Particle-1 vs Sarvam-30B
Particle-1 leads the LLM Stats Score 31.9 to 18.9.
Particle AI · Sarvam AI · Updated for 2026
Which is better?
Particle-1 leads the overall LLM Stats Score 31.9 to 18.9, ranking #133 overall.
In the 2 individual benchmarks reported for both models, Particle-1 wins 2; this is a narrower head-to-head signal than the composite indexes.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Particle-1
- overall performance matters — it scores 31.9 and ranks #133 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- you want the most recent training data — it shipped Oct 2026
Choose Sarvam-30B
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Individual benchmarks
3 reported for Particle-1 · 14 for Sarvam-30B
Particle-1 outperforms in 2 benchmarks (GPQA, MMLU), while Sarvam-30B is better at 0 benchmarks.
Particle-1 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Context Window
Maximum input and output token capacity
Only Particle-1 specifies input context (1,048,576 tokens). Only Particle-1 specifies output context (131,072 tokens).
Input capabilities
Documented input modalities across available providers
Particle-1 supports multimodal inputs, whereas Sarvam-30B does not.
Particle-1 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Particle-1
Sarvam-30B
License
Usage and distribution terms
Particle-1 is licensed under a proprietary license, while Sarvam-30B uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
Particle-1 was released on 2026-10-28, while Sarvam-30B was released on 2026-03-06.
Particle-1 is 8 months newer than Sarvam-30B.
Oct 28, 2026
3 days ago
7mo newerMar 6, 2026
7 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Judge for yourself.
Run your own prompts against Particle-1 and Sarvam-30B side-by-side, then vote on the output you prefer.
FAQ
Common questions about Particle-1 vs Sarvam-30B.