Model Comparison

Gemini 3 Flash vs Sarvam-30B

Gemini 3 Flash significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

Gemini 3 Flash outperforms in 3 benchmarks (AIME 2025, GPQA, SWE-Bench Verified), while Sarvam-30B is better at 0 benchmarks.

Gemini 3 Flash significantly outperforms across most benchmarks.

Sat May 02 2026 • llm-stats.com

Arena Performance

Human preference votes

Context Window

Maximum input and output token capacity

Only Gemini 3 Flash specifies input context (1,000,000 tokens). Only Gemini 3 Flash specifies output context (65,536 tokens).

Google
Gemini 3 Flash
Input1,000,000 tokens
Output65,536 tokens
Sarvam AI
Sarvam-30B
Input- tokens
Output- tokens
Sat May 02 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Gemini 3 Flash supports multimodal inputs, whereas Sarvam-30B does not.

Gemini 3 Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.

Gemini 3 Flash

Text
Images
Audio
Video

Sarvam-30B

Text
Images
Audio
Video

License

Usage and distribution terms

Gemini 3 Flash 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.

Gemini 3 Flash

Proprietary

Closed source

Sarvam-30B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Gemini 3 Flash was released on 2025-12-17, while Sarvam-30B was released on 2026-03-06.

Sarvam-30B is 3 months newer than Gemini 3 Flash.

Gemini 3 Flash

Dec 17, 2025

4 months ago

Sarvam-30B

Mar 6, 2026

1 months ago

2mo newer

Knowledge Cutoff

When training data ends

Gemini 3 Flash has a documented knowledge cutoff of 2025-01-31, while Sarvam-30B's cutoff date is not specified.

We can confirm Gemini 3 Flash's training data extends to 2025-01-31, but cannot make a direct comparison without Sarvam-30B's cutoff date.

Gemini 3 Flash

Jan 2025

Sarvam-30B

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Outputs Comparison

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Key Takeaways

Google
Larger context window (1,000,000 tokens)
Supports multimodal inputs
Higher AIME 2025 score (99.7% vs 96.7%)
Higher GPQA score (90.4% vs 66.5%)
Higher SWE-Bench Verified score (78.0% vs 34.0%)
Sarvam AI
Has open weights

Detailed Comparison

AI Model Comparison Table
Feature
Google
Gemini 3 Flash
Sarvam AI
Sarvam-30B

FAQ

Common questions about Gemini 3 Flash vs Sarvam-30B.

Which is better, Gemini 3 Flash or Sarvam-30B?

Gemini 3 Flash significantly outperforms across most benchmarks. Gemini 3 Flash is made by Google 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 Gemini 3 Flash compare to Sarvam-30B in benchmarks?

Gemini 3 Flash scores Vending-Bench 2: 100.0%, AIME 2025: 99.7%, Global PIQA: 92.8%, MMMLU: 91.8%, GPQA: 90.4%. 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 Gemini 3 Flash and Sarvam-30B?

Gemini 3 Flash supports 1.0M 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 Gemini 3 Flash and Sarvam-30B?

Key differences include multimodal support (yes vs no), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes Gemini 3 Flash and Sarvam-30B?

Gemini 3 Flash is developed by Google and Sarvam-30B is developed by Sarvam AI.