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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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11:11 Systems Announces Strategic Partnership with Cato Networks to Deliver SASE Solution for Distributed Enterprises

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New Managed Secure Access Service Edge (SASE) solution combines SD-WAN, cloud-native networking and security capabilities with 11:11’s connectivity, cyber resilience and cloud expertise

SYDNEY, July 22, 2026 /PRNewswire/ — 11:11 Systems, a leading managed infrastructure solutions provider, today announced the global availability of its 11:11 Managed Secure Access Service Edge (SASE) solution and a new strategic partnership with Cato Networks.

11:11 Managed SASE is a fully managed secure connectivity solution leveraging Cato Networks AI-native network security platform. This solution brings together intelligent SD-WAN, cloud-delivered security and global connectivity into a single offering. It enables organisations to simplify and secure access across branch offices, data centres, users and cloud environments, reducing complexity without sacrificing performance or control.

Built on the Cato Networks cloud-native SASE platform, 11:11 Managed SASE combines zero trust network access (ZTNA), firewall as a service (FWaaS), secure web gateway (SWG), cloud access security broker (CASB), advanced threat protection and centralised visibility into a unified managed experience. 11:11 also delivers 24x7x365 monitoring and support, incident management integration and operational accountability to help customers limit vendor sprawl, increase agility and free internal teams to focus on higher-value priorities.

The offering is backed by 11:11’s broader networking, cloud and cyber resilience capabilities. Through its global backbone, carrier-agnostic connectivity options and integrated portfolio spanning cloud, backup, disaster recovery and security services, 11:11 gives customers a practical path to modernise network and security architecture while strengthening resilience across the business.

“Enterprises are under pressure to support users, applications and locations that are more distributed than ever, while limiting complexity and improving security,” said Justin Giardina, CTO, 11:11 Systems. “Our Managed SASE solution provides customers with a unified approach to modernising networking and security, along with the visibility, support and flexibility they need to thrive in a rapidly changing environment.”

According to Karl Soderlund, global channel chief, Cato Networks, “As enterprises move beyond fragmented legacy networking and security stacks, they need a simpler way to gain visibility, context and control across hybrid work environments and reduce the operational burden on IT. Through our partnership, we can address these challenges head on and deliver end-to-end visibility and protection in a single service built for the reality of modern work.”

The joint offering is well suited for distributed enterprises, multi-site organisations, hybrid workforce initiatives, SD-WAN refreshes, security modernisation efforts and businesses with limited IT resources. 11:11 meets customers where they are by supporting existing environments, simplifying multi-vendor operations and serving as a single provider accountable for network, security, cloud and data integration.

This partnership expands 11:11’s Network as a Service portfolio and follows Forrester’s inclusion of 11:11 Systems in its report, “The Secure Access Service Edge Services Landscape, Q1 2026.”

About 11:11 Systems

11:11 Systems is a managed infrastructure solutions provider that empowers customers to modernise, protect and manage mission-critical applications and data, leveraging 11:11’s resilient cloud platform. Learn more at www.1111Systems.com and follow 11:11 on LinkedIn.

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SOURCE 11:11 Systems

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Crowell & Moring Expands Financial Services Group with Former UBS Bank USA General Counsel Cristina Diaz

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NEW YORK, July 21, 2026 /PRNewswire/ — Crowell & Moring has added Cristina Diaz, former executive director and general counsel of UBS Bank USA, and most recently head of legal for UBS’s U.S. Remediation Management Office, to the firm’s Financial Services Group as senior counsel in New York. Diaz brings more than two decades of in-house counsel and law firm experience in bank regulation, compliance, and risk management.

At Crowell, Diaz will counsel banks, fintechs, and digital assets companies on a broad range of bank regulatory matters, including charters and licensing, permissible activities, capital requirements, regulatory enforcement, M&A, and corporate governance. She will also counsel clients navigating the intersection of traditional banking and emerging financial services, including digital assets companies seeking to acquire or establish national banks, and banks exploring partnerships with fintechs and digital assets firms.

At UBS, Diaz advised on the firm’s most pressing regulatory matters, including most recently UBS Bank USA’s charter conversion from a Utah industrial bank to an OCC national bank and key compliance remediations. This work gave Diaz extensive experience navigating relationships with state and federal financial regulators. Earlier in her career, Diaz spent eight years at Davis Polk & Wardwell advising U.S. and foreign banks on bank regulatory matters, M&A, and capital markets transactions.

“Cristina is a highly experienced, solution-oriented attorney who brings deep knowledge in the bank regulatory space. She will be an enormous asset to the firm’s growing regulatory and transactional offerings to banks, digital assets businesses, and fintechs,” said Carlton Greene, Co-Chair of Crowell’s Financial Services Group.

“I am delighted to join Crowell & Moring and integrate my bank regulatory experience with the firm’s nationally-recognized digital assets practice. As traditional banking and emerging financial technologies continue to evolve, clients need actionable and sophisticated legal counsel. Crowell offers the collaborative platform to help institutions successfully execute their growth and compliance strategies,” said Diaz.

Diaz received her J.D. from New York University School of Law, where she was a member of the New York University Law Review, and received her B.A., summa cum laude, from New York University. She is fluent in Spanish.

About Crowell & Moring LLP
Crowell & Moring is an international law firm with operations in the United States, Europe, and MENA. Drawing on significant government, business, industry, and legal experience, the firm helps clients capitalize on opportunities and provides creative solutions to complex regulatory and policy, litigation, transactional, and intellectual property issues. The firm is consistently recognized for its commitment to pro bono service, as well as its comprehensive programs and initiatives to advance the professional and personal development of all members of the Crowell community.

Media Contact:
Email: prteam@crowell.com

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Quantinuum and SoftBank Corp. Publish Joint White Paper on Scaling Practical Quantum Computing Use Cases Toward the Fault-Tolerant Era

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The companies have published a joint white paper mapping commercially relevant quantum computing use cases in quantum chemistry and graph analytics to Quantinuum’s hardware roadmap.The paper provides a framework for assessing how advances in quantum hardware and algorithms, could affect when practical industrial applications become feasible.SoftBank Corp. and Quantinuum will use the roadmap to inform their exploration of future quantum AI data center services and related business models.

TOKYO and BROOMFIELD, Colo., July 22, 2026 /PRNewswire/ — Quantinuum (NASDAQ: QNT) and SoftBank Corp. (“SoftBank”) today announced the publication of “Quantum Computing Frontiers,” a joint white paper that maps two commercially-relevant quantum computing application areas against Quantinuum’s hardware roadmap. The analysis examines how advances in quantum hardware and algorithms could affect when these applications become practical for industrial use.

The paper focuses on two representative application domains that SoftBank is actively using Quantinuum’s systems to research: quantum chemistry for new materials discovery and energy research, and topological data analysis for large-scale graph analytics, including for telecommunications fraud detection. The authors anchor their assessment of the scalability of these two application areas against Quantinuum’s published hardware roadmap, examining how projected advances in hardware capabilities and algorithms may enable the commercial readiness of future industrial applications.

Building on this use-case roadmap, the paper also examines how quantum computing, AI, and high-performance computing could be integrated into future computing infrastructure. It considers how progress across successive hardware generations could inform future quantum AI data center services and related business models, a key focus of the Quantinuum and SoftBank partnership announced last year.

“The key takeaway of this study is that organizations do not need to wait for large-scale, fault-tolerant systems to explore where quantum computing can begin creating value,” said Duncan Jones, General Manager, Applications Group at Quantinuum. “By using today’s systems to develop, benchmark and refine applications in areas such as quantum chemistry and graph analytics, enterprises can build the technical and operational readiness needed for the next era of quantum-enabled computing.”

“The question is no longer whether quantum computing may deliver value, but rather which problem classes become executable at which stage of hardware maturity,” said Ryuji Wakikawa, Senior Vice President & CTO at SoftBank Corp. “However, we believe progress in hardware must be complemented by equally strong developments in quantum algorithms and the integration of quantum systems with AI and high-performance computing.”

The white paper discusses illustrative scenarios describing how representative applications, technology maturity, and potential market opportunities may evolve over time under stated assumptions. The analysis provided in the paper is intended to provide a conceptual framework for understanding potential market evolution and does not represent financial guidance or forecasts. These analyses are intended to support discussion of future technology development and should not be interpreted as commitments regarding commercialization, infrastructure investment, products, services, or financial performance.

The full white paper is available to download on the SoftBank and Quantinuum websites.

About SoftBank Corp.

Guided by the SoftBank Group’s corporate philosophy, “Information Revolution – Happiness for everyone,” SoftBank Corp. (TOKYO: 9434) operates telecommunications and IT businesses in Japan and globally. Building on its strong business foundation, SoftBank Corp. is aiming to activate the potential of AI across its businesses and drive implementation in line with its “Activate AI for Society” growth strategy. While further growing its telecom business, SoftBank is expanding its AI computing infrastructure and AI and Cloud service businesses with the aim of becoming a provider of Next-generation Social Infrastructure. To learn more, please visit https://www.softbank.jp/en/corp/

About Quantinuum

Quantinuum (NASDAQ: QNT) is a leading quantum computing company offering a full-stack platform designed to make quantum computing deployable in real-world environments. The company has commercially deployed multiple generations of quantum systems built on the well-established QCCD architecture, which it has implemented with novel designs and capabilities to achieve the industry’s highest accuracy levels based on average two-qubit gate fidelity.[1] Quantinuum has active engagements with market leaders across pharmaceuticals, material science, financial services, and government and industrial markets. The company has a global workforce of approximately 700 employees, including top scientists and researchers. Over 70% of its technology team holds PhDs or Master’s degrees. Quantinuum’s headquarters is in Broomfield, Colorado, with additional facilities across the United States, United Kingdom, Germany, Japan, Qatar, and Singapore.

For more information, please visit www.quantinuum.com.

Cautionary Statement Concerning Forward-Looking Statements

This press release contains certain statements that may be deemed “forward-looking statements” within the meaning of the Private Securities Litigation Reform Act of 1995. Forward-looking statements include all statements that are not historical facts. The words “anticipate,” “assume,” “believe,” “continue,” “could,” “estimate,” “expect,” “intend,” “may,” “plan,” “potential,” “predict,” “project,” “future,” “will,” “seek,” “foreseeable,” the negative version of these words, or similar terms and phrases are intended to identify forward-looking statements. Such statements are based on certain assumptions and assessments made by our management in light of their experience and their perception of historical trends, current economic and industry conditions, expected future developments and other factors they believe to be appropriate. The forward-looking statements included in this release are also subject to a number of material risks and uncertainties, including but not limited to economic, competitive, governmental, and technological factors affecting our operations, markets, products, services and prices. New factors emerge from time to time, and it is not possible for Quantinuum to predict all such factors. Any forward-looking statement speaks only as of the date on which it is made, and, except as required by law, Quantinuum does not undertake any obligation to update or revise any forward-looking statement, whether as a result of new information, future events or otherwise.

 

[1] As of December 31, 2025.

SOURCE Quantinuum

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