Mistral Medium 3.5 vs Sarvam-105B
Mistral Medium 3.5 and Sarvam-105B are closely matched at 26.9 and 25.7 on the LLM Stats Score.
Mistral AI · Sarvam AI · Updated for 2026
Which is better?
Mistral Medium 3.5 and Sarvam-105B are closely matched on the overall LLM Stats Score at 26.9 and 25.7.
In the 4 individual benchmarks reported for both models, Sarvam-105B wins 3; 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 Mistral Medium 3.5
- your work emphasizes coding — it leads those capability indexes
- you want the most recent training data — it shipped Apr 2026
Choose Sarvam-105B
- you value its reported benchmark strengths — it wins 3 of 4 exact shared results
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
11 reported for Mistral Medium 3.5 · 14 for Sarvam-105B
Mistral Medium 3.5 outperforms in 1 benchmarks (SWE-Bench Verified), while Sarvam-105B is better at 3 benchmarks (AIME 2025, Beyond AIME, BrowseComp).
Sarvam-105B shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
Mistral Medium 3.5 has 23.0B more parameters than Sarvam-105B, making it 21.9% larger.
Context Window
Maximum input and output token capacity
Only Mistral Medium 3.5 specifies input context (256,000 tokens). Only Mistral Medium 3.5 specifies output context (256,000 tokens).
Input capabilities
Documented input modalities across available providers
Mistral Medium 3.5 supports multimodal inputs, whereas Sarvam-105B does not.
Mistral Medium 3.5 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Mistral Medium 3.5
Sarvam-105B
License
Usage and distribution terms
Mistral Medium 3.5 is licensed under Modified MIT License, while Sarvam-105B uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Modified MIT License
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Mistral Medium 3.5 was released on 2026-04-29, while Sarvam-105B was released on 2026-03-06.
Mistral Medium 3.5 is 2 months newer than Sarvam-105B.
Apr 29, 2026
5 months ago
1mo newerMar 6, 2026
6 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 Mistral Medium 3.5 and Sarvam-105B side-by-side, then vote on the output you prefer.
FAQ
Common questions about Mistral Medium 3.5 vs Sarvam-105B.