# Which is the best LLM to build chatbots in 2025?
Author: Manav Mahajan
Author URL: https://www.heltar.com/blogs/author/manav-mahajan
Published: 2025-07-27
Category: WhatsApp Chatbot
Category URL: https://www.heltar.com/blogs/category/whatsapp-chatbot
Tags: WhatsApp Chatbot, Automation, AI
Tag URLs: WhatsApp Chatbot (https://www.heltar.com/blogs/tag/whatsapp-chatbot), Automation (https://www.heltar.com/blogs/tag/automation), AI (https://www.heltar.com/blogs/tag/ai)
URL: https://www.heltar.com/blogs/best-llm-for-building-chatbots-in-2025

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.

![How to integrate LLM's with WhatsApp using MCP](https://prod.superblogcdn.com/site_cuid_clnw4nrag2342701vpmufcj1n2w/images/image-cp-1753620767624-compressed.png)

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](https://www.heltar.com/blogs/best-llm-models-for-customer-support-chatbot) 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](https://www.heltar.com/blogs/best-llm-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

![Heltar](https://prod.superblogcdn.com/site_cuid_clnw4nrag2342701vpmufcj1n2w/images/auto1-1753620798018-compressed.webp)

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](https://www.heltar.com/demo.html) with our team today** and discover which model and architecture are best for your specific chatbot use case.


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