Model Comparison

Qwen3 VL 30B A3B Thinking vs Sarvam-30BWhich is better in 2026?

Qwen3 VL 30B A3B Thinking has a slight edge in benchmark performance.

Verdict: Qwen3 VL 30B A3B Thinking vs Sarvam-30B — which is better?

Qwen3 VL 30B A3B Thinking (by Alibaba Cloud / Qwen Team) and Sarvam-30B (by Sarvam AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.

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.

Choose Qwen3 VL 30B A3B Thinking if…

  • you want the strongest raw capability — it leads on 4 of 7 shared benchmarks

Choose Sarvam-30B if…

  • you want the most recent training data — it shipped Mar 2026

Performance Benchmarks

Comparative analysis across standard metrics

7 benchmarks

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.

Tue Jul 28 2026 • llm-stats.com

Arena Performance

Human preference votes

Model Size

Parameter count comparison

1.0B diff

Qwen3 VL 30B A3B Thinking has 1.0B more parameters than Sarvam-30B, making it 3.3% larger.

Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
31.0Bparameters
Sarvam AI
Sarvam-30B
30.0Bparameters
31.0B
Qwen3 VL 30B A3B Thinking
30.0B
Sarvam-30B

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).

Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
Input131,072 tokens
Output32,768 tokens
Sarvam AI
Sarvam-30B
Input- tokens
Output- tokens
Tue Jul 28 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

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

Text
Images
Audio
Video

Sarvam-30B

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under Apache 2.0.

Both models share the same licensing terms, providing consistent usage rights.

Qwen3 VL 30B A3B Thinking

Apache 2.0

Open weights

Sarvam-30B

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.

Qwen3 VL 30B A3B Thinking

Sep 22, 2025

10 months ago

Sarvam-30B

Mar 6, 2026

4 months ago

5mo newer

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Alibaba Cloud / Qwen Team

Qwen3 VL 30B A3B Thinking

View details

Alibaba Cloud / Qwen Team

Larger context window (131,072 tokens)
Supports multimodal inputs
Higher Arena-Hard v2 score (56.7% vs 49.0%)
Higher GPQA score (74.4% vs 66.5%)
Higher MMLU score (87.6% vs 85.1%)
Higher MMLU-Pro score (80.5% vs 80.0%)
Sarvam AI
Higher AIME 2025 score (96.7% vs 83.1%)
Higher HMMT25 score (74.2% vs 67.6%)
Higher LiveCodeBench v6 score (70.0% vs 64.2%)

Detailed Comparison

Interactive Arena

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.

Qwen3 VL 30B A3B Thinking
✓ Preferred
Sarvam-30B
Open in Playground
AI Model Comparison Table
Feature
Alibaba Cloud / Qwen Team
Qwen3 VL 30B A3B Thinking
Sarvam AI
Sarvam-30B

FAQ

Common questions about Qwen3 VL 30B A3B Thinking vs Sarvam-30B.

Which is better, Qwen3 VL 30B A3B Thinking or Sarvam-30B?

Qwen3 VL 30B A3B Thinking has a slight edge in benchmark performance. Qwen3 VL 30B A3B Thinking is made by Alibaba Cloud / Qwen Team and Sarvam-30B is made by Sarvam AI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Qwen3 VL 30B A3B Thinking compare to Sarvam-30B in benchmarks?

Qwen3 VL 30B A3B Thinking scores DocVQAtest: 95.0%, ScreenSpot: 94.7%, MMLU-Redux: 90.9%, MMBench-V1.1: 88.9%, MMLU: 87.6%. Sarvam-30B scores MATH-500: 97.0%, AIME 2025: 96.7%, MBPP: 92.7%, HumanEval: 92.1%, MMLU: 85.1%.

What are the context window sizes for Qwen3 VL 30B A3B Thinking and Sarvam-30B?

Qwen3 VL 30B A3B Thinking supports 131K tokens and Sarvam-30B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Qwen3 VL 30B A3B Thinking and Sarvam-30B?

Key differences include multimodal support (yes vs no). See the full comparison above for benchmark-by-benchmark results.

Who makes Qwen3 VL 30B A3B Thinking and Sarvam-30B?

Qwen3 VL 30B A3B Thinking is developed by Alibaba Cloud / Qwen Team and Sarvam-30B is developed by Sarvam AI.

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