In the past year, businesses of every size, especially emerging D2C brands, have been rethinking how they engage with customers. What used to be the domain of scripted chatbots and static FAQs has evolved into dynamic, AI-driven conversations that feel almost human.
But not all AI models are created equal.
So we asked the real question: Which LLMs are best suited for building accurate, fast, and cheap chatbots today?
At Heltar, where we help businesses automate conversations via WhatsApp Business API, we’ve seen firsthand how the choice of a Large Language Model (LLM) can make or break the customer support experience. We tested the most current and capable LLMs for this exact use case. Here's what we found.
This blog distills our learnings to help you select the best LLM, not just in isolation but in the context of the kind of chatbot you’re building.
Why the “Best LLM” Depends on the Use Case?
There is no single “best” LLM. The right model depends entirely on what kind of chatbot you are building. Each chatbot has different demands.
Chatbot Type | Primary Goal | LLM Needs |
|---|---|---|
Support Bot | Accurate resolutions, fast responses | High accuracy, low hallucination, fast context switching |
Sales Bot | Persuasion, follow-ups, lead scoring | Conversational fluency, personalization, structure adherence |
Onboarding Bot | Educate, activate new users, answer FAQs | Instruction-following, memory, structured responses |
Utility Bot | Perform tasks (bookings, updates, etc.) | Tool-use, output formatting, deterministic logic |
Multilingual Bot | Engage diverse user base (e.g. India) | Native multilingual fluency, tone adaptability |
To assess how each model performs, we looked at six key capabilities.
Evaluation Criteria
Criteria | Why It Matters |
|---|---|
Accuracy | Essential for factual correctness in support or informational bots |
Speed (Latency) | Crucial for WhatsApp or real-time experiences |
Instruction Following | Can it respond in formats like JSON, buttons, or predefined templates? |
Memory and Context | Does it track previous user inputs across long flows? |
Conversational Fluency | Important for persuasive sales flows and human-like tone |
Cost Efficiency | Can it scale to thousands of chats per day affordably? |
Models Evaluated
We focused on six of the most production-ready and widely used models in 2025.
Model | Provider(s) | Open Source | Key Strength |
|---|---|---|---|
GPT-4o | OpenAI | No | Industry-leading fluency and reasoning |
Claude 3 Sonnet | Anthropic | No | Safe, contextual, emotionally intelligent |
Gemini 1.5 Flash | Google | No | Ultra-fast, great for structured tasks |
Command R+ | Cohere | Yes | Excellent for instruction-following and structured outputs |
Mistral 7B | Mistral and others | Yes | Fast and affordable, ready for fine-tuning |
LLaMA 3 (8B) | Meta | Yes | Multilingual, tunable, open for customization |
Comparative Scoring (1 to 5 scale)
Model | Accuracy | Speed | Instruction Following | Memory | Fluency | Cost Efficiency |
|---|---|---|---|---|---|---|
GPT-4o | 5 | 4 | 5 | 5 | 5 | 2 |
Claude 3 | 4.5 | 4 | 4.5 | 5 | 4.5 | 3 |
Gemini Flash | 4 | 5 | 4.5 | 3.5 | 4 | 3.5 |
Command R+ | 4 | 5 | 5 | 4 | 4 | 4 |
Mistral 7B | 3.8 | 5 | 3.5 | 3.5 | 3.8 | 5 |
LLaMA 3 | 4.2 | 4.5 | 4 | 4 | 4 | 5 |
Best LLM by Chatbot Type
1. For Support Chatbots
Need: high factual accuracy, low hallucination, fast recovery
Best Picks:
GPT-4o for unmatched accuracy and instruction following
Claude 3 for safest outputs with long memory
Command R+ for structured FAQ support at scale
Why: Support bots require precision and reliability. GPT-4o is ideal for industries like finance and healthcare. Claude adds an empathetic tone that helps in sensitive interactions. Command R+ is the right fit when scale matters more than nuance.
(Read more about LLMs for customer support chatbots here.)
2. For Sales Chatbots
Need: persuasive tone, follow-up ability, CRM-ready structure
Best Picks:
GPT-4o for high-conversion conversational logic
Claude 3 Sonnet for longer sales flows and user nurture
Mistral 7B for budget-conscious outreach when prompt-tuned
Why: Sales chatbots need to feel human, follow up logically, and handle objections. GPT-4o does this best for premium products. Claude works beautifully in longer B2B cycles. Mistral, when tuned well, scales affordably for ecommerce or mid-funnel leads.
(Read more about LLMs for Sales chatbots here.)
3. For Onboarding Chatbots
Need: guide users, explain steps clearly, maintain memory
Best Picks:
Claude 3 for clean step-by-step instructions and long flows
Command R+ for structured interactions like account setup
Gemini Flash for quick, app-like onboarding experiences
Why: These bots need to educate users while keeping the interface simple. Claude works well in educational and HR contexts. Command R+ is best for step logic like KYC onboarding. Gemini’s speed suits mobile-first SaaS or fintech flows.
4. For Utility Bots (e.g. Booking, Tracking)
Need: deterministic responses, tool-use readiness, accuracy
Best Picks:
Command R+ for fast and precise structured outputs
Gemini Flash for responsive booking or order flows
LLaMA 3 for cost-effective, logic-driven flows with fine-tuning
Why: Utility bots must deliver consistent results like booking confirmation, date pickers, or calculations. Command R+ is purpose-built for this. Gemini adds snappiness. LLaMA can replicate API-based logic with the right wrapper.
5. For Multilingual or Regional Bots
Need: fluency in Hinglish, Hindi, or other Indian languages
Best Picks:
GPT-4o for robust multilingual support across Indian dialects
LLaMA 3 for regional bot fine-tuning in open environments
Claude 3 for conversational fluency with Indian tone adaptability
Why: For Indian businesses, reaching users in their preferred language matters deeply. GPT-4o works well out of the box. LLaMA lets you control tone, voice, and grammar through training. Claude feels emotionally native in Hindi and Hinglish.
What Heltar Recommends?
We never recommend an LLM in isolation. We recommend the best model for your business goals, volume, and customer flow.
If you need... | Our recommendation |
|---|---|
Highest accuracy and trust | GPT-4o for regulated or mission-critical flows |
Scalability on a budget | Mistral 7B or LLaMA 3 with RAG and tuning |
CRM-integrated lead chatbots | Command R+ for structured CRM fields |
Regional language support | GPT-4o or LLaMA 3 with Hinglish prompts |
User onboarding journeys | Claude 3 Sonnet or Gemini Flash |
And with Heltar, you get:
Chatbot development on WhatsApp Business API
Multi-LLM routing logic (different model for different use case)
CRM and catalog integrations
Multilingual capability built-in
Domain-specific fine-tuning and retrieval-augmented setup
Final Thoughts
Choosing the right LLM is not just a technical decision. It is a business decision. The difference between a mediocre chatbot and one that boosts conversion, satisfaction, or retention is often the model underneath.
At Heltar, we help businesses choose the right LLM and build chatbots that do more than just respond. They convert, educate, assist, and retain.
Book a free consultation with our team today and discover which model and architecture are best for your specific chatbot use case.
