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DeepSeek-V4-Flash-Max vs Qwen3.8-27B

Qwen3.8-27B shows notably better performance in the majority of benchmarks.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

DeepSeek-V4-Flash-Max outperforms in 1 benchmarks (Humanity's Last Exam), while Qwen3.8-27B is better at 2 benchmarks (GPQA, SWE-Bench Pro). Qwen3.8-27B shows notably better performance in the majority of benchmarks.

Based on current benchmark, pricing, and model metadata for 2026.

Choose DeepSeek-V4-Flash-Max

  • you want predictable pricing at $0.14/M input and $0.28/M output

Choose Qwen3.8-27B

  • you want the strongest raw capability — it leads on 2 of 3 shared benchmarks
  • you want the most recent training data — it shipped Aug 2026

At a glance

The differences that matter most.

Benchmark wins
1 of 3
2 of 3
Input price
$0.14 / M
— / M
Output price
$0.28 / M
— / M
Context window
1,048,576
Released
Apr 2026
Aug 2026
License
MIT
Apache 2.0

Performance Benchmarks

Comparative analysis across standard metrics

3 benchmarks

DeepSeek-V4-Flash-Max outperforms in 1 benchmarks (Humanity's Last Exam), while Qwen3.8-27B is better at 2 benchmarks (GPQA, SWE-Bench Pro).

Qwen3.8-27B shows notably better performance in the majority of benchmarks.

Tue Aug 25 2026 • llm-stats.com

Arena Performance

Playground indexes and blind preference scores

Model Size

Parameter count comparison

256.2B diff

DeepSeek-V4-Flash-Max has 256.2B more parameters than Qwen3.8-27B, making it 922.3% larger.

DeepSeek
DeepSeek-V4-Flash-Max
284.0Bparameters
Alibaba Cloud / Qwen Team
Qwen3.8-27B
27.8Bparameters
284.0B
DeepSeek-V4-Flash-Max
27.8B
Qwen3.8-27B

Context Window

Maximum input and output token capacity

Only DeepSeek-V4-Flash-Max specifies input context (1,048,576 tokens). Only DeepSeek-V4-Flash-Max specifies output context (393,216 tokens).

DeepSeek
DeepSeek-V4-Flash-Max
Input1,048,576 tokens
Output393,216 tokens
Alibaba Cloud / Qwen Team
Qwen3.8-27B
Input- tokens
Output- tokens
Tue Aug 25 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

Qwen3.8-27B supports multimodal inputs, whereas DeepSeek-V4-Flash-Max does not.

Qwen3.8-27B can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V4-Flash-Max

Text
Images
Audio
Video

Qwen3.8-27B

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4-Flash-Max is licensed under MIT, while Qwen3.8-27B uses Apache 2.0.

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

DeepSeek-V4-Flash-Max

MIT

Open weights

Qwen3.8-27B

Apache 2.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4-Flash-Max was released on 2026-04-23, while Qwen3.8-27B was released on 2026-08-14.

Qwen3.8-27B is 4 months newer than DeepSeek-V4-Flash-Max.

DeepSeek-V4-Flash-Max

Apr 23, 2026

4 months ago

Qwen3.8-27B

Aug 14, 2026

1 weeks ago

3mo 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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against DeepSeek-V4-Flash-Max and Qwen3.8-27B side-by-side, then vote on the output you prefer.

DeepSeek-V4-Flash-Max
✓ Preferred
Qwen3.8-27B
Open in Playground

FAQ

Common questions about DeepSeek-V4-Flash-Max vs Qwen3.8-27B.

Which is better, DeepSeek-V4-Flash-Max or Qwen3.8-27B?

Qwen3.8-27B shows notably better performance in the majority of benchmarks. DeepSeek-V4-Flash-Max is made by DeepSeek and Qwen3.8-27B is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.

How does DeepSeek-V4-Flash-Max compare to Qwen3.8-27B in benchmarks?

DeepSeek-V4-Flash-Max scores CodeForces: 100.0%, HMMT Feb 26: 94.8%, LiveCodeBench: 91.6%, IMO-AnswerBench: 88.4%, GPQA: 88.1%. Qwen3.8-27B scores MathVision: 94.6%, OmniDocBench 1.5: 91.1%, LiveCodeBench v6: 90.3%, CharXiv-R: 90.2%, GPQA: 89.2%.

What are the context window sizes for DeepSeek-V4-Flash-Max and Qwen3.8-27B?

DeepSeek-V4-Flash-Max supports 1.0M tokens and Qwen3.8-27B supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V4-Flash-Max and Qwen3.8-27B?

Key differences include multimodal support (no vs yes), licensing (MIT vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4-Flash-Max and Qwen3.8-27B?

DeepSeek-V4-Flash-Max is developed by DeepSeek and Qwen3.8-27B is developed by Alibaba Cloud / Qwen Team.