Sarvam-30B

Sarvam-30B (Chat LLM)

A 30B parameter Mixture-of-Experts reasoning model trained from scratch, optimized for Indian languages with only 2.4B active parameters per token. Delivers strong reasoning, coding, and conversational capabilities while remaining efficient to deploy.

Highlights:

• 30B total parameters, 2.4B active — efficient MoE architecture with Grouped Query Attention
• Pre-trained on 16 trillion tokens across code, math, multilingual, and web data
• State-of-the-art Indian language performance across native and romanized scripts
• Optimized inference for H100, L40S, and Apple Silicon (MXFP4)
• OpenAI-compatible chat completions API

At a Glance

Key Features

Learn More

For detailed information on architecture, training methodology, performance benchmarks, and inference optimizations, visit our blog.

Model Specifications

Key Capabilities

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from sarvamai import SarvamAI
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client = SarvamAI(
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    api_subscription_key="YOUR_SARVAM_API_KEY",
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)
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response = client.chat.completions(
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    model="sarvam-30b",
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    messages=[
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        {"role": "user", "content": "Explain the significance of the Indian monsoon season."}
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    ],
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    temperature=0.5,
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    top_p=1,
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    max_tokens=1000,
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)
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print(response.choices[0].message.content)

Limits

Known Limitations

Next Steps