Sarvam 105B
@sdn/sarvam-105bGeneral purposeLaunch planLive in the catalogSarvam AI's flagship model, released with open weights under Apache 2.0. It is a mixture-of-experts model with about 10B of its 106B parameters active per token, trained for 22 Indian languages plus English, so it handles Hindi, Hinglish and regional-language prompts well. Reasoning is on by default. Send reasoning_effort none to turn it off, and the first token arrives in about 0.6 s. In our tests it called tools reliably, including parallel calls, and with reasoning off it finished a coding fix that spanned several files.
- 0122 Indian languages and English, Hinglish included
- 02Reliable tool calls, including parallel calls
- 03Reasoning you can switch off for first tokens under a second
Strict, schema-faithful tool calls, enforced by the engine on every request — safe to build an agent loop on.
Thinks before it answers. Budget max_tokens generously — hidden reasoning counts against it.
Text-only.
One endpoint. Served by our engine.
Sarvam 105B is served through the Sideren engine — zero-downtime serving is the design target, not a status-page apology. You request it by name; everything else is our problem.
curl https://api.sideren.io/v1/messages \
-H "x-api-key: sdn_your_key" \
-H "content-type: application/json" \
-d '{
"model": "@sdn/sarvam-105b",
"max_tokens": 1024,
"messages": [{ "role": "user", "content": "Hello" }]
}'OpenAI-style clients work too — send the same model name to /v1/chat/completions with a Bearer key. See the docs for both dialects.
Your agent stays the same.
Its inference gets better.
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