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Model Comparison

Qwen3.5-397B-A17B vs DeepSeek-V4-Pro-Max

DeepSeek-V4-Pro-Max significantly outperforms across most benchmarks. Qwen3.5-397B-A17B is 1.6x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

9 benchmarks

Qwen3.5-397B-A17B outperforms in 1 benchmarks (MMLU-Pro), while DeepSeek-V4-Pro-Max is better at 8 benchmarks (BrowseComp, GPQA, Humanity's Last Exam, IMO-AnswerBench, SWE-bench Multilingual, SWE-Bench Verified, Terminal-Bench 2.0, Toolathlon).

DeepSeek-V4-Pro-Max significantly outperforms across most benchmarks.

Fri Apr 24 2026 • llm-stats.com

Arena Performance

Human preference votes

CallingBox

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Pricing Analysis

Price comparison per million tokens

Qwen3.5-397B-A17B costs less

For input processing, Qwen3.5-397B-A17B ($0.60/1M tokens) is 2.9x cheaper than DeepSeek-V4-Pro-Max ($1.74/1M tokens).

For output processing, Qwen3.5-397B-A17B ($3.60/1M tokens) is 1.0x more expensive than DeepSeek-V4-Pro-Max ($3.48/1M tokens).

In conclusion, DeepSeek-V4-Pro-Max is more expensive than Qwen3.5-397B-A17B.*

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

Lowest available price from all providers
Fri Apr 24 2026 • llm-stats.com
Alibaba Cloud / Qwen Team
Qwen3.5-397B-A17B
Input tokens$0.60
Output tokens$3.60
Best providerNovita
DeepSeek
DeepSeek-V4-Pro-Max
Input tokens$1.74
Output tokens$3.48
Best providerDeepSeek
Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

1203.0B diff

DeepSeek-V4-Pro-Max has 1203.0B more parameters than Qwen3.5-397B-A17B, making it 303.0% larger.

Alibaba Cloud / Qwen Team
Qwen3.5-397B-A17B
397.0Bparameters
DeepSeek
DeepSeek-V4-Pro-Max
1600.0Bparameters
397.0B
Qwen3.5-397B-A17B
1600.0B
DeepSeek-V4-Pro-Max

Context Window

Maximum input and output token capacity

DeepSeek-V4-Pro-Max accepts 1,048,576 input tokens compared to Qwen3.5-397B-A17B's 262,144 tokens. DeepSeek-V4-Pro-Max can generate longer responses up to 393,216 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-V4-Pro-Max
Input1,048,576 tokens
Output393,216 tokens
Fri Apr 24 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3.5-397B-A17B supports multimodal inputs, whereas DeepSeek-V4-Pro-Max 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-V4-Pro-Max

Text
Images
Audio
Video

License

Usage and distribution terms

Qwen3.5-397B-A17B is licensed under Apache 2.0, while DeepSeek-V4-Pro-Max 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-V4-Pro-Max

MIT

Open weights

Release Timeline

When each model was launched

Qwen3.5-397B-A17B was released on 2026-02-16, while DeepSeek-V4-Pro-Max was released on 2026-04-23.

DeepSeek-V4-Pro-Max is 2 months newer than Qwen3.5-397B-A17B.

Qwen3.5-397B-A17B

Feb 16, 2026

2 months ago

DeepSeek-V4-Pro-Max

Apr 23, 2026

1 days ago

2mo 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

Provider Availability

Qwen3.5-397B-A17B is available from Novita. DeepSeek-V4-Pro-Max is available from DeepSeek.

Qwen3.5-397B-A17B

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

DeepSeek-V4-Pro-Max

deepseek logo
DeepSeek
Input Price:Input: $1.74/1MOutput Price:Output: $3.48/1M
* 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

Supports multimodal inputs
Less expensive input tokens
Higher MMLU-Pro score (87.8% vs 87.5%)
DeepSeek
Larger context window (1,048,576 tokens)
Less expensive output tokens
Higher BrowseComp score (83.4% vs 69.0%)
Higher GPQA score (90.1% vs 88.4%)
Higher Humanity's Last Exam score (48.2% vs 28.7%)
Higher IMO-AnswerBench score (89.8% vs 80.9%)
Higher SWE-bench Multilingual score (76.2% vs 69.3%)
Higher SWE-Bench Verified score (80.6% vs 76.4%)
Higher Terminal-Bench 2.0 score (67.9% vs 52.5%)
Higher Toolathlon score (51.8% vs 38.3%)

Detailed Comparison

AI Model Comparison Table
Feature
Alibaba Cloud / Qwen Team
Qwen3.5-397B-A17B
DeepSeek
DeepSeek-V4-Pro-Max

FAQ

Common questions about Qwen3.5-397B-A17B vs DeepSeek-V4-Pro-Max

DeepSeek-V4-Pro-Max significantly outperforms across most benchmarks. Qwen3.5-397B-A17B is made by Alibaba Cloud / Qwen Team and DeepSeek-V4-Pro-Max 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-V4-Pro-Max scores CodeForces: 100.0%, HMMT Feb 26: 95.2%, LiveCodeBench: 93.5%, MathArena Apex: 90.2%, GPQA: 90.1%.
Qwen3.5-397B-A17B is 2.9x cheaper for input tokens. Qwen3.5-397B-A17B costs $0.60/M input and $3.60/M output via novita. DeepSeek-V4-Pro-Max costs $1.74/M input and $3.48/M output via deepseek.
Qwen3.5-397B-A17B supports 262K tokens and DeepSeek-V4-Pro-Max supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (262K vs 1.0M), input pricing ($0.60 vs $1.74/M), 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-V4-Pro-Max is developed by DeepSeek.