What are the main differences between CustomGPT and OpenAI?

CustomGPT excels in Industry-leading accuracy with 97% benchmark score and Patented technology to reduce hallucinations, scoring 94/100 in user ratings with 97% accuracy. OpenAI leads in Industry-leading model performance and Comprehensive API features with 90/100 overall rating and 95% accuracy. Key technical difference: CustomGPT focuses on No-code chatbot builder while OpenAI emphasizes GPT-4 and GPT-3.5 models. Pricing differs by $99/month.

Which is better for enterprises: CustomGPT or OpenAI?

CustomGPT offers SOC 2 compliance for enterprise security. HIPAA compliance varies - contact vendors for details. For scalability, both offer cloud-based deployment options. CustomGPT leads with 94/100 enterprise readiness score (96/100 enterprise features).

How much does CustomGPT cost vs OpenAI?

CustomGPT starts at $99/monthly (freemium model), while OpenAI begins at contact sales/usage-based (pay-as-you-go model). OpenAI provides a free tier, and free trials are available. This represents a significant price difference of $99/month. See our detailed pricing breakdown for complete tier comparisons.

Can I migrate from OpenAI to CustomGPT?

Migration from OpenAI to CustomGPT typically requires API-based data export/import, which CustomGPT provides. CustomGPT provides comprehensive API access excellent documentation for the migration process. Estimated migration time: 1-2 days for cloud setup. Contact CustomGPT support for migration assistance and best practices.

What integrations do CustomGPT and OpenAI support?

CustomGPT integrates with Direct sitemap (Auto-sync), Wordpress(Auto-sync), Wix(Auto-sync), YouTube (Auto-sync), Hubspot Knowledge Base (Auto-sync) (13 integrations total). OpenAI supports REST API, Python SDK, Node.js SDK, Community libraries, Azure OpenAI Service (8 integrations available). Both offer REST APIs for custom integrations. CustomGPT offers 63% more integrations, with webhook support for real-time data sync.

What are the main differences between CustomGPT and OpenAI?

CustomGPT offers strong capabilities, scoring 0/100 in user ratings. OpenAI provides unique strengths with 0/100 overall rating. Key technical difference: CustomGPT focuses on advanced features while OpenAI emphasizes specialized capabilities.

Which is better for enterprises: CustomGPT or OpenAI?

Both platforms provide enterprise-grade security. HIPAA compliance varies - contact vendors for details. For scalability, both offer cloud-based deployment options. OpenAI leads with strong/100 enterprise readiness score.

How much does CustomGPT cost vs OpenAI?

CustomGPT starts at custom pricing/month (subscription model), while OpenAI begins at contact sales/month (subscription model). Both require paid plans. Pricing is relatively comparable. See our detailed pricing breakdown for complete tier comparisons.

Can I migrate from CustomGPT to OpenAI?

Migration from CustomGPT to OpenAI typically requires manual data transfer since API access may be limited. OpenAI offers standard documentation for the migration process. Estimated migration time: 1-2 days for cloud setup. Contact OpenAI support for migration assistance and best practices.

What integrations do CustomGPT and OpenAI support?

CustomGPT integrates with (multiple platforms). OpenAI supports (various tools). API availability varies by plan. Integration coverage is comparable.

CustomGPT vs OpenAI

Make an informed decision with our comprehensive comparison. Discover which RAG solution perfectly fits your needs.

More about OpenAI More about CustomGPT Get Started Today

Priyansh KhodiyarDevRel at CustomGPT.ai

Fact checked and reviewed by Bill Cava

Published: 01.04.2025Updated: 25.04.2025

In this comprehensive guide, we compare CustomGPT and OpenAI across various parameters including features, pricing, performance, and customer support to help you make the best decision for your business needs.

Overview

When choosing between CustomGPT and OpenAI, understanding their unique strengths and architectural differences is crucial for making an informed decision. Both platforms serve the RAG (Retrieval-Augmented Generation) space but cater to different use cases and organizational needs.

Quick Decision Guide

Choose CustomGPT if: you value industry-leading accuracy with 97% benchmark score
Choose OpenAI if: you value industry-leading model performance

About CustomGPT

CustomGPT is most accurate rag-as-a-service api for business. CustomGPT is the #1 benchmarked RAG platform that enables businesses to create powerful AI assistants trained on their specific data, offering industry-leading accuracy with reduced hallucinations and seamless integration capabilities. Founded in 2021, headquartered in Needham, Massachusetts, United States, the platform has established itself as a reliable solution in the RAG space.

Overall Rating

94/100

Starting Price

$99/mo

About OpenAI

OpenAI is leading ai research company and api provider. OpenAI provides state-of-the-art language models and AI capabilities through APIs, including GPT-4, assistants with retrieval capabilities, and various AI tools for developers and enterprises. Founded in 2015, headquartered in San Francisco, CA, the platform has established itself as a reliable solution in the RAG space.

Overall Rating

90/100

Starting Price

Custom

Key Differences at a Glance

In terms of user ratings, both platforms score similarly in overall satisfaction. From a cost perspective, OpenAI offers more competitive entry pricing. The platforms also differ in their primary focus: AI Chatbot versus AI Platform. These differences make each platform better suited for specific use cases and organizational requirements.

⚠️ What This Comparison Covers

We'll analyze features, pricing, performance benchmarks, security compliance, integration capabilities, and real-world use cases to help you determine which platform best fits your organization's needs. All data is independently verified from official documentation and third-party review platforms.

Detailed Feature Comparison

Features	CustomGPT	OpenAI
Data Ingestion & Knowledge Sources	1,400+ file formats – PDF, DOCX, Excel, PowerPoint, Markdown, HTML + auto-extraction from ZIP/RAR/7Z archives Website crawling – Sitemap indexing with configurable depth for help docs, FAQs, and public content Multimedia transcription – AI Vision, OCR, YouTube/Vimeo/podcast speech-to-text built-in Cloud integrations – Google Drive, SharePoint, OneDrive, Dropbox, Notion with auto-sync Knowledge platforms – Zendesk, Freshdesk, HubSpot, Confluence, Shopify connectors Massive scale – 60M words (Standard) / 300M words (Premium) per bot with no performance degradation	✅ Embeddings API – text-embedding models generate vectors for semantic search workflows ⚠️ DIY Pipeline – No ready-made ingestion; build chunking, indexing, refreshing yourself Azure File Search – Beta preview tool accepts uploads for semantic search Manual Architecture – Embed docs → vector DB → retrieve chunks at query time
Integrations & Channels	Website embedding – Lightweight JS widget or iframe with customizable positioning CMS plugins – WordPress, WIX, Webflow, Framer, SquareSpace native support 5,000+ app ecosystem – Zapier connects CRMs, marketing, e-commerce tools MCP Server – Integrate with Claude Desktop, Cursor, ChatGPT, Windsurf OpenAI SDK compatible – Drop-in replacement for OpenAI API endpoints LiveChat + Slack – Native chat widgets with human handoff capabilities	⚠️ No First-Party Channels – Build Slack bots, widgets, integrations yourself or use third-party ✅ API Flexibility – Run GPT anywhere; channel-agnostic engine for custom implementations Community Tools – Zapier, community Slack bots exist but aren't official OpenAI Manual Wiring – Everything is code-based; no out-of-the-box UI or connectors
Core Chatbot Features	✅ #1 accuracy – Median 5/5 in independent benchmarks, 10% lower hallucination than OpenAI ✅ Source citations – Every response includes clickable links to original documents ✅ 93% resolution rate – Handles queries autonomously, reducing human workload ✅ 92 languages – Native multilingual support without per-language config ✅ Lead capture – Built-in email collection, custom forms, real-time notifications ✅ Human handoff – Escalation with full conversation context preserved	✅ Multi-Turn Chat – GPT-4/3.5 handle conversations; you resend history for context ⚠️ No Agent Memory – OpenAI doesn't store conversational state; you manage it Function Calling – Model triggers your functions (search endpoints); you wire retrieval ChatGPT Web UI – Separate from API; not brand-customizable for private data
Customization & Branding	Full white-labeling included – Colors, logos, CSS, custom domains at no extra cost 2-minute setup – No-code wizard with drag-and-drop interface Persona customization – Control AI personality, tone, response style via pre-prompts Visual theme editor – Real-time preview of branding changes Domain allowlisting – Restrict embedding to approved sites only	⚠️ No Turnkey UI – Build branded front-end yourself; no theming layer provided System Messages – Set tone/style via prompts; white-label chat requires development ChatGPT Custom Instructions – Apply only inside ChatGPT app, not embedded widgets Developer Project – All branding, UI customization is your responsibility
L L M Model Options	GPT-5.1 models – Latest thinking models (Optimal & Smart variants) GPT-4 series – GPT-4, GPT-4 Turbo, GPT-4o available Claude 4.5 – Anthropic's Opus available for Enterprise Auto model routing – Balances cost/performance automatically Zero API key management – All models managed behind the scenes	✅ GPT-4 Family – GPT-4 (8k/32k), GPT-4 Turbo (128k), GPT-4o top-tier performance ✅ GPT-3.5 Family – GPT-3.5 Turbo (4k/16k) cost-effective for high-volume use ⚠️ OpenAI-Only – Cannot swap to Claude, Gemini; locked to OpenAI ecosystem Manual Routing – Developer chooses model per request; no automatic selection ✅ Frequent Upgrades – Regular releases with larger context windows and better benchmarks
Developer Experience ( A P I & S D Ks)	REST API – Full-featured for agents, projects, data ingestion, chat queries Python SDK – Open-source `customgpt-client` with full API coverage Postman collections – Pre-built requests for rapid prototyping Webhooks – Real-time event notifications for conversations and leads OpenAI compatible – Use existing OpenAI SDK code with minimal changes	✅ Excellent Docs – Official Python/Node.js SDKs; comprehensive API reference and guides Function Calling – Simplifies prompting; you build RAG pipeline (indexing, retrieval, assembly) Framework Support – Works with LangChain/LlamaIndex (third-party tools, not OpenAI products) ⚠️ No Reference Architecture – Vast community examples but no official RAG blueprint
Performance & Accuracy	Sub-second responses – Optimized RAG with vector search and multi-layer caching Benchmark-proven – 13% higher accuracy, 34% faster than OpenAI Assistants API Anti-hallucination tech – Responses grounded only in your provided content OpenGraph citations – Rich visual cards with titles, descriptions, images 99.9% uptime – Auto-scaling infrastructure handles traffic spikes	✅ GPT-4 Top-Tier – Leading performance for language tasks; requires RAG for domain accuracy ⚠️ Hallucination Risk – Can hallucinate on private/recent data without retrieval implementation Well-Built RAG Delivers – High accuracy achievable with proper indexing, chunking, prompt design Latency Considerations – Larger models (128k context) add latency; scales well under load
Security & Compliance	SOC 2 Type II + GDPR – Regular third-party audits, full EU compliance 256-bit AES encryption – Data at rest; SSL/TLS in transit SSO + 2FA + RBAC – Enterprise access controls with role-based permissions Data isolation – Never trains on customer data Domain allowlisting – Restrict chatbot to approved domains	✅ API Data Privacy – Not used for training; 30-day retention for abuse checks only ✅ ChatGPT Enterprise – SOC 2 Type II, SSO, stronger privacy, enterprise-grade security ✅ Encryption – TLS in transit, at rest encryption with enterprise standards ✅ GDPR/HIPAA – DPA for GDPR; BAA for HIPAA; regional data residency available ✅ Zero-Retention Option – Enterprise/API customers can opt for no data retention ⚠️ Developer Responsibility – User auth, input validation, logging entirely on you
Pricing & Plans	Standard: $99/mo – 10 chatbots, 60M words, 5K items/bot Premium: $449/mo – 100 chatbots, 300M words, 20K items/bot Enterprise: Custom – SSO, dedicated support, custom SLAs 7-day free trial – Full Standard access, no charges Flat-rate pricing – No per-query charges, no hidden costs	✅ Pay-As-You-Go – $0.0015/1K tokens GPT-3.5; ~$0.03-0.06/1K GPT-4 token pricing ✅ No Platform Fees – Pure consumption pricing; no subscriptions, monthly minimums Rate Limits by Tier – Usage tiers auto-increase limits as spending grows ⚠️ Cost at Scale – Bills spike without optimization; high-volume needs token management External Costs – RAG incurs vector DB (Pinecone, Weaviate) and hosting costs ✅ Best Value For – Low-volume use or teams with existing infrastructure
Support & Ecosystem	Comprehensive docs – Tutorials, cookbooks, API references Email + in-app support – Under 24hr response time Premium support – Dedicated account managers for Premium/Enterprise Open-source SDK – Python SDK, Postman, GitHub examples 5,000+ Zapier apps – CRMs, e-commerce, marketing integrations	✅ Massive Community – Thorough docs, code samples; direct support requires Enterprise Third-Party Frameworks – Slack bots, LangChain, LlamaIndex building blocks abound Broad AI Focus – Text, speech, images; RAG is one of many use cases Enterprise Premium Support – Success managers, SLAs, compliance environment for Enterprise customers
Observability & Monitoring	Real-time dashboard – Query volumes, token usage, response times Customer Intelligence – User behavior patterns, popular queries, knowledge gaps Conversation analytics – Full transcripts, resolution rates, common questions Export capabilities – API export to BI tools and data warehouses	⚠️ Basic Dashboard – Tracks monthly token spend, rate limits; no conversation analytics DIY Logging – Log Q&A traffic yourself; no specialized RAG metrics Status Page – Uptime monitoring, error codes, rate-limit headers available Community Solutions – Datadog/Splunk setups shared; you build monitoring pipeline
Use Cases	Customer support – 24/7 AI handling common queries with citations Internal knowledge – HR policies, onboarding, technical docs Sales enablement – Product info, lead qualification, education Documentation – Help centers, FAQs with auto-crawling E-commerce – Product recommendations, order assistance	✅ Custom AI Applications – Bespoke solutions requiring maximum flexibility beyond pre-packaged platforms ✅ Code Generation – GitHub Copilot-style tools, IDE integrations, automated review ✅ Creative Writing – Content generation, marketing copy, storytelling at scale ✅ Data Analysis – Natural language queries over structured data, report generation Customer Service – Custom chatbots integrated with business systems and knowledge bases ⚠️ NOT IDEAL FOR – Non-technical teams wanting turnkey RAG chatbot without coding
Limitations & Considerations	Managed service – Less control over RAG pipeline vs build-your-own Model selection – OpenAI + Anthropic only; no Cohere, AI21, open-source Real-time data – Requires re-indexing; not ideal for live inventory/prices Enterprise features – Custom SSO only on Enterprise plan	⚠️ NO Built-In RAG – Entire retrieval infrastructure must be built by developers ⚠️ Developer-Only – Requires coding expertise; no no-code interface for non-technical teams ⚠️ Rate Limits – Usage tiers start restrictive (Tier 1: 500 RPM GPT-4) ⚠️ Model Lock-In – Cannot use Claude, Gemini; tied to OpenAI ecosystem ⚠️ NO Chat UI – ChatGPT web interface not embeddable or customizable for business ⚠️ Cost at Scale – Token pricing can spike without optimization; needs cost management
Core Agent Features	Custom AI Agents – Autonomous GPT-4/Claude agents for business tasks Multi-Agent Systems – Specialized agents for support, sales, knowledge Memory & Context – Persistent conversation history across sessions Tool Integration – Webhooks + 5,000 Zapier apps for automation Continuous Learning – Auto re-indexing without manual retraining	✅ Assistants API (v2) – Built-in conversation history, persistent threads, tool access management ✅ Function Calling – Models invoke external functions/tools; describe structure, receive calls with arguments ✅ Parallel Tool Execution – Access Code Interpreter, File Search, custom functions simultaneously Responses API (2024) – New primitive with web search, file search, computer use ✅ Structured Outputs – strict: true guarantees arguments match JSON Schema for reliable parsing ⚠️ Agent Limitations – Less control vs LangChain for complex workflows; simpler assistant paradigm
R A G Capabilities	GPT-4 + RAG – Outperforms OpenAI in independent benchmarks Anti-hallucination – Responses grounded in your content only Automatic citations – Clickable source links in every response Sub-second latency – Optimized vector search and caching Scale to 300M words – No performance degradation at scale	⚠️ NO Built-In RAG – LLM models only; build entire RAG pipeline yourself ✅ Embeddings API – text-embedding-ada-002 and newer for vector embeddings/semantic search DIY Architecture – Embed docs → external vector DB → retrieve → inject into prompt Azure Assistants Preview – Beta File Search tool; minimal, preview-stage only Framework Integration – Works with LangChain/LlamaIndex (third-party, not OpenAI products) ⚠️ Developer Responsibility – Chunking, indexing, retrieval optimization all require custom code
Competitive Positioning	Market position – Leading RAG platform balancing enterprise accuracy with no-code usability. Trusted by 6,000+ orgs including Adobe, MIT, Dropbox. Key differentiators – #1 benchmarked accuracy • 1,400+ formats • Full white-labeling included • Flat-rate pricing vs OpenAI – 10% lower hallucination, 13% higher accuracy, 34% faster vs Botsonic/Chatbase – More file formats, source citations, no hidden costs vs LangChain – Production-ready in 2 min vs weeks of development	Market Position – Leading AI model provider; top GPT models as custom AI building blocks Target Customers – Dev teams building bespoke solutions; enterprises needing flexibility beyond RAG Key Competitors – Anthropic Claude API, Google Gemini, Azure AI, AWS Bedrock, RAG platforms ✅ Competitive Advantages – Top GPT-4 performance, frequent upgrades, excellent docs, massive ecosystem, Enterprise SOC 2/SSO ✅ Pricing Advantage – Pay-as-you-go highly cost-effective at small scale; best value low-volume use Use Case Fit – Ideal for custom AI requiring flexibility; less suitable for turnkey RAG without dev resources
R A G-as-a- Service Assessment	Platform type – TRUE RAG-AS-A-SERVICE with managed infrastructure API-first – REST API, Python SDK, OpenAI compatibility, MCP Server No-code option – 2-minute wizard deployment for non-developers Hybrid positioning – Serves both dev teams (APIs) and business users (no-code) Enterprise ready – SOC 2 Type II, GDPR, WCAG 2.0, flat-rate pricing	⚠️ NOT RAG-AS-A-SERVICE – Provides LLM models/APIs, not managed RAG infrastructure DIY RAG Architecture – Embed docs → external vector DB → retrieve → inject into prompt File Search (Beta) – Azure preview includes minimal semantic search; not production RAG ⚠️ No Managed Infrastructure – Unlike CustomGPT/Vectara, leaves chunking, indexing, retrieval to developers Framework vs Service – Compare to LLM APIs (Claude, Gemini), not managed RAG platforms External Costs – RAG needs vector DBs (Pinecone $70+/month), hosting, embeddings API
A I Models	OpenAI – GPT-5.1 (Optimal/Smart), GPT-4 series Anthropic – Claude 4.5 Opus/Sonnet (Enterprise) Auto-routing – Intelligent model selection for cost/performance Managed – No API keys or fine-tuning required	✅ GPT-4 Family – GPT-4 (8k/32k), GPT-4 Turbo (128k), GPT-4o - top language understanding/generation ✅ GPT-3.5 Family – GPT-3.5 Turbo (4k/16k) cost-effective with good performance ✅ Frequent Upgrades – Regular releases with improved capabilities, larger context windows ⚠️ OpenAI-Only – Cannot swap to Claude, Gemini; locked to OpenAI models ✅ Fine-Tuning – GPT-3.5 fine-tuning for domain-specific customization with training data
No- Code Interface & Usability	2-minute deployment – Fastest time-to-value in the industry Wizard interface – Step-by-step with visual previews Drag-and-drop – Upload files, paste URLs, connect cloud storage In-browser testing – Test before deploying to production Zero learning curve – Productive on day one	⚠️ Not No-Code – Requires coding embeddings, retrieval, chat UI; no-code OpenAI options minimal ChatGPT Web App – User-friendly but not embeddable with your data/branding by default Third-Party Tools – Zapier/Bubble offer partial integrations; not official OpenAI solutions Developer-Focused – Extremely capable for coders; less for non-technical teams wanting self-serve
Customization & Flexibility ( Behavior & Knowledge)	Live content updates – Add/remove content with automatic re-indexing System prompts – Shape agent behavior and voice through instructions Multi-agent support – Different bots for different teams Smart defaults – No ML expertise required for custom behavior	✅ Fine-Tuning Available – GPT-3.5 fine-tuning for style; knowledge injection via RAG code ⚠️ Content Freshness – Re-embed, re-fine-tune, or pass context each call; developer overhead Tool Calling Power – Powerful moderation/tools but requires thoughtful design; no unified UI Maximum Flexibility – Extremely flexible for general AI; lacks built-in document management
Pricing & Scalability	Standard: $99/mo – 60M words, 10 bots Premium: $449/mo – 300M words, 100 bots Auto-scaling – Managed cloud scales with demand Flat rates – No per-query charges	✅ Pay-As-You-Go – $0.0015/1K tokens GPT-3.5; ~$0.03-0.06/1K GPT-4 token pricing ⚠️ Scale Costs – Great low usage; bills spike at scale with rate limits No Flat Rate – Consumption-based only; cover external hosting (vector DB) separately Enterprise Contracts – Higher concurrency, compliance features, dedicated capacity via sales
Security & Privacy	SOC 2 Type II + GDPR – Third-party audited compliance Encryption – 256-bit AES at rest, SSL/TLS in transit Access controls – RBAC, 2FA, SSO, domain allowlisting Data isolation – Never trains on your data	✅ API Data Privacy – Not used for training; 30-day retention for abuse checks ✅ Encryption Standard – TLS in transit, at rest encryption; ChatGPT Enterprise adds SOC 2/SSO ⚠️ Developer Responsibility – You secure user inputs, logs, auth, HIPAA/GDPR compliance No User Portal – Build auth/access control in your own front-end
Support & Documentation	Documentation hub – Docs, tutorials, API references Support channels – Email, in-app chat, dedicated managers (Premium+) Open-source – Python SDK, Postman, GitHub examples Community – User community + 5,000 Zapier integrations	✅ Excellent Documentation – Comprehensive guides, API reference, code samples at platform.openai.com ✅ Official SDKs – Well-maintained Python, Node.js libraries with examples ✅ Massive Community – Extensive tutorials, LangChain/LlamaIndex integrations, ecosystem resources ⚠️ Limited Direct Support – Community forums for standard users; Enterprise gets premium support OpenAI Cookbook – Practical examples and recipes for common use cases including RAG
Additional Considerations	Time-to-value – 2-minute deployment vs weeks with DIY Always current – Auto-updates to latest GPT models Proven scale – 6,000+ organizations, millions of queries Multi-LLM – OpenAI + Claude reduces vendor lock-in	✅ Maximum Freedom – Best for bespoke AI solutions beyond RAG (code gen, creative writing) ✅ Regular Upgrades – Frequent model releases with bigger context windows keep tech current ⚠️ Coding Required – Near-infinite customization comes with setup complexity; developer-friendly only Cost Management – Token pricing cost-effective at small scale; maintaining RAG adds ongoing effort

Final Thoughts

Final Verdict: CustomGPT vs OpenAI

After analyzing features, pricing, performance, and user feedback, both CustomGPT and OpenAI are capable platforms that serve different market segments and use cases effectively.

When to Choose CustomGPT

You value industry-leading accuracy with 97% benchmark score
Patented technology to reduce hallucinations
Easy no-code setup with powerful customization

Best For: Industry-leading accuracy with 97% benchmark score

When to Choose OpenAI

You value industry-leading model performance
Comprehensive API features
Regular model updates

Best For: Industry-leading model performance

Migration & Switching Considerations

Switching between CustomGPT and OpenAI requires careful planning. Consider data export capabilities, API compatibility, and integration complexity. Both platforms offer migration support, but expect 2-4 weeks for complete transition including testing and team training.

Pricing Comparison Summary

CustomGPT starts at $99/month, while OpenAI begins at custom pricing. Total cost of ownership should factor in implementation time, training requirements, API usage fees, and ongoing support. Enterprise deployments typically see annual costs ranging from $10,000 to $500,000+ depending on scale and requirements.

Our Recommendation Process

Start with a free trial - Both platforms offer trial periods to test with your actual data
Define success metrics - Response accuracy, latency, user satisfaction, cost per query
Test with real use cases - Don't rely on generic demos; use your production data
Evaluate total cost - Factor in implementation time, training, and ongoing maintenance
Check vendor stability - Review roadmap transparency, update frequency, and support quality

For most organizations, the decision between CustomGPT and OpenAI comes down to specific requirements rather than overall superiority. Evaluate both platforms with your actual data during trial periods, focusing on accuracy, latency, ease of integration, and total cost of ownership.

📚 Next Steps

Ready to make your decision? We recommend starting with a hands-on evaluation of both platforms using your specific use case and data.

• Review: Check the detailed feature comparison table above
• Test: Sign up for free trials and test with real queries
• Calculate: Estimate your monthly costs based on expected usage
• Decide: Choose the platform that best aligns with your requirements

Last updated: December 25, 2025 | This comparison is regularly reviewed and updated to reflect the latest platform capabilities, pricing, and user feedback.

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Priyansh Khodiyar

DevRel at CustomGPT.ai. Passionate about AI and its applications. Here to help you navigate the world of AI tools and make informed decisions for your business.

CustomGPT vs OpenAI