Audience
Developers and AI teams building multilingual applications who need a reasoning-capable model optimized for Indian languages, coding, and mathematical tasks
About Sarvam-M
Sarvam-M is a multilingual, hybrid-reasoning large language model designed to deliver strong performance across Indian languages, mathematical reasoning, and programming tasks within a single, efficient system. Built on top of Mistral-Small, it is a 24-billion-parameter text-only model that has been enhanced through supervised fine-tuning, reinforcement learning with verifiable rewards, and inference optimizations to improve both accuracy and efficiency. The model is specifically trained to handle more than ten major Indic languages, supporting native scripts, romanized text, and code-mixed inputs, enabling seamless multilingual communication across diverse linguistic contexts. Sarvam-M introduces a hybrid reasoning approach that allows it to switch between “thinking” mode for complex tasks like math, logic, and coding, and faster response mode for everyday interactions, balancing performance and speed.
Other Popular Alternatives & Related Software
DeepSeek-V4-Pro
DeepSeek-V4-Pro is a large-scale Mixture-of-Experts (MoE) language model designed for advanced reasoning, coding, and long-context understanding. It features 1.6 trillion total parameters with 49 billion activated parameters, enabling high performance while maintaining efficiency. The model supports an exceptionally large context window of up to one million tokens, allowing it to process extensive documents and workflows. It uses a hybrid attention architecture to optimize long-context performance and reduce computational cost. DeepSeek-V4-Pro is trained on over 32 trillion tokens, improving its knowledge and reasoning capabilities. It also includes advanced optimization techniques for stability and faster convergence during training. The model supports multiple reasoning modes, allowing users to balance speed and accuracy based on their needs. Overall, it provides a powerful open-source solution for complex AI tasks and large-scale applications.
Learn more
Sarvam 105B
Sarvam-105B is the flagship large language model in Sarvam’s open source model family, designed to deliver high-performance reasoning, multilingual understanding, and agent-based execution within a single scalable system. Built as a Mixture-of-Experts (MoE) model with approximately 105 billion total parameters, of which only a fraction are activated per token, it achieves strong computational efficiency while maintaining high capability across complex tasks. The model is optimized for advanced reasoning, coding, mathematics, and agentic workflows, making it suitable for tasks that require multi-step problem solving and structured outputs rather than simple conversational responses. Sarvam-105B supports long-context processing of up to around 128K tokens, enabling it to handle large documents, extended conversations, and deep analytical queries without losing coherence.
Learn more
Sarvam 30B
Sarvam-30B is an open source, next-generation large language model designed as a unified system for both real-time conversational AI and deep reasoning workloads, built with a strong focus on multilingual intelligence and practical deployment. The 30B model is optimized for speed and efficiency, using a Mixture-of-Experts (MoE) architecture that activates only a subset of parameters per request, enabling high throughput, low latency, and deployment even in resource-constrained environments such as local machines or edge systems. It delivers strong performance in conversational tasks, coding, and reasoning while achieving state-of-the-art results across more than 20 Indian languages, making it highly effective for multilingual applications and voice-based systems. It represents a dual-tier architecture, a fast, deployable “conversational workhorse”, leveraging MoE designs to reduce compute cost while maintaining high performance.
Learn more
Nemotron 3 Ultra
Nemotron 3 Nano is a compact, open large language model in NVIDIA’s Nemotron 3 family, designed for efficient agentic reasoning, conversational AI, and coding tasks. It uses a hybrid Mixture-of-Experts Mamba-Transformer architecture that activates only a small subset of parameters per token, enabling low-latency inference while maintaining strong accuracy and reasoning performance. It has approximately 31.6 billion total parameters with around 3.2 billion active (3.6 billion including embeddings), allowing it to achieve higher accuracy than previous Nemotron 2 Nano while using less computation per forward pass. Nemotron 3 Nano supports long-context processing of up to one million tokens, enabling it to handle large documents, multi-step workflows, and extended reasoning chains in a single pass. It is designed for high-throughput, real-time execution, excelling in multi-turn conversations, tool calling, and agent-based workflows where tasks require planning, reasoning, and more.
Learn more
Company Information
Sarvam
Founded: 2023
India
www.sarvam.ai/blogs/sarvam-m
Videos and Screen Captures
Other Useful Business Software
MongoDB Atlas runs apps anywhere
MongoDB Atlas gives you the freedom to build and run modern applications anywhere—across AWS, Azure, and Google Cloud. With global availability in over 115 regions, Atlas lets you deploy close to your users, meet compliance needs, and scale with confidence across any geography.
Product Details
Platforms Supported
Cloud
Training
Documentation
Live Online
Videos
Support
24/7 Live Support
Online
