IndiVibe
Models answer 110 source prompts in chat, STEM, math and coding, translated into 22 Indian languages in native and romanized script. A judge model compares answers pairwise.
The judge scores fluency, language and script correctness, usefulness and verbosity. Claude Opus 4 reference answers in English guide the usefulness score. Results are win rates.
- Made by
- Sarvam AI
- Released
- March 2026
- Kind
- Chat and instructions in many languages
- Level
- Everyday
- Scored
- Graded by a model
- Answers
- Open-ended
- Tasks
- All public
- Last in a launch post
- March 2026, dropped after it saturated
- Last model added
- March 2026
Sarvam 105B leads with 90%
Best score per model as labs report them in their own cards. Labs pick their own settings, so these compare less cleanly than independent runs.
- 1 Sarvam 105B 90%
- 2 Sarvam 30B 89%
Source: Labs’ model cards
| # | Model | Score | Setting | Date | Source |
|---|---|---|---|---|---|
| 1 | Sarvam 105B | 90% | Mar 2026 | Lab model card | |
| 2 | Sarvam 30B | 89% | Mar 2026 | Lab model card |
Sarvam AI’s own number for Sarvam 105B passed 85% in March 2026
All the scores we have, one dot each, so a model tested at several settings appears more than once.
Source: Labs’ model cards
Labs headline it less often now, last in March 2026
Launch posts from every lab that has listed it, one tick per post. Tall colored ticks include it, and short gray ones leave it out.
| Date | Launch post | Score | As the post writes it |
|---|---|---|---|
| Mar 6, 2026 | Sarvam 30B | 89 | Average pairwise win rate across all dimensions on the Indic benchmark (indivibe) |
| Mar 6, 2026 | Sarvam 105B | 90 | Average pairwise win rate across all dimensions on the Indic benchmark (indivibe) |
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