Model Comparison

Qwen3.5-397B-A17B vs Sarvam-30B

Qwen3.5-397B-A17B significantly outperforms across most benchmarks.

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Performance Benchmarks

Comparative analysis across standard metrics

7 benchmarks

Qwen3.5-397B-A17B outperforms in 7 benchmarks (BrowseComp, GPQA, HMMT 2025, HMMT25, LiveCodeBench v6, MMLU-Pro, SWE-Bench Verified), while Sarvam-30B is better at 0 benchmarks.

Qwen3.5-397B-A17B significantly outperforms across most benchmarks.

Sat Apr 18 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Cost data unavailable.

Lowest available price from all providers
Sat Apr 18 2026 • llm-stats.com
Alibaba Cloud / Qwen Team
Qwen3.5-397B-A17B
Input tokens$0.60
Output tokens$3.60
Best providerNovita
Sarvam AI
Sarvam-30B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

367.0B diff

Qwen3.5-397B-A17B has 367.0B more parameters than Sarvam-30B, making it 1223.3% larger.

Alibaba Cloud / Qwen Team
Qwen3.5-397B-A17B
397.0Bparameters
Sarvam AI
Sarvam-30B
30.0Bparameters
397.0B
Qwen3.5-397B-A17B
30.0B
Sarvam-30B

Context Window

Maximum input and output token capacity

Only Qwen3.5-397B-A17B specifies input context (262,144 tokens). Only Qwen3.5-397B-A17B specifies output context (64,000 tokens).

Alibaba Cloud / Qwen Team
Qwen3.5-397B-A17B
Input262,144 tokens
Output64,000 tokens
Sarvam AI
Sarvam-30B
Input- tokens
Output- tokens
Sat Apr 18 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3.5-397B-A17B supports multimodal inputs, whereas Sarvam-30B does not.

Qwen3.5-397B-A17B can handle both text and other forms of data like images, making it suitable for multimodal applications.

Qwen3.5-397B-A17B

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.

Qwen3.5-397B-A17B

Apache 2.0

Open weights

Sarvam-30B

Apache 2.0

Open weights

Release Timeline

When each model was launched

Qwen3.5-397B-A17B was released on 2026-02-16, while Sarvam-30B was released on 2026-03-06.

Sarvam-30B is 1 month newer than Qwen3.5-397B-A17B.

Qwen3.5-397B-A17B

Feb 16, 2026

2 months ago

Sarvam-30B

Mar 6, 2026

1 months ago

2w 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

Qwen3.5-397B-A17B

View details

Alibaba Cloud / Qwen Team

Larger context window (262,144 tokens)
Supports multimodal inputs
Higher BrowseComp score (69.0% vs 35.5%)
Higher GPQA score (88.4% vs 66.5%)
Higher HMMT 2025 score (94.8% vs 73.3%)
Higher HMMT25 score (92.7% vs 74.2%)
Higher LiveCodeBench v6 score (83.6% vs 70.0%)
Higher MMLU-Pro score (87.8% vs 80.0%)
Higher SWE-Bench Verified score (76.4% vs 34.0%)
Sarvam AI

Detailed Comparison

AI Model Comparison Table
Feature
Alibaba Cloud / Qwen Team
Qwen3.5-397B-A17B
Sarvam AI
Sarvam-30B

FAQ

Common questions about Qwen3.5-397B-A17B vs Sarvam-30B

Qwen3.5-397B-A17B significantly outperforms across most benchmarks. Qwen3.5-397B-A17B 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.
Qwen3.5-397B-A17B scores MMLU-Redux: 94.9%, HMMT 2025: 94.8%, C-Eval: 93.0%, HMMT25: 92.7%, IFEval: 92.6%. Sarvam-30B scores MATH-500: 97.0%, AIME 2025: 96.7%, MBPP: 92.7%, HumanEval: 92.1%, MMLU: 85.1%.
Qwen3.5-397B-A17B supports 262K 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.
Key differences include multimodal support (yes vs no). See the full comparison above for benchmark-by-benchmark results.
Qwen3.5-397B-A17B is developed by Alibaba Cloud / Qwen Team and Sarvam-30B is developed by Sarvam AI.