looking for budget-friendly AI solutions. With ongoing investment and research in AI technologies, the Asia Pacific is set to witness the fastest growth in the SLM market.

Top Key Companies in Small Language Model Market:

The major players in the Small Language Model Market include Microsoft (US), IBM (US), Infosys (India), Mistral AI (France), AWS (US), Meta (US), Anthropic (US), Cohere (Canada), OpenAI (US), Alibaba (China), Arcee AI (US), Deepseek (China), Upstage AI (US), AI21 Labs (Israel), Krutrim (India), Stability AI (UK), Together AI (US), Lamini AI (US), Groq (US), Malted.ai (UK), Predibase (US), Cerebras (US), Ollama (US), Fireworks AI (US), Snowflake (US), and Prem AI (Switzerland).

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About MarketsandMarkets™

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MarketsandMarkets™ is a blue ocean alternative in growth consulting and program management, leveraging a man-machine offering to drive supernormal growth for progressive organizations in the B2B space. With the widest lens on emerging technologies, we are proficient in co-creating supernormal growth for clients across the globe.

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FULTON FINANCIAL CORPORATION APPOINTS DAVID S. SCHULZ TO BOARD OF DIRECTORS

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LANCASTER, Pa., July 21, 2026 /PRNewswire/ — Fulton Financial Corporation (NASDAQ: FULT) (“Fulton”) today announced the appointment of David S. Schulz as a member of its board of directors (the “Board”) for a term commencing September 14, 2026 and expiring at Fulton’s 2027 annual meeting of shareholders.

“We’re excited to welcome Dave to Fulton’s board of directors,” said Curt Myers, Fulton Chairman, CEO, and President. “Dave brings extensive financial leadership experience gained through more than a decade of service with publicly traded companies. His expertise in finance, strategic planning, risk, and mergers and acquisitions will provide valuable perspective as we continue to execute our growth strategy and create long-term value for our shareholders, customers and communities.”

With the addition of Schulz, Fulton’s Board will have 11 members, and he will serve on the Audit and Risk committees. Schulz has also been appointed to the board of directors of Fulton’s banking subsidiary, Fulton Bank, N.A.

Schulz served as Senior Vice President and Chief Financial Officer of Wesco International, Inc. (“Wesco”) from 2016 to June 2020, Executive Vice President and Chief Financial Officer of Wesco from June 2020 to February 2026 and as Executive Vice President and Special Advisor to the CEO of Wesco from February 2026 until his retirement on May 31, 2026. 

Prior to joining Wesco, Schulz served as Senior Vice President and Chief Operating Officer of Armstrong Flooring, Inc. and was previously Senior Vice President and Chief Financial Officer of Armstrong World Industries, Inc. and Vice President of Finance of the Armstrong Building Products division.

Before joining Armstrong World Industries in 2011, he held various financial leadership roles with Procter & Gamble and The J.M. Smucker Company. He was also an officer in the United States Marine Corps.

In 2025, Schulz joined the board of Sterling Infrastructure, Inc., and he was appointed as chair of the audit committee in 2026. He also serves on the company’s compensation and talent development committee.

ABOUT FULTON FINANCIAL CORPORATION

Fulton, a $34 billion Lancaster, Pa.-based financial holding company, has more than 3,400 employees and operates more than 215 financial centers in Pennsylvania, New Jersey, Maryland, Delaware and Virginia through Fulton Bank, N.A. Additional information on Fulton can be found at https://investor.fultonbank.com.

Contact: Steve Trapnell
717-291-2739

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SOURCE Fulton Financial Corporation

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Octavio Marquez Elected to MSA Safety Board of Directors

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PITTSBURGH, July 21, 2026 /PRNewswire/ — The Board of Directors of MSA Safety Inc. (NYSE: MSA), a global leader in the development of advanced industrial safety technology products and solutions, today announced that Octavio Marquez, president and chief executive officer of Diebold Nixdorf, has been elected to the company’s Board of Directors. His election was part of the MSA Board’s regular succession plans.

“We are very pleased to have the opportunity to add Octavio to the MSA Board,” said Robert A. Bruggeworth, MSA chairman. “He brings a broad range of executive leadership experience, including strategy development, capital allocation, business transformation and serving international markets, which will serve MSA well.”

“Octavio’s perspectives will be an asset to me and our entire Executive Leadership Team,” said Steven C. Blanco, MSA president and CEO. “It is a pleasure to welcome Octavio to MSA, and I look forward to working with him.”

Mr. Marquez joined Diebold Nixdorf in 2014 and has held senior leadership roles across the company’s Global Banking organization and its Americas region, including as executive vice president of Global Banking and senior vice president of the Americas. Before joining Diebold Nixdorf, Mr. Marquez held leadership positions at Dell EMC, Hewlett Packard Enterprise, IBM and NCR.

Diebold Nixdorf automates, digitizes and transforms the way people bank and shop. As a partner to the majority of the world’s top 100 financial institutions and top 25 global retailers, its integrated solutions connect digital and physical channels conveniently, securely and efficiently for millions of customers every day. Headquartered in North Canton, Ohio, Diebold Nixdorf employs approximately 20,000 employees globally, supporting more than 100 countries.

Mr. Marquez holds a degree in business and finance from Universidad Iberoamericana and has completed executive education programs at MIT Sloan, The Wharton School and The University of Texas at Austin.

About MSA Safety

MSA Safety Incorporated (NYSE: MSA) is the global leader in advanced industrial safety technology products and solutions. Driven by its singular mission of safety, the company has been at the forefront of safety innovation since 1914, protecting workers and facility infrastructure around the world across a broad range of diverse end markets while creating sustainable value for shareholders. With 2025 revenues of $1.9 billion, MSA Safety is headquartered in Cranberry Township, Pennsylvania, and employs a team of approximately 5,300 associates across its more than 40 international locations. For more information, please visit www.MSASafety.com.

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SOURCE MSA Safety

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BlueFolder Field Service Software Launches New AI-Powered Features to Transform How Teams Work

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New AI capabilities instantly surface customer insights and transform technician notes into actionable summaries to help field service teams work faster, stay aligned, and deliver better service

AUBURN, Ala., July 21, 2026 /PRNewswire/ — BlueFolder field service software recently announced the launch of two powerful new AI features: AI-Powered Customer Summaries and AI-Powered Field Notes Summarization. Together, these capabilities are designed to eliminate the time-consuming, manual work of reviewing fragmented customer records and lengthy technician notes—giving field service teams instant clarity to respond faster, make smarter decisions, and deliver exceptional service.

BlueFolder expands it’s field service and work order management suite with two exciting new AI field service features.

Built directly into the BlueFolder platform, both features leverage artificial intelligence to automatically compile and summarize complex, unstructured data into clear, easy-to-read overviews. The result: technicians, dispatchers, and managers always have the context they need, right when they need it.

AI-Powered Customer Summaries

As field service organizations grow, customer information becomes increasingly scattered across emails, service request logs, and communication histories. BlueFolder’s AI Customer Summary feature addresses this challenge head-on by consolidating those interactions into a single, actionable snapshot.

Instead of manually digging through multiple records before a service call or customer interaction, teams can now access a real-time summary highlighting key concerns, past service activity, and recent updates. The feature goes beyond basic summarization and surfaces critical business insights such as equipment past due for maintenance, approaching warranty expirations, and proactive revenue opportunities, empowering teams to recommend follow-ups or upgrades directly from the customer record.

Built-in traceability links each summary back to its original source communications, so users can validate insights with confidence, ensuring both speed and accuracy in every customer interaction.

AI-Powered Field Notes Summarization

In many service organizations, technicians log updates across multiple visits, often resulting in long, fragmented notes that are difficult to review at a glance. BlueFolder’s AI Field Notes Summarization feature solves this by automatically condensing multiple technician entries into a structured summary that highlights key milestones, actions taken, and next steps.

Rather than scrolling through pages of updates, managers and dispatchers can immediately understand job status and determine what needs to happen next, improving alignment between field and office teams, accelerating decision-making, and reducing miscommunication. The feature is especially valuable for complex or multi-day jobs, where clear continuity and smooth technician handoffs are critical to delivering consistent service. It’s another featuring making BlueFolder’s work order management software capabilities stronger every day.

“History is one of the most powerful tools a service team has — the problem is it’s usually buried. BlueFolder’s new AI features fix that. Your team walks into every interaction already knowing the customer, knowing the equipment, and exactly where things stand. That changes the entire experience,” says John Shaw, VP, Technology, Service Operations.

AI as a Core Part of the BlueFolder Platform

The launch of these two features reflects BlueFolder’s broader commitment to embedding AI throughout its field service management software as an integrated layer of intelligence that makes every workflow smarter. Rather than requiring teams to change how they work, BlueFolder’s AI capabilities are designed to surface the right information at the right moment automatically, within the tools that technicians, dispatchers, and managers already use every day.

“AI is transforming what’s possible in field service, and BlueFolder is answering that call. These features are the result of deep platform expertise and a clear vision for where the industry is headed. We’re embedding intelligence throughout the platform because we know it makes our customers more competitive, more efficient, and better positioned to grow,” says Stephen Myslicki, Group President of Field Services.

Availability

Both AI-Powered Customer Summaries and AI-Powered Field Notes Summarization are available now to BlueFolder customers as optional, easy-to-enable features within the platform. They are part of BlueFolder’s growing suite of AI-driven capabilities designed to help field service organizations operate more efficiently and scale with confidence.

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SOURCE BlueFolder

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