Model Comparison

Qwen3.5-397B-A17B vs DeepSeek R1 Distill Qwen 7B

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

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Performance Benchmarks

Comparative analysis across standard metrics

1 benchmarks

Qwen3.5-397B-A17B outperforms in 1 benchmarks (GPQA), while DeepSeek R1 Distill Qwen 7B is better at 0 benchmarks.

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

Wed Apr 15 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
Wed Apr 15 2026 • llm-stats.com
Alibaba Cloud / Qwen Team
Qwen3.5-397B-A17B
Input tokens$0.60
Output tokens$3.60
Best providerNovita
DeepSeek
DeepSeek R1 Distill Qwen 7B
Input tokens$0.00
Output tokens$0.00
Best providerUnknown Organization
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

389.4B diff

Qwen3.5-397B-A17B has 389.4B more parameters than DeepSeek R1 Distill Qwen 7B, making it 5110.0% larger.

Alibaba Cloud / Qwen Team
Qwen3.5-397B-A17B
397.0Bparameters
DeepSeek
DeepSeek R1 Distill Qwen 7B
7.6Bparameters
397.0B
Qwen3.5-397B-A17B
7.6B
DeepSeek R1 Distill Qwen 7B

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
DeepSeek
DeepSeek R1 Distill Qwen 7B
Input- tokens
Output- tokens
Wed Apr 15 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3.5-397B-A17B supports multimodal inputs, whereas DeepSeek R1 Distill Qwen 7B 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

DeepSeek R1 Distill Qwen 7B

Text
Images
Audio
Video

License

Usage and distribution terms

Qwen3.5-397B-A17B is licensed under Apache 2.0, while DeepSeek R1 Distill Qwen 7B uses MIT.

License differences may affect how you can use these models in commercial or open-source projects.

Qwen3.5-397B-A17B

Apache 2.0

Open weights

DeepSeek R1 Distill Qwen 7B

MIT

Open weights

Release Timeline

When each model was launched

Qwen3.5-397B-A17B was released on 2026-02-16, while DeepSeek R1 Distill Qwen 7B was released on 2025-01-20.

Qwen3.5-397B-A17B is 13 months newer than DeepSeek R1 Distill Qwen 7B.

Qwen3.5-397B-A17B

Feb 16, 2026

1 months ago

1.1yr newer
DeepSeek R1 Distill Qwen 7B

Jan 20, 2025

1.2 years ago

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 GPQA score (88.4% vs 49.1%)
DeepSeek

Detailed Comparison

AI Model Comparison Table
Feature
Alibaba Cloud / Qwen Team
Qwen3.5-397B-A17B
DeepSeek
DeepSeek R1 Distill Qwen 7B

FAQ

Common questions about Qwen3.5-397B-A17B vs DeepSeek R1 Distill Qwen 7B

Qwen3.5-397B-A17B significantly outperforms across most benchmarks. Qwen3.5-397B-A17B is made by Alibaba Cloud / Qwen Team and DeepSeek R1 Distill Qwen 7B is made by DeepSeek. 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%. DeepSeek R1 Distill Qwen 7B scores MATH-500: 92.8%, AIME 2024: 83.3%, GPQA: 49.1%, LiveCodeBench: 37.6%.
Qwen3.5-397B-A17B supports 262K tokens and DeepSeek R1 Distill Qwen 7B 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), licensing (Apache 2.0 vs MIT). See the full comparison above for benchmark-by-benchmark results.
Qwen3.5-397B-A17B is developed by Alibaba Cloud / Qwen Team and DeepSeek R1 Distill Qwen 7B is developed by DeepSeek.