Top 10 OpenAI Alternatives to Try in 2025

The landscape of artificial intelligence is changing day by day. Over the past few years, OpenAI has been at the forefront of making conversational AI go mainstream through platforms like ChatGPT. In this blog, you will get to learn about the top 10 OpenAI alternatives to try in 2025.

Many companies have emerged with strong alternatives, each with its benefits and strengths. Whether you’re looking for better integration with your existing tech stack, improved affordability, or a model that prioritizes safe and ethical responses, there are plenty of options to consider.

Why OpenAI Alternatives?

In comparing these, we look at several important factors:

• Performance: Accuracy, speed, reasoning ability, and capacity to manage complex tasks.
• Affordability: Pricing model, flexibility, and overall cost-effectiveness.
• Scalability: How scalable is the system for growing your business?
• Accessibility: Developer and non-developer ease of use, documentation, and support.
• Integration: Ease of integrating these solutions into current systems.
• Customization: Fine-tuning options, custom training, and extra features.
• Community and Support: Live user communities, developer resources, and regular updates.

Top 10 OpenAI Alternatives in 2025

Here is the list of the top 10 OpenAI alternatives that you might consider exploring in 2025.

1. Google Gemini

Google Gemini is also one of the top contenders to OpenAI models. As a multimodal large language model, Gemini not only deals with text but is also capable of dealing with other inputs such as images and voice. 

Its architecture provides long context windows—a functionality that enables the model to recall and process information over extended conversations. Gemini is thoroughly integrated into the Google ecosystem, so it interacts perfectly with services such as Gmail, Docs, and Google Search.

Key Features and Use Cases

• Multimodal Capabilities: Gemini supports both text and visual content as input and output.
• Extended Context: Due to its large token window, it is well-suited for longer conversational tasks or intricate data analysis.
• Integration: Particularly handy for companies that already utilize Google’s suite of applications and would like to optimize productivity or interaction with customers.

Pricing

• Google Gemini Advanced access comes through Google One AI Premium at USD 19.99 per month with 2 TB of storage.
• Another price is around USD 20 per month.
• Students get it free until June 30, 2026.

Pros

• Strong multimodal capabilities
• Seamless integration with popular Google services
• Ongoing enhancements fueled by the immense research power of Google

Cons

• Pricing details may be better suited for enterprise clients
• Advanced features might come with a learning curve for smaller teams

Here’s how you can easily generate prompts using Google Gemini.

2. Anthropic’s Claude

Anthropic, which OpenAI defectors started, has created Claude, a language model with a strong focus on safety and ethical standards. The model uses what Anthropic refers to as Constitutional AI, which is the system adhering to a predetermined set of rules that guarantee the outputs are beneficial, inoffensive, and truthful.

Key Features and Use Cases

• Safety and Alignment: Created to reduce dangerous or biased responses, making it especially appealing to industries where trust is paramount.
• Human-like Conversation: Praised frequently for its capacity to preserve context in lengthy conversations, Claude is excellent for customer support and creative writing use.
• Pricing Flexibility: With a free and pro plan starting at approximately $20 per month, it’s affordable for individuals and small businesses.

Pricing

• Anthropic’s Claude Pro plan includes USD 20 per month (US) or USD 17 per month billed yearly.
• Claude Max plan starts at USD 100 per month with the restriction to use it only five times, up to USD 200 per month, which you can use twenty times.

Pros

• Strong emphasis on moral AI and safety protocols
• Multi-purpose for both everyday chat and difficult problem-solving
• Transparent strategy for AI alignment

Cons

• Could fall short of some plug-in capabilities of the larger models
• Some advanced features may need further configuration

Simplify your coding journey with Claude.

3. Mistral AI

Mistral AI is one of the new stars in the field of AI startups, renowned for its cost-efficient and performance-oriented text generation models. In spite of having relatively smaller model sizes, Mistral AI offers competitive performance.

The flexible nature of content creation by the company makes it a great choice for applications such as article writing, content summarization, and even customer support automation.

Key Features and Use Cases

• Cost Effectiveness: Mistral AI models are built to be resource-friendly and hence, a cost-effective choice for organizations with limited budgets.
• Speed and Reactivity: Its models are built for rapid output, which is useful in real-time use cases.
• Multi-Language Support: With support for various languages, these models can be used for global audiences and local markets.

Pricing

• Mistral AI’s Le Chat Pro plan includes USD 14.99 per month (or €14.99 in Europe), unlocking advanced models, unlimited messaging, web browsing, file uploads, and enhanced capabilities.

Pros

• Highly efficient and economical
• Quick response times are ideal for real-time use
• Supports many languages

Cons

• Lacks possibly as many sophisticated fine-tuning options as larger, enterprise-level models
• Being a newer organization, community support may still be developing

Generate prompts with the help of Mistral AI.

4. Perplexity AI

Perplexity AI is a kind of chatbot that serves as an alternative to both OpenAI and search engines. It is designed to offer detailed, well-referenced answers by linking users with quality information. It is, therefore, specifically tailored for research, academic work, and in-depth learning assignments.

Key Features and Use Cases

• Integrated Search Functionality: In addition to responding, it fetches information from trusted sources, providing users with confidence in the response.
• User-Friendly Interface: Easy to use, Perplexity AI is perfect for students, researchers, and working professionals requiring authentic information.
• Citations and Transparency: Provides assurance that responses are supported by quoted sources, mitigating the danger of misinformation.

Pricing

• Perplexity AI’s Professional plan costs around USD 20 per month for each user, and offers unlimited Pro searches, advanced model selection, such as GPT-4, Claude 3), file uploads, and priority response speeds.

Pros

• Great for deep research and academic questions
• Offers clear references and citations
• Blends the strengths of search engines and chat AI

Cons

• Not necessarily as well-suited for more creative or less formal conversational work
• Free vs. premium features can be a tipping point for heavy use

Get various options for your specific prompt with Perplexity AI:

5. Cohere Command R+

Cohere’s Command R+ is built to serve enterprise requirements. It simplifies sophisticated production processes and excels specifically in those areas where complex language understanding is needed. Cohere focuses on delivering solutions to businesses that must incorporate strong AI capabilities into their activities.

Key Features and Use Cases

• Tuned for Retrieval-Augmented Generation (RAG): Command R+ performs best for operations that need the use of external data to create intricate answers.
• Multilingual Support: It accommodates more than one language to allow international businesses to utilize the model across global regions.
• Scalability: Designed for enterprise environments, it is able to process a large amount of data and multiple interactions at the same time, hence appropriate for business-critical uses.

Pricing

• Cohere Command R+ is priced at $2.50 per 1 M input tokens and $10.00 per 1 M output tokens.

Pros

• Best suited for production-grade business applications
• Very scalable and customizable to suit individual business requirements
• Robust integration capabilities for cloud-based processes

Cons

• Could be overqualified for smaller projects or personal use
• Pricing is often enterprise-oriented, which may not be best for startups or small teams

Generate easily the prompts in any language using Cohere’s Command R+ like this:

6. IBM Watson

IBM Watson has been an established force in the realm of enterprise AI. With a wealth of experience across industries, Watson provides a robust set of AI services suited to large enterprises. Its interest lies in providing scalable and reliable enterprise solutions that play nicely with existing IT environments.

Key Features and Use Cases

• Enterprise-Level Reliability: IBM Watson is highly known for being stable and able to perform large-scale operations, which is why it is one of the preferred choices among Fortune 500 enterprises.
• Broad Integration Options: Watson can seamlessly integrate with IBM’s wider range of software tools and services, which is beneficial to companies already running IBM products.
• Data Processing Abilities: From understanding natural language to data analysis, Watson offers comprehensive analytical tools suitable for sophisticated business environments.

Pricing

• IBM Watsonx Assistant Plus plan starts at USD 140 per month and includes up to 1,000 monthly active users.
• Additional users are charged USD 14 per 100 MAUs.
• Custom Enterprise pricing is also available.

Pros

• Very reliable and tested in corporate environments
• Top-notch integration with other IBM solutions and legacy infrastructure
• Large availability of support, documentation, and professional services

Cons

• The platform may be costly and could be less flexible than some newer alternatives
• Customization could be restricted to enterprise workflows and thus less suitable for smaller projects

You can even build Generative AI solutions out of IBM WatsonX like this:

7. Microsoft Copilot

Microsoft Copilot is intended to boost productivity by embedding itself in day-to-day business applications such as Microsoft Office. Intimately integrated with the Microsoft 365 platform, Copilot is a virtual assistant that assists with everything from writing emails to creating reports, making it a compelling choice for organizations that depend on Office products.

Key Features and Use Cases

• Productivity Integration: Seamless integration with tools like Word, Excel, and Outlook makes Microsoft Copilot a contributor to simplifying day-to-day tasks and enhancing workplace productivity.
• Conversational Support: It is capable of parsing detailed prompts and coming up with useful, context-based answers that facilitate enriched decision-making.
• Enterprise Support: With support from Microsoft’s vast cloud infrastructure, Copilot includes strong data handling and security tools ideal for large companies.

Pricing

• Microsoft 365 Copilot is starting at $30 for each user per month, which is billed yearly.
• $31.50 if paid monthly, as an add‑on to a qualifying Microsoft 365 subscription.

Pros

• Ideal for companies already embedded in the Microsoft environment
• Boosts productivity with familiar Office applications
• Backed by Microsoft’s deep cloud and security infrastructure

Cons

• Its abilities are tuned to Microsoft products and may be less adaptable outside of this environment
• Some will see it as less customizable than stand-alone AI solutions

Here’s how you can easily generate prompts in Microsoft Copilot.

8. Meta’s Llama 4

Meta’s Llama 4 offers an open-weight model that is a solid option for customers looking for powerful AI capabilities at a lower price. Llama 4 is intended to deliver high performance even on small scales and is integrated across Meta’s products, making it available to customers all around the world.

Key Features and Use Cases

• Open-Source Flexibility: Llama 4 is offered on open-source terms that permit wide-ranging customization and community contribution.
• Cost-Effective: Optimizing the model for performance with comparatively lower computational demands, Llama 4 provides a cost-effective solution for developers and businesses alike.
• Wide Community Support: Its open-source nature ensures a wide community of developers contributes to updates, bug fixes, and innovative applications.

Pricing

• Llama 4 Scout at $0.11 per 1M input tokens, $0.34 per 1M output.
• Llama 4 Maverick at $0.19–$0.49 per 1M tokens.

Pros

• Greater customization due to its open-source philosophy
• Lower overhead costs relative to proprietary models
• Active community and regular updates

Cons

• It can be more technically demanding to install and get working optimally
• Documentation and support may not be as structured relative to business solutions

Here is an illustration for prompt generation in Meta Llama.

9. xAI’s Grok

xAI’s Grok, developed by Elon Musk’s xAI, offers a unique alternative with a personality and tone that stands out from more conventional AI systems. Grok is designed not only to provide responses to queries but also to engage with users in a distinctive, often irreverent manner. It draws on data from the X platform (formerly Twitter) and focuses on creative and witty responses.

Key Features and Use Cases

• Distinct Tone and Personality: Grok has been characterized by its “rebellious” and edgy personality traits that users seeking a non-traditional conversational AI experience are attracted to.
• Advanced Reasoning Mode: With the likes of “Think” and “Big Brain” modes, Grok can solve sophisticated issues and deliver detailed explanations if required.
• Platform Integration: As integrated into X, it provides a new means of interacting with social media data, potentially useful for marketing and community interaction.

Pricing

• Grok is accessed via X Premium, starting at $7 per month paid annually or $8 per month.
• Premium+ is starting at $40 per month for full Grok‑3 access.

Pros

• Provides a unique personality and imaginative interaction style
• Has sophisticated reasoning abilities for answering tough questions
• Integrated natively with a well-known social platform

Cons

• Its voice might not be ideal for every business setting
• It will sometimes bring controversies regarding its political position or content filtering
• Initial iterations have been criticized for false information or changes

Here is an example showing how a prompt is generated in Grok AI.

10. DeepSeek

DeepSeek is a Chinese AI company that has made a splash in the industry within a short period by selling open-source models at a tenth of the price of its peers.

With performance-matching models to those of OpenAI and others, DeepSeek’s model is based on cost efficiency and frugal training methods. Its recent success in the app store has proved that quality AI is possible without draining huge budgets.

Read our blog to understand the ultimate comparison of DeepSeek vs ChatGPT.

Key Features and Use Cases

• Cost Efficiency: DeepSeek models are renowned for lower costs of training and lesser dependence on costly hardware, thus making them desirable for startups and research establishments.
• Open-Source Method: By opening its algorithms and training information freely, DeepSeek supports collaborative efforts of the community and speedy innovation.
• Competitive Reasoning Capability: In spite of reduced expenses, its R1 model and the rest of its range have established reasoning ability rivaling that of costlier products.
• Market Impact: DeepSeek’s results have even begun to impact stock markets and pose questions regarding the necessity of significant capital investments in AI research, making it a fascinating choice for investors and technology fans alike.

Pricing

DeepSeek AI offers a token-based pricing model for its API services, with rates varying by model and usage conditions:

• DeepSeek-Chat:
  • Input (Cache Hit): $0.07 per million tokens
  • Input (Cache Miss): $0.27 per million tokens
  • Output: $1.10 per million tokens
• DeepSeek-Reasoner:
  • Input (Cache Hit): $0.14 per million tokens
  • Input (Cache Miss): $0.55 per million tokens
  • Output: $2.19 per million tokens

Additionally, DeepSeek Coder models are priced as follows:

• 6.7B model:
  • Input: $0.20 per million tokens
  • Output: $0.40 per million tokens
• 33B model:
  • Input: $1.00 per million tokens
  • Output: $2.00 per million tokens

Pros

• Exceptional performance at significantly lower cost
• The open, transparent, open-source model that fosters cooperation
• Competitive thinking capabilities with reduced hardware demands

Cons

• As a newer vendor, support and documentation might not yet be as comprehensive as larger vendors
• Some content and regulatory limitations exist based on local regulations
• Its open method may demand more technical proficiency from users

Here is an illustration of a prompt in DeepSeek.

Conclusion

The AI landscape of 2025 is more diverse and competitive than ever before from the easy integration of Google Gemini with commonly used services such as Google Drive, Doc, etc. to Anthropic’s emphasis on safe and ethical AI, from the budget-friendly performance of Mistral AI and DeepSeek to the enterprise-ready feature sets of Cohere Command R+ and IBM Watson, every company, as well as developers, has plenty of choices at their disposal to develop their next-generation AI offerings. 

Microsoft Copilot and Meta’s Llama 4 offer strong alternatives for those already embedded within their ecosystems, and xAI’s Grok adds an entirely new, personality-driven twist to conversational AI.

Each alternative has its own strengths and weaknesses. The best choice will depend on your particular use case, budget, and technical needs. As the technology of AI continues to grow, these alternatives can only continue to get better, providing users with technology that suits their needs today as well as tomorrow.

Frequently Asked Questions (FAQs)