Best Open-Source LLMs for Indian Languages in 2026
A curated catalog of production-ready open-source models for Indian language workloads - chat, reasoning, speech-to-text, TTS, and embeddings.
The Indic AI Model Landscape
The ecosystem of open-source models for Indian languages has matured dramatically. Two years ago, builders had few options beyond multilingual models that treated Indian languages as an afterthought. Today, there are purpose-built Indic-native models across every category - chat, reasoning, speech, and embeddings - many with permissive Apache 2.0 licenses.
This guide covers the production-ready options available for India-hosted deployment in mid-2026.
Chat and Conversation
Sarvam-30B
The current default choice for production Indian language workloads.
- Parameters: 32.2B (Mixture of Experts)
- Languages: English + 22 Indian languages (hi, bn, ta, te, mr, gu, kn, ml, pa, or, as, ur, sa, ne, sd, kok, mai, doi, mni, sat, ks, bo)
- License: Apache 2.0
- Context: 8K tokens
- VRAM: 77.2 GB (FP16), available in FP8 quantization
- Hosting: vLLM-ready, H100 recommended
Sarvam-30B is trained from the ground up for Indian languages - not fine-tuned from an English base. It handles code-mixing (Hinglish, Tanglish) naturally and understands cultural context that translated models miss.
Sarvam-M (24B)
Fine-tuned from Mistral Small 3.1 for Indian languages. Smaller than Sarvam-30B but with 32K context and strong multilingual performance.
- Parameters: 23.6B
- Languages: en, bn, hi, kn, gu, mr, ml, or, pa, ta, te
- License: Apache 2.0
- Context: 32K tokens
- Best for: Tasks needing longer context with good Indic support
Krutrim-2 (12B)
Economy-tier option from Ola's Krutrim team. Based on Mistral-NeMo architecture, optimized for 22 Indic languages.
- Parameters: 12B
- Languages: English + 22 scheduled Indian languages
- License: Apache 2.0
- Best for: High-volume chatbots, cost-sensitive deployments
Krutrim-1 (7B)
Smaller sibling, suitable for edge deployment or very high throughput.
- Parameters: 7B
- Languages: English + Hindi + major Indian languages
- License: Apache 2.0
- Best for: Lightweight chat, classification, extraction
OpenHathi-7B
Hindi-focused base model from Sarvam. Older but proven for Hindi-specific tasks.
- Parameters: 6.9B
- Languages: Hindi
- License: Llama 2 Community
- Best for: Hindi-only applications, fine-tuning base
Reasoning
Param2-17B Thinking
From BharatGenAI. A Mixture-of-Experts reasoning model with chain-of-thought capabilities in Indian languages.
- Parameters: 17.2B total, 2.4B active per token
- Languages: English + 22 Indian languages
- License: Apache 2.0
- VRAM: 41.2 GB (FP16)
- Best for: Multi-step reasoning, math, logic in Indian languages
This is currently the strongest open-source reasoning model with native Indic support. The MoE architecture means active parameters per inference are only 2.4B, making it efficient to serve despite the total parameter count.
Domain-Specific
FiMI-24B (Finance)
From NPCI (National Payments Corporation of India). Fine-tuned from Mistral Small 24B for Indian financial services.
- Parameters: 24B
- Languages: English, Hindi
- License: Mistral Research License
- Best for: Financial analysis, regulatory Q&A, banking use cases
Strong candidate for BFSI deployments where domain expertise matters more than broad language coverage.
Speech-to-Text (ASR)
IndicConformer-600M
From AI4Bharat. The widest language coverage for Indian ASR.
- Parameters: 600M
- Languages: 22 Indian languages (all scheduled languages)
- License: MIT
- Downloads: 41,000+
- Best for: Multilingual transcription, voice bot input
Whisper-V3 Hindi (Fine-tuned)
ARTPARK-IISc fine-tune of OpenAI's Whisper Large V3 on the Vaani Hindi dataset.
- Parameters: 1.5B
- Languages: Hindi
- License: Apache 2.0
- Best for: High-accuracy Hindi transcription
Dhwani
Government-backed speech LLM from IndiaAI (AIKosh). Covers multiple Indic languages for STT and translation.
- Languages: Multiple Indian languages
- Best for: Government and public sector deployments
Text-to-Speech (TTS)
Indic Parler TTS
From AI4Bharat. State-of-the-art multilingual TTS.
- Parameters: 937M
- Languages: 18 Indian languages (en, as, bn, gu, hi, kn, ks, or, ml, mr, ne, pa, sa, sd, ta, te, ur, om)
- License: Apache 2.0
- Downloads: 818,000+
- Best for: Production voice synthesis, IVR systems, accessibility
AI4Bharat VITS (vits_rasa_13)
Lighter TTS option covering 10+ languages.
- Parameters: 40M
- Languages: as, bn, brx, doi, kn, mai, ml, mr, ne, pa
- License: CC-BY-4.0
- Best for: Low-resource deployment, mobile/edge TTS
Embeddings and Retrieval
IndicBERT v2
From AI4Bharat. Multilingual BERT model for Indian language embeddings.
- Languages: 24 Indian languages
- License: MIT
- Best for: Semantic search, RAG retrieval, classification across Indian languages
MuRIL
Google's Multilingual Representations for Indian Languages.
- Languages: Bengali, Hindi, Tamil, Telugu, Kannada, Malayalam, Marathi, Punjabi, Urdu
- Best for: Cross-lingual retrieval, sentence similarity
How to Choose
| Use Case | Recommended Model | Tier |
|---|---|---|
| Production chatbot (multilingual) | Sarvam-30B | Default |
| High-volume simple chat | Krutrim-2 | Economy |
| Hindi-only application | OpenHathi-7B or Krutrim-1 | Economy |
| Complex reasoning (Indic) | Param2-17B Thinking | Default |
| BFSI domain tasks | FiMI-24B | Default |
| Voice bot input (multilingual) | IndicConformer-600M | Economy |
| Voice bot input (Hindi, high accuracy) | Whisper-V3 Hindi | Economy |
| Voice output (multilingual) | Indic Parler TTS | Economy |
| Semantic search / RAG | IndicBERT v2 | Economy |
Hosting Considerations
All models listed above can be self-hosted on Indian GPU infrastructure via vLLM or equivalent serving frameworks. Key considerations:
- 30B+ models need H100 or equivalent (77+ GB VRAM for FP16, ~40GB for FP8)
- 7-12B models run comfortably on A100 or even A30 GPUs
- Speech models (600M-1.5B) fit on any modern GPU including 8GB cards
- TTS models are lightweight and can run on CPU for low-volume use
Indian GPU providers (E2E Networks, NeevCloud, Yotta) offer H100s from $1.80/hr with INR billing.
What's Coming
Models we're tracking for near-term availability:
- Sarvam-105B - Premium tier, 106B parameters, complex reasoning
- Chitrarth - Vision-language model for Indian languages (multimodal)
- SUTRA - 50+ language architecture with decoupled language processing
- Praxy Voice - Commercial-quality Indic TTS with voice cloning
Access via IndicStack
All production-ready models in this guide are available (or coming soon) through IndicStack's OpenAI-compatible API. One base URL, one billing relationship, India-hosted inference.
No need to manage GPU infrastructure, model updates, or serving frameworks. Choose a model, change your base URL, and deploy.
Request early access to start building.