Indic Models
Indic STT, TTS, and LLM models — optimized for Indian languages.
LLM
sarvam-105b
- Architecture: 105B MoE, MLA architecture
- Context: 128K tokens
- Training: Pre-trained on 12T tokens
- Best for: Complex reasoning, agentic tasks, long documents
- Thinking mode:
reasoning_effort: "low" | "medium" | "high"
sarvam-105b-conversations
- Architecture: 105B MoE, tuned for conversation and voice
- Context: 128K tokens
- Tool calling: yes
- Streaming: yes
- Best for: Multi-turn dialogue, voice agents, assistants that talk
- Thinking mode:
reasoning_effort: "low" | "medium" | "high"
Same family, same price and same 128K window as sarvam-105b — tuned for spoken dialogue rather than long-form work. It does not accept image input.
Thinking Mode
The sarvam-105b models support hybrid thinking mode:
response = client.chat.completions.create(
model="sarvam-105b",
messages=[{"role": "user", "content": "Solve this complex problem step by step"}],
extra_body={"reasoning_effort": "high"}
)| Value | Description |
|---|---|
"low" | Minimal reasoning — fastest, cheapest |
"medium" | Balanced reasoning |
"high" | Deep reasoning — best quality, slower |
The sarvam-* models reject "none" and "minimal"; the API maps both
of those values down to "low" so an OpenAI-style client that sends
reasoning_effort: "none" for thinking-off still works. Full
thinking-disable is available on the direct-routed kimi-k2.5 / kimi-k2.6 /
kimi-k2.7-code / gemma-4-26b-a4b-it models — see the reasoning_effort matrix.
Speech to Text
saaras:v3
- Languages: 23 (22 Indic + English)
- Output modes: transcribe, translate, verbatim, translit, codemix
- Auto language detection: yes
- Telephony support: 8kHz audio
- Endpoint:
POST /v1/audio/transcriptions
Supported languages include: Hindi, Bengali, Gujarati, Kannada, Malayalam, Marathi, Odia, Punjabi, Tamil, Telugu, Urdu, Assamese, Bodo, Dogri, Kashmiri, Konkani, Maithili, Manipuri, Nepali, Sanskrit, Santali, Sindhi, and English.
saaras:v4
- Languages: 24
- Output modes: transcribe, translate, verbatim, translit, codemix
- Auto language detection: yes
- Endpoint:
POST /v1/audio/transcriptions
Five output modes on one model — standard transcription, English translation, verbatim (fillers kept), Latin-script transliteration, and code-mixed output. Select one with the mode form field; transcribe is the default.
Text to Speech
bulbul:v3
- Voices: 37 speakers
- Languages: 11
- Audio codecs: WAV, MP3, OPUS, FLAC, AAC, Mulaw, Alaw, PCM
- Pace: 0.5–2.0 (maps to
speedparameter) - Sample rates: 8000, 16000, 22050, 24000, 48000 Hz
- Endpoint:
POST /v1/audio/speech
Default voice: shubh. See the Voices page for the full list.