Model Comparison
Qwen3.5-397B-A17B vs DeepSeek-V4-Flash-MaxWhich is better in 2026?
DeepSeek-V4-Flash-Max significantly outperforms across most benchmarks. DeepSeek-V4-Flash-Max is 7.7x cheaper per token.
Verdict: Qwen3.5-397B-A17B vs DeepSeek-V4-Flash-Max — which is better?
Qwen3.5-397B-A17B (by Alibaba Cloud / Qwen Team) and DeepSeek-V4-Flash-Max (by DeepSeek) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
Qwen3.5-397B-A17B outperforms in 2 benchmarks (GPQA, MMLU-Pro), while DeepSeek-V4-Flash-Max is better at 7 benchmarks (BrowseComp, Humanity's Last Exam, IMO-AnswerBench, SWE-bench Multilingual, SWE-Bench Verified, Terminal-Bench 2.0, Toolathlon). DeepSeek-V4-Flash-Max significantly outperforms across most benchmarks.
On price, DeepSeek-V4-Flash-Max is roughly 7.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Flash-Max also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Choose Qwen3.5-397B-A17B if…
- you want predictable pricing at $0.60/M input and $3.60/M output
Choose DeepSeek-V4-Flash-Max if…
- you want the strongest raw capability — it leads on 7 of 9 shared benchmarks
- cost matters — it's about 7.7x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Apr 2026
Performance Benchmarks
Comparative analysis across standard metrics
Qwen3.5-397B-A17B outperforms in 2 benchmarks (GPQA, MMLU-Pro), while DeepSeek-V4-Flash-Max is better at 7 benchmarks (BrowseComp, Humanity's Last Exam, IMO-AnswerBench, SWE-bench Multilingual, SWE-Bench Verified, Terminal-Bench 2.0, Toolathlon).
DeepSeek-V4-Flash-Max significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, Qwen3.5-397B-A17B ($0.60/1M tokens) is 4.3x more expensive than DeepSeek-V4-Flash-Max ($0.14/1M tokens).
For output processing, Qwen3.5-397B-A17B ($3.60/1M tokens) is 12.9x more expensive than DeepSeek-V4-Flash-Max ($0.28/1M tokens).
In conclusion, Qwen3.5-397B-A17B is more expensive than DeepSeek-V4-Flash-Max.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Qwen3.5-397B-A17B has 113.0B more parameters than DeepSeek-V4-Flash-Max, making it 39.8% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Flash-Max accepts 1,048,576 input tokens compared to Qwen3.5-397B-A17B's 262,144 tokens. DeepSeek-V4-Flash-Max can generate longer responses up to 393,216 tokens, while Qwen3.5-397B-A17B is limited to 64,000 tokens.
Input Capabilities
Supported data types and modalities
Qwen3.5-397B-A17B supports multimodal inputs, whereas DeepSeek-V4-Flash-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
DeepSeek-V4-Flash-Max
License
Usage and distribution terms
Qwen3.5-397B-A17B is licensed under Apache 2.0, while DeepSeek-V4-Flash-Max uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
MIT
Open weights
Release Timeline
When each model was launched
Qwen3.5-397B-A17B was released on 2026-02-16, while DeepSeek-V4-Flash-Max was released on 2026-04-23.
DeepSeek-V4-Flash-Max is 2 months newer than Qwen3.5-397B-A17B.
Feb 16, 2026
3 months ago
Apr 23, 2026
1 months ago
2mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Qwen3.5-397B-A17B is available from Novita. DeepSeek-V4-Flash-Max is available from DeepSeek.
Qwen3.5-397B-A17B
DeepSeek-V4-Flash-Max
Outputs Comparison
Key Takeaways
Qwen3.5-397B-A17B
View detailsAlibaba Cloud / Qwen Team
Detailed Comparison
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FAQ
Common questions about Qwen3.5-397B-A17B vs DeepSeek-V4-Flash-Max.