Qwen3 VL 30B A3B Thinking vs Sarvam-30B
Qwen3 VL 30B A3B Thinking and Sarvam-30B are closely matched at 18.3 and 19.6 on the LLM Stats Score.
Alibaba Cloud / Qwen Team · Sarvam AI · Updated for 2026
Which is better?
Qwen3 VL 30B A3B Thinking and Sarvam-30B are closely matched on the overall LLM Stats Score at 18.3 and 19.6.
In the 7 individual benchmarks reported for both models, Qwen3 VL 30B A3B Thinking 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 Qwen3 VL 30B A3B Thinking
- you value its reported benchmark strengths — it wins 4 of 7 exact shared results
Choose Sarvam-30B
- 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
50 reported for Qwen3 VL 30B A3B Thinking · 14 for Sarvam-30B
Qwen3 VL 30B A3B Thinking outperforms in 4 benchmarks (Arena-Hard v2, GPQA, MMLU, MMLU-Pro), while Sarvam-30B is better at 3 benchmarks (AIME 2025, HMMT25, LiveCodeBench v6).
Qwen3 VL 30B A3B Thinking has a slight edge in benchmark performance.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
Qwen3 VL 30B A3B Thinking has 1.0B more parameters than Sarvam-30B, making it 3.3% larger.
Context Window
Maximum input and output token capacity
Only Qwen3 VL 30B A3B Thinking specifies input context (131,072 tokens). Only Qwen3 VL 30B A3B Thinking specifies output context (32,768 tokens).
Input capabilities
Documented input modalities across available providers
Qwen3 VL 30B A3B Thinking supports multimodal inputs, whereas Sarvam-30B does not.
Qwen3 VL 30B A3B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.
Qwen3 VL 30B A3B Thinking
Sarvam-30B
License
Usage and distribution terms
Both models are licensed under Apache 2.0.
Both models share the same licensing terms, providing consistent usage rights.
Apache 2.0
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
Qwen3 VL 30B A3B Thinking was released on 2025-09-22, while Sarvam-30B was released on 2026-03-06.
Sarvam-30B is 6 months newer than Qwen3 VL 30B A3B Thinking.
Sep 22, 2025
11 months ago
Mar 6, 2026
6 months ago
5mo 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 Qwen3 VL 30B A3B Thinking and Sarvam-30B side-by-side, then vote on the output you prefer.
FAQ
Common questions about Qwen3 VL 30B A3B Thinking vs Sarvam-30B.