Top 10 LLM Models by Market Share in 2026

Executive Summary

LONDON, February 15, 2026 — The large language model market has undergone a dramatic transformation over the past 18 months. According to Menlo Ventures' 2025 Mid-Year LLM Market Report, enterprise LLM spending has reached $8.4 billion — up from $3.5 billion in November 2024, representing a 2.4x increase in just six months. The market is projected to reach $15 billion by the end of 2026.

The most significant shift has been Anthropic's rise to enterprise dominance. As TechCrunch reported, Anthropic now commands 40% of enterprise LLM spending, up from just 12% in 2023, while OpenAI has fallen from 50% to 27% over the same period. Meanwhile, Google has tripled its enterprise share from 7% to 21%, and Chinese models from Alibaba and DeepSeek have emerged as globally competitive alternatives.

This analysis ranks the 10 most significant LLM models by market share and adoption in 2026, drawing on verified industry data, analyst reports, and executive commentary to map the competitive landscape of the most consequential technology market of the decade.

Key Takeaways

• Anthropic leads enterprise LLM spending at 40%, overtaking OpenAI (27%) and Google (21%), according to Menlo Ventures.
• OpenAI retains overwhelming consumer dominance with approximately 74% market share through ChatGPT, processing over 2.5 billion daily prompts.
• Enterprise LLM spending reached $8.4 billion by mid-2025, with projections of $15 billion by end of 2026.
• Claude Code has achieved $1 billion annualised revenue within six months of launch, capturing 54% of the enterprise coding market.
• Open-source model adoption has declined to 13% of enterprise workloads, down from 19% in early 2025, as enterprises consolidate around closed-source providers.
• Chinese models — particularly Qwen (Alibaba) and DeepSeek-R1 — have achieved global competitiveness, with Qwen holding approximately 12% global usage share.

Top 10 LLM Models by Market Share in 2026

#	Model	Company	Market Position	Key Metric	Primary Use
1	GPT-5 / GPT-4o	OpenAI	74% consumer share, 27% enterprise spend	2.5B+ daily prompts	Consumer, general-purpose
2	Claude Opus 4.1 / Sonnet 4	Anthropic	40% enterprise spend (leader)	$1B ARR (Claude Code alone)	Enterprise, coding, reasoning
3	Gemini 2.5 Pro / Flash	Google	21% enterprise spend, ~40% consumer interaction	Integrated across Google ecosystem	Consumer, enterprise, search
4	Qwen 2.5	Alibaba Cloud	~12% global usage share	Leading Chinese open-source model	Multi-lingual, open-source
5	Llama 4	Meta	~9% enterprise share	Most downloaded open-source LLM	Enterprise, local deployment
6	DeepSeek-R1	DeepSeek	High developer adoption	Top reasoning benchmarks	Coding, reasoning, research
7	Grok 3	xAI	Rapid consumer growth	Real-time X/Twitter integration	Consumer, real-time information
8	Mistral Large 2	Mistral AI	European market leader	Leading EU sovereign AI provider	Enterprise, open-weights
9	Kimi k2	Moonshot AI	Growing Chinese market share	1M+ token context window	Long-context, research
10	Command R+	Cohere	Enterprise RAG leader	Specialised enterprise deployment	RAG, enterprise search

LLM API Pricing Comparison: Cost per Million Tokens in 2026

Model	Provider	Input (per 1M tokens)	Output (per 1M tokens)	Context Window	Pricing Page
GPT-5	OpenAI	$1.25	$10.00	128K	openai.com/api/pricing
GPT-4o	OpenAI	$2.50	$10.00	128K	openai.com/api/pricing
Claude Opus 4.1	Anthropic	$15.00	$75.00	200K	anthropic.com/pricing
Claude Sonnet 4	Anthropic	$3.00	$15.00	200K	anthropic.com/pricing
Gemini 2.5 Pro	Google	$1.25	$10.00	1M	ai.google.dev/pricing
Gemini 2.5 Flash	Google	$0.15	$0.60	1M	ai.google.dev/pricing
Qwen 2.5 72B	Alibaba Cloud	$0.90	$0.90	128K	alibabacloud.com
Llama 4 Maverick	Meta (via providers)	$0.20	$0.60	1M	ai.meta.com/llama
DeepSeek-R1	DeepSeek	$0.55	$2.19	128K	deepseek.com/pricing
Mistral Large 2	Mistral AI	$2.00	$6.00	128K	mistral.ai/pricing

Source: Pricing data compiled from official provider pricing pages as of February 2026. Prices reflect standard API rates; volume discounts, committed-use agreements, and batch processing rates may reduce costs significantly for enterprise customers. Google's Gemini 2.5 Flash represents the most cost-efficient frontier model at $0.15 per million input tokens, while Anthropic's Opus 4.1 commands premium pricing at $15.00 per million input tokens, reflecting its positioning as the highest-capability enterprise model.

1. GPT-5 / GPT-4o (OpenAI) — Consumer Dominance, Enterprise Decline

OpenAI's GPT models remain the most widely used large language models globally, commanding approximately 74% of consumer market share through ChatGPT, which processes over 2.5 billion daily prompts. The launch of GPT-5 in mid-2025 brought significant improvements in reasoning, multimodal capabilities, and instruction following, maintaining OpenAI's position as the default consumer AI platform.

However, OpenAI's enterprise position has eroded significantly. According to Menlo Ventures, OpenAI's share of enterprise LLM spending fell from 50% in 2023 to 27% by mid-2025. The company's projected revenue for 2025 is $12.7 billion, representing 243% year-over-year growth, but the enterprise share loss to Anthropic represents a strategic vulnerability. OpenAI's API pricing for GPT-5 sits at $1.25 per million input tokens and $10 per million output tokens, positioning it as a mid-tier option between Google's aggressive pricing and Anthropic's premium models.

"OpenAI still has the largest user base by far, but the enterprise narrative has shifted decisively toward Anthropic," said Matt Murphy, Partner at Menlo Ventures, in the firm's mid-2025 market analysis. "The question for OpenAI is whether consumer scale can compensate for enterprise margin erosion."

2. Claude Opus 4.1 / Sonnet 4 (Anthropic) — The Enterprise Champion

Anthropic's Claude models have achieved the most dramatic market share gain in the history of enterprise software. From 12% of enterprise LLM spending in 2023, Anthropic has surged to 40% by mid-2025 — making it the undisputed leader in enterprise AI deployment. As TechCrunch reported, enterprises now prefer Anthropic's models over all competitors, including OpenAI.

The catalyst was Claude 3.5 Sonnet, launched in June 2024, which established an 18-month lead atop coding benchmarks that competitors have struggled to close. Claude Code, Anthropic's dedicated coding assistant, reached $1 billion in annualised revenue within just six months of its May 2025 launch, capturing 54% of the enterprise coding market compared to OpenAI's 21%. Anthropic's revenue target for 2026 is $20-26 billion ARR, with the company expecting positive cash flow by 2027.

"Claude has become the model of choice for serious engineering teams," said Dario Amodei, CEO of Anthropic. "Our focus on safety and capability has proven that you don't have to choose between the two."

3. Gemini 2.5 Pro / Flash (Google) — The Ecosystem Play

Google's Gemini models have tripled their enterprise market share from 7% in 2023 to 21% by mid-2025, making Google the third-largest provider by spending. In the consumer market, approximately 40% of users interact with Gemini through Google Search, Android, and Workspace integration, according to Menlo Ventures.

Google's competitive advantage lies in pricing and ecosystem integration. Gemini 2.5 Flash is priced at just $0.26 per million tokens — significantly undercutting both OpenAI and Anthropic — making it the default choice for cost-sensitive, high-volume applications. The model's integration across Gmail, Docs, Sheets, and Google Cloud Platform creates distribution advantages that standalone model providers cannot match.

"Google's strategy is clear: make Gemini the ambient intelligence layer across every Google product," said Sundar Pichai, CEO of Alphabet, at the company's 2025 developer conference. "We're not competing on benchmarks alone — we're competing on ubiquity."

4. Qwen 2.5 (Alibaba Cloud) — China's Global Contender

Alibaba's Qwen has emerged as the most significant Chinese open-source model in the global market, commanding approximately 12% of worldwide LLM usage as of late 2025. Qwen 2.5 is a multi-lingual, multi-modal model that performs competitively with Western frontier models on major benchmarks while being freely available under open-source licences.

Qwen's significance extends beyond raw performance. As geopolitical tensions drive demand for non-US AI alternatives, Qwen has become the default choice for enterprises in Southeast Asia, the Middle East, and parts of Europe seeking to reduce dependency on American AI providers. Alibaba Cloud's global infrastructure provides the deployment support that many open-source models lack, combining the flexibility of open weights with enterprise-grade reliability.

5. Llama 4 (Meta) — The Open-Source Standard

Meta's Llama remains the most downloaded open-source large language model, with approximately 9% of enterprise workloads using Llama-based deployments. However, Llama 4's launch in early 2025 underwhelmed relative to expectations, and open-source model adoption has declined from 19% to 13% of enterprise workloads as organisations consolidate around closed-source providers, according to Menlo Ventures.

Despite the decline in enterprise share, Llama's importance to the ecosystem remains substantial. The model serves as the foundation for thousands of fine-tuned variants deployed in healthcare, finance, legal, and government applications where data sovereignty requirements preclude the use of cloud-based API services. Meta's continued investment in the Llama family ensures the open-source ecosystem has a competitive frontier model, even as the commercial market consolidates.

6. DeepSeek-R1 (DeepSeek) — Efficient Reasoning at Scale

DeepSeek-R1 has established itself as one of the most important reasoning models in the global market, achieving benchmark scores competitive with OpenAI's o-series models at a fraction of the computational cost. The model's efficiency — delivering frontier-level reasoning performance with significantly lower inference costs — has driven high adoption among developers, researchers, and Chinese technology platforms.

DeepSeek's approach to "thinking" models — where the AI explicitly works through reasoning chains before producing answers — has influenced the entire industry's direction. The model's open-weights release allows researchers and enterprises to study and build upon its reasoning architecture, contributing to the broader understanding of how large language models can be made more reliable for complex analytical tasks.

7. Grok 3 (xAI) — Real-Time Intelligence

Elon Musk's xAI has positioned Grok as the fastest-growing consumer AI model, differentiated by its real-time integration with the X (formerly Twitter) platform. Grok 3, released in late 2025, offers real-time access to news, social media discourse, and trending topics — capabilities that traditional LLMs, trained on static datasets, cannot match without additional tooling.

Grok's consumer growth has been accelerated by its integration into X's 500+ million user base, providing distribution at a scale that only Google can rival. While Grok's enterprise adoption remains limited, its consumer momentum and xAI's reported $6 billion funding round position it as a significant competitive force in the consumer AI market through 2026 and beyond.

8. Mistral Large 2 (Mistral AI) — Europe's Sovereign AI

Mistral AI, headquartered in Paris, has established itself as Europe's leading AI model provider and a champion of the "sovereign AI" movement — the principle that nations and regions should have access to frontier AI models that are not controlled by US or Chinese technology companies. Mistral Large 2 competes directly with GPT-4 class models while being available under open-weights licences for on-premise deployment.

Mistral's strategic significance extends beyond pure performance. The company has secured partnerships with major European enterprises and government agencies seeking AI capabilities that comply with EU data sovereignty regulations and the AI Act. With over $1 billion in total funding, including investment from Microsoft and Andreessen Horowitz, Mistral is positioned as the default AI provider for organisations that require European-hosted, European-governed AI infrastructure.

9. Kimi k2 (Moonshot AI) — The Long-Context Specialist

Moonshot AI's Kimi has carved a distinctive position in the Chinese AI market through its industry-leading long-context capabilities, supporting context windows exceeding 1 million tokens. This capability makes Kimi particularly valuable for research, legal analysis, and enterprise applications that require processing entire documents, codebases, or datasets within a single prompt.

Kimi's user base has grown rapidly in China, where it competes directly with Baidu's ERNIE and Alibaba's Qwen for consumer attention. The model's long-context specialisation addresses a genuine market need that frontier Western models are only beginning to match, giving Moonshot AI a defensible position in the world's second-largest AI market.

10. Command R+ (Cohere) — Enterprise RAG Specialist

Cohere's Command R+ has established a strong niche in enterprise retrieval-augmented generation (RAG) — the architecture that allows LLMs to access and reason over private enterprise data. While Cohere's overall market share is smaller than the consumer-facing giants, its specialised focus on enterprise search, document analysis, and knowledge management has created a loyal customer base among Fortune 500 companies.

Command R+ is optimised for accuracy and groundedness — the ability to generate responses that are faithfully anchored to source documents rather than hallucinated. This capability is critical for enterprise applications in healthcare, legal, and financial services where factual accuracy is non-negotiable. Cohere's deployment options include fully private cloud instances, making it attractive to regulated industries that cannot send data to third-party APIs.

Market Dynamics: The Great Enterprise Shift

The most significant trend defining the 2026 LLM landscape is the consolidation of enterprise spending around closed-source models. According to Menlo Ventures, 87% of enterprise LLM workloads now run on proprietary models, up from 81% in early 2025. The decline of open-source adoption — from 19% to 13% of enterprise workloads — reflects a market maturation where enterprises prioritise reliability, support, and liability protections over the cost savings of self-hosted models.

The coding market has emerged as the first "killer app" for enterprise LLMs, reaching $2.3 billion in spending in 2025. Anthropic's Claude Code dominates with 54% share, followed by GitHub Copilot (integrated with OpenAI's models) with 20 million users across 90% of Fortune 100 companies, and Cursor which reached $1 billion ARR in November 2025, just 17 months after launch.

"We are witnessing the fastest enterprise software market creation in history," noted Jason Lemkin, founder of SaaStr. "The AI LLM market share story of 2023-2025 is one of just massive change, fast. Anthropic went from distant third to number one in enterprise in just two years."

Forward Outlook: What to Watch in 2026-2027

Several dynamics will shape the LLM market through the remainder of 2026 and into 2027. First, the enterprise market is likely to continue consolidating around Anthropic, OpenAI, and Google, with smaller providers competing on specialisation rather than general capability. Second, the emergence of "reasoning" models — exemplified by DeepSeek-R1 and OpenAI's o-series — is creating a new category of LLM usage focused on complex analytical tasks, scientific research, and code generation.

Third, the geopolitical dimension of LLM competition is intensifying. Chinese models from Alibaba, DeepSeek, and Moonshot AI have achieved global competitiveness, creating a multipolar AI landscape that mirrors broader geopolitical alignments. European sovereignty concerns are driving adoption of Mistral and similar providers, while enterprises in Asia and the Middle East are increasingly evaluating non-US alternatives.

The total addressable market for LLM services is projected to exceed $30 billion by 2027, according to Bloomberg Intelligence. Whether this market produces a dominant winner or remains fragmented across use cases, geographies, and enterprise requirements will define the next chapter of the most significant technology competition since the cloud computing wars of the 2010s.

Bibliography

1. Menlo Ventures — 2025 Mid-Year LLM Market Update: Foundation Model Landscape + Economics
2. Menlo Ventures — 2025: The State of Generative AI in the Enterprise
3. TechCrunch — Enterprises Prefer Anthropic's AI Models Over Anyone Else's, Including OpenAI's
4. Yahoo Finance — Enterprise LLM Spend Reaches $8.4B as Anthropic Overtakes OpenAI
5. Crunchbase — LLM and AI Market Funding Trends 2025
6. Deep Research Global — Anthropic Company Analysis and Outlook Report (2026)
7. AI CERTs — Evolving LLM Market: Anthropic Leads 2025 Enterprise Share
8. PowerDrill — LLM Market Landscape 2025: Global Leaders, Revenue Models, and AI Trends
9. Fortune Business Insights — AI Market Size Projections
10. Bloomberg Intelligence — AI and LLM Market Forecasts