Model Comparison

Qwen3.5-397B-A17B vs DeepSeek-V3

Qwen3.5-397B-A17B significantly outperforms across most benchmarks. DeepSeek-V3 is 2.8x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

7 benchmarks

Qwen3.5-397B-A17B outperforms in 7 benchmarks (C-Eval, GPQA, IFEval, LongBench v2, MMLU-Pro, MMLU-Redux, SWE-Bench Verified), while DeepSeek-V3 is better at 0 benchmarks.

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

Thu Apr 16 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V3 costs less

For input processing, Qwen3.5-397B-A17B ($0.60/1M tokens) is 2.2x more expensive than DeepSeek-V3 ($0.27/1M tokens).

For output processing, Qwen3.5-397B-A17B ($3.60/1M tokens) is 3.3x more expensive than DeepSeek-V3 ($1.10/1M tokens).

In conclusion, Qwen3.5-397B-A17B is more expensive than DeepSeek-V3.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Thu Apr 16 2026 • llm-stats.com
Alibaba Cloud / Qwen Team
Qwen3.5-397B-A17B
Input tokens$0.60
Output tokens$3.60
Best providerNovita
DeepSeek
DeepSeek-V3
Input tokens$0.27
Output tokens$1.10
Best providerDeepSeek
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

274.0B diff

DeepSeek-V3 has 274.0B more parameters than Qwen3.5-397B-A17B, making it 69.0% larger.

Alibaba Cloud / Qwen Team
Qwen3.5-397B-A17B
397.0Bparameters
DeepSeek
DeepSeek-V3
671.0Bparameters
397.0B
Qwen3.5-397B-A17B
671.0B
DeepSeek-V3

Context Window

Maximum input and output token capacity

Qwen3.5-397B-A17B accepts 262,144 input tokens compared to DeepSeek-V3's 131,072 tokens. DeepSeek-V3 can generate longer responses up to 131,072 tokens, while Qwen3.5-397B-A17B is limited to 64,000 tokens.

Alibaba Cloud / Qwen Team
Qwen3.5-397B-A17B
Input262,144 tokens
Output64,000 tokens
DeepSeek
DeepSeek-V3
Input131,072 tokens
Output131,072 tokens
Thu Apr 16 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3.5-397B-A17B supports multimodal inputs, whereas DeepSeek-V3 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-V3

Text
Images
Audio
Video

License

Usage and distribution terms

Qwen3.5-397B-A17B is licensed under Apache 2.0, while DeepSeek-V3 uses MIT + Model License (Commercial use allowed).

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-V3

MIT + Model License (Commercial use allowed)

Open weights

Release Timeline

When each model was launched

Qwen3.5-397B-A17B was released on 2026-02-16, while DeepSeek-V3 was released on 2024-12-25.

Qwen3.5-397B-A17B is 14 months newer than DeepSeek-V3.

Qwen3.5-397B-A17B

Feb 16, 2026

1 months ago

1.1yr newer
DeepSeek-V3

Dec 25, 2024

1.3 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

Provider Availability

Qwen3.5-397B-A17B is available from Novita. DeepSeek-V3 is available from DeepSeek.

Qwen3.5-397B-A17B

novita logo
Novita
Input Price:Input: $0.60/1MOutput Price:Output: $3.60/1M

DeepSeek-V3

deepseek logo
DeepSeek
Input Price:Input: $0.27/1MOutput Price:Output: $1.10/1M
* Prices shown are per million tokens

Outputs Comparison

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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 C-Eval score (93.0% vs 86.5%)
Higher GPQA score (88.4% vs 59.1%)
Higher IFEval score (92.6% vs 86.1%)
Higher LongBench v2 score (63.2% vs 48.7%)
Higher MMLU-Pro score (87.8% vs 75.9%)
Higher MMLU-Redux score (94.9% vs 89.1%)
Higher SWE-Bench Verified score (76.4% vs 42.0%)
DeepSeek
Less expensive input tokens
Less expensive output tokens

Detailed Comparison

AI Model Comparison Table
Feature
Alibaba Cloud / Qwen Team
Qwen3.5-397B-A17B
DeepSeek
DeepSeek-V3

FAQ

Common questions about Qwen3.5-397B-A17B vs DeepSeek-V3

Qwen3.5-397B-A17B significantly outperforms across most benchmarks. Qwen3.5-397B-A17B is made by Alibaba Cloud / Qwen Team and DeepSeek-V3 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-V3 scores DROP: 91.6%, CLUEWSC: 90.9%, MATH-500: 90.2%, MMLU-Redux: 89.1%, MMLU: 88.5%.
DeepSeek-V3 is 2.2x cheaper for input tokens. Qwen3.5-397B-A17B costs $0.60/M input and $3.60/M output via novita. DeepSeek-V3 costs $0.27/M input and $1.10/M output via deepseek.
Qwen3.5-397B-A17B supports 262K tokens and DeepSeek-V3 supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (262K vs 131K), input pricing ($0.60 vs $0.27/M), multimodal support (yes vs no), licensing (Apache 2.0 vs MIT + Model License (Commercial use allowed)). See the full comparison above for benchmark-by-benchmark results.
Qwen3.5-397B-A17B is developed by Alibaba Cloud / Qwen Team and DeepSeek-V3 is developed by DeepSeek.