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[GH-ISSUE #14688] Add Support For Following Models By SarvamAI #9506

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opened 2026-04-12 22:25:49 -05:00 by GiteaMirror · 0 comments
GiteaMirror commented 2026-04-12 22:25:49 -05:00
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Originally created by @MeetSolanki530 on GitHub (Mar 7, 2026).
Original GitHub issue: https://github.com/ollama/ollama/issues/14688

🚀 Model Request: Add Sarvam AI Models to Ollama

Model Repository

Model Overview

Sarvam AI provides multilingual large language models optimized for Indian languages and reasoning tasks. These models support a wide range of Indic languages including Hindi, Gujarati, Tamil, Telugu, Kannada, and Marathi while maintaining strong English performance.

Adding Sarvam models to Ollama would enable developers to run Indic-focused LLMs locally, which is currently an underserved area in open-source LLM tooling.

Why This Model Should Be Added

  • Strong Indic language support
  • Useful for local AI applications in India
  • Good performance on reasoning, multilingual tasks, and coding
  • Growing ecosystem around Sarvam AI models
  • Expands Ollama’s coverage beyond primarily English-centric models

Potential Use Cases

  • Multilingual assistants for Indian users
  • Government and enterprise document processing
  • Regional language chatbots
  • Translation and cross-lingual workflows
  • Education and accessibility tools

Suggested Model Variants

Model Description
sarvam-1 Lightweight model for local deployment
sarvam-m Mid-size multilingual model
sarvam-30b Large high-performance model
sarvam-105b Enterprise-scale model

Technical Details

  • Organization: Sarvam AI
  • Architecture: Transformer / Mixture-of-Experts (larger variants)
  • Language Support: English + Indic languages (Hindi, Gujarati, Tamil, Telugu, Kannada, Marathi, etc.)
  • License: (As specified in the HuggingFace repositories)

Additional Notes

If required, the models could be converted to GGUF format for llama.cpp compatibility, allowing them to run efficiently through Ollama.

Adding Sarvam models would significantly improve regional language support within the Ollama ecosystem.

Originally created by @MeetSolanki530 on GitHub (Mar 7, 2026). Original GitHub issue: https://github.com/ollama/ollama/issues/14688 # 🚀 Model Request: Add Sarvam AI Models to Ollama ## Model Repository - https://huggingface.co/sarvamai/sarvam-1 - https://huggingface.co/sarvamai/sarvam-30b - https://huggingface.co/sarvamai/sarvam-105b - https://huggingface.co/sarvamai/sarvam-m --- ## Model Overview Sarvam AI provides multilingual large language models optimized for **Indian languages and reasoning tasks**. These models support a wide range of Indic languages including Hindi, Gujarati, Tamil, Telugu, Kannada, and Marathi while maintaining strong English performance. Adding Sarvam models to Ollama would enable developers to run **Indic-focused LLMs locally**, which is currently an underserved area in open-source LLM tooling. --- ## Why This Model Should Be Added - Strong **Indic language support** - Useful for **local AI applications in India** - Good performance on **reasoning, multilingual tasks, and coding** - Growing ecosystem around **Sarvam AI models** - Expands Ollama’s coverage beyond primarily English-centric models --- ## Potential Use Cases - Multilingual assistants for Indian users - Government and enterprise document processing - Regional language chatbots - Translation and cross-lingual workflows - Education and accessibility tools --- ## Suggested Model Variants | Model | Description | |------|-------------| | sarvam-1 | Lightweight model for local deployment | | sarvam-m | Mid-size multilingual model | | sarvam-30b | Large high-performance model | | sarvam-105b | Enterprise-scale model | --- ## Technical Details - **Organization:** Sarvam AI - **Architecture:** Transformer / Mixture-of-Experts (larger variants) - **Language Support:** English + Indic languages (Hindi, Gujarati, Tamil, Telugu, Kannada, Marathi, etc.) - **License:** (As specified in the HuggingFace repositories) --- ## Additional Notes If required, the models could be converted to **GGUF format for llama.cpp compatibility**, allowing them to run efficiently through Ollama. Adding Sarvam models would significantly improve **regional language support** within the Ollama ecosystem.
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