Model Comparison

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

DeepSeek-V4-Flash-Max significantly outperforms across most benchmarks. DeepSeek-V4-Flash-Max is 7.7x cheaper per token.

Want to compare interactively?Try the playground

Performance Benchmarks

Comparative analysis across standard metrics

9 benchmarks

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.

Wed May 13 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

DeepSeek-V4-Flash-Max costs less

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

Lowest available price from all providers

Wed May 13 2026 • llm-stats.com

Qwen3.5-397B-A17B

Input tokens$0.60

Output tokens$3.60

Best providerNovita

DeepSeek-V4-Flash-Max

Input tokens$0.14

Output tokens$0.28

Best providerDeepSeek

Notice missing or incorrect data?Start an Issue→

Model Size

Parameter count comparison

113.0B diff

Qwen3.5-397B-A17B has 113.0B more parameters than DeepSeek-V4-Flash-Max, making it 39.8% larger.

Qwen3.5-397B-A17B

397.0Bparameters

DeepSeek-V4-Flash-Max

284.0Bparameters

397.0B

Qwen3.5-397B-A17B

284.0B

DeepSeek-V4-Flash-Max

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.

Qwen3.5-397B-A17B

Input262,144 tokens

Output64,000 tokens

DeepSeek-V4-Flash-Max

Input1,048,576 tokens

Output393,216 tokens

Wed May 13 2026 • llm-stats.com

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

Text

Images

Audio

Video

DeepSeek-V4-Flash-Max

Text

Images

Audio

Video

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.

Qwen3.5-397B-A17B

Apache 2.0

Open weights

DeepSeek-V4-Flash-Max

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.

Qwen3.5-397B-A17B

Feb 16, 2026

2 months ago

DeepSeek-V4-Flash-Max

Apr 23, 2026

2 weeks 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-Flash-Max is available from DeepSeek.

Qwen3.5-397B-A17B

Novita

Input Price:Input: $0.60/1MOutput Price:Output: $3.60/1M

DeepSeek-V4-Flash-Max

DeepSeek

Input Price:Input: $0.14/1MOutput Price:Output: $0.28/1M

* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Key Takeaways

Qwen3.5-397B-A17B

View details

Alibaba Cloud / Qwen Team

Supports multimodal inputs

Higher GPQA score (88.4% vs 88.1%)

Higher MMLU-Pro score (87.8% vs 86.2%)

DeepSeek-V4-Flash-Max

View details

DeepSeek

Larger context window (1,048,576 tokens)

Less expensive input tokens

Less expensive output tokens

Higher BrowseComp score (73.2% vs 69.0%)

Higher Humanity's Last Exam score (45.1% vs 28.7%)

Higher IMO-AnswerBench score (88.4% vs 80.9%)

Higher SWE-bench Multilingual score (73.3% vs 69.3%)

Higher SWE-Bench Verified score (79.0% vs 76.4%)

Higher Terminal-Bench 2.0 score (56.9% vs 52.5%)

Higher Toolathlon score (47.8% vs 38.3%)

Detailed Comparison

AI Model Comparison Table
Feature	Qwen3.5-397B-A17B	DeepSeek-V4-Flash-Max

FAQ

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

Which is better, Qwen3.5-397B-A17B or DeepSeek-V4-Flash-Max?

DeepSeek-V4-Flash-Max significantly outperforms across most benchmarks. Qwen3.5-397B-A17B is made by Alibaba Cloud / Qwen Team and DeepSeek-V4-Flash-Max is made by DeepSeek. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does Qwen3.5-397B-A17B compare to DeepSeek-V4-Flash-Max in benchmarks?

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-Flash-Max scores CodeForces: 100.0%, HMMT Feb 26: 94.8%, LiveCodeBench: 91.6%, IMO-AnswerBench: 88.4%, GPQA: 88.1%.

Is Qwen3.5-397B-A17B cheaper than DeepSeek-V4-Flash-Max?

DeepSeek-V4-Flash-Max is 4.3x cheaper for input tokens. Qwen3.5-397B-A17B costs $0.60/M input and $3.60/M output via novita. DeepSeek-V4-Flash-Max costs $0.14/M input and $0.28/M output via deepseek.

What are the context window sizes for Qwen3.5-397B-A17B and DeepSeek-V4-Flash-Max?

Qwen3.5-397B-A17B supports 262K tokens and DeepSeek-V4-Flash-Max supports 1.0M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between Qwen3.5-397B-A17B and DeepSeek-V4-Flash-Max?

Key differences include context window (262K vs 1.0M), input pricing ($0.60 vs $0.14/M), multimodal support (yes vs no), licensing (Apache 2.0 vs MIT). See the full comparison above for benchmark-by-benchmark results.

Who makes Qwen3.5-397B-A17B and DeepSeek-V4-Flash-Max?

Qwen3.5-397B-A17B is developed by Alibaba Cloud / Qwen Team and DeepSeek-V4-Flash-Max is developed by DeepSeek.