DeepSeek-R1-0528 vs Sarvam-105B
DeepSeek-R1-0528 and Sarvam-105B are closely matched at 24.1 and 25.7 on the LLM Stats Score.
DeepSeek · Sarvam AI · Updated for 2026
Which is better?
DeepSeek-R1-0528 and Sarvam-105B are closely matched on the overall LLM Stats Score at 24.1 and 25.7.
In the 7 individual benchmarks reported for both models, Sarvam-105B wins 4; 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 DeepSeek-R1-0528
- you want predictable pricing at $0.50/M input and $2.15/M output
Choose Sarvam-105B
- your work emphasizes agents — it leads those capability indexes
- you value its reported benchmark strengths — it wins 4 of 7 exact shared results
- you want the most recent training data — it shipped Mar 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
16 reported for DeepSeek-R1-0528 · 14 for Sarvam-105B
DeepSeek-R1-0528 outperforms in 3 benchmarks (GPQA, Humanity's Last Exam, MMLU-Pro), while Sarvam-105B is better at 4 benchmarks (AIME 2025, BrowseComp, HMMT 2025, SWE-Bench Verified).
Sarvam-105B has a slight edge in benchmark performance.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
DeepSeek-R1-0528 has 566.0B more parameters than Sarvam-105B, making it 539.0% larger.
Context Window
Maximum input and output token capacity
Only DeepSeek-R1-0528 specifies input context (163,840 tokens). Only DeepSeek-R1-0528 specifies output context (163,840 tokens).
License
Usage and distribution terms
DeepSeek-R1-0528 is licensed under MIT, while Sarvam-105B uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek-R1-0528 was released on 2025-05-28, while Sarvam-105B was released on 2026-03-06.
Sarvam-105B is 9 months newer than DeepSeek-R1-0528.
May 28, 2025
1.3 years ago
Mar 6, 2026
6 months ago
9mo newerKnowledge 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 DeepSeek-R1-0528 and Sarvam-105B side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-R1-0528 vs Sarvam-105B.