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DeepSeek-V4.1-Flash vs Qwen3.8-Flash-Next

DeepSeek-V4.1-Flash and Qwen3.8-Flash-Next are closely matched at 51.8 and 49.1 on the LLM Stats Score.

DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash and Qwen3.8-Flash-Next are closely matched on the overall LLM Stats Score at 51.8 and 49.1.

In the 5 individual benchmarks reported for both models, DeepSeek-V4.1-Flash wins 3; this is a narrower head-to-head signal than the composite indexes.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-V4.1-Flash

  • your work emphasizes coding and agents — it leads those capability indexes
  • you value its reported benchmark strengths — it wins 3 of 5 exact shared results
  • you want the most recent training data — it shipped Sep 2026

Choose Qwen3.8-Flash-Next

  • you are already invested in the Alibaba Cloud / Qwen Team ecosystem

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash
DeepSeek
Qwen3.8-Flash-Next
Alibaba Cloud / Qwen Team
Core performance indexes
LLM Stats Score
51.8
#13
49.1
#20
Reasoning
48.9
#18
48.9
#19
Coding
44.2
#5
36.1
#23
Agents
41.1
#4
35.1
#20
Cost, coverage & limits
Benchmark wins
3 of 5
2 of 5
Input price
$0.22 / M
— / M
Output price
$0.66 / M
— / M
Context window
1,040,000
—

Capability indexes

Additional strengths measured across groups of related public benchmarks

4 shared
Index
DeepSeek-V4.1-Flash
Qwen3.8-Flash-Next
Math
35.2#43
32.7#56
Vision
29.5#31
34.1#14
Tool use
34.8#2
31.1#11
Multimodal
34.3#13
36.1#9
Conservative TrueSkill rating · higher is betterHow scores work

Individual benchmarks

20 reported for DeepSeek-V4.1-Flash · 22 for Qwen3.8-Flash-Next

5 shared

DeepSeek-V4.1-Flash outperforms in 3 benchmarks (DeepSWE 1.1, Humanity's Last Exam, NL2Repo), while Qwen3.8-Flash-Next is better at 2 benchmarks (Agents' Last Exam, GPQA).

DeepSeek-V4.1-Flash has a slight edge in benchmark performance.

Sun Sep 20 2026 • llm-stats.com

Human preference

Blind head-to-head votes and playground preference scores

Model Size

Parameter count comparison

638.2B diff

DeepSeek-V4.1-Flash has 638.2B more parameters than Qwen3.8-Flash-Next, making it 510.6% larger.

DeepSeek
DeepSeek-V4.1-Flash
763.2Bparameters
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
125.0Bparameters
763.2B
DeepSeek-V4.1-Flash
125.0B
Qwen3.8-Flash-Next

Context Window

Maximum input and output token capacity

Only DeepSeek-V4.1-Flash specifies input context (1,040,000 tokens). Only DeepSeek-V4.1-Flash specifies output context (393,216 tokens).

DeepSeek
DeepSeek-V4.1-Flash
Input1,040,000 tokens
Output393,216 tokens
Alibaba Cloud / Qwen Team
Qwen3.8-Flash-Next
Input- tokens
Output- tokens
Sun Sep 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

Both DeepSeek-V4.1-Flash and Qwen3.8-Flash-Next support multimodal inputs.

They are both capable of processing various types of data, offering versatility in application.

DeepSeek-V4.1-Flash

Text
Images
Audio
Video

Qwen3.8-Flash-Next

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash is licensed under MIT, while Qwen3.8-Flash-Next uses Qwen Community License 1.0.

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

DeepSeek-V4.1-Flash

MIT

Open weights

Qwen3.8-Flash-Next

Qwen Community License 1.0

Open weights

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash was released on 2026-09-10, while Qwen3.8-Flash-Next was released on 2026-08-26.

DeepSeek-V4.1-Flash is 1 month newer than Qwen3.8-Flash-Next.

DeepSeek-V4.1-Flash

Sep 10, 2026

1 weeks ago

2w newer
Qwen3.8-Flash-Next

Aug 26, 2026

3 weeks 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

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash and Qwen3.8-Flash-Next side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash
✓ Preferred
Qwen3.8-Flash-Next
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash vs Qwen3.8-Flash-Next.

Which is better, DeepSeek-V4.1-Flash or Qwen3.8-Flash-Next?

DeepSeek-V4.1-Flash and Qwen3.8-Flash-Next are closely matched on the LLM Stats Score at 51.8 and 49.1. DeepSeek-V4.1-Flash is made by DeepSeek and Qwen3.8-Flash-Next is made by Alibaba Cloud / Qwen Team. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V4.1-Flash compare to Qwen3.8-Flash-Next in benchmarks?

DeepSeek-V4.1-Flash scores CodeForces: 100.0%, GPQA: 90.9%, Terminal-Bench 2.1: 90.6%, BabyVision: 89.6%, CyberGym: 88.1%. Qwen3.8-Flash-Next scores MathVision: 95.7%, LiveCodeBench v6: 91.9%, GPQA: 91.7%, CharXiv-R: 90.6%, RealWorldQA: 88.5%.

What are the context window sizes for DeepSeek-V4.1-Flash and Qwen3.8-Flash-Next?

DeepSeek-V4.1-Flash supports 1.0M tokens and Qwen3.8-Flash-Next 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-V4.1-Flash and Qwen3.8-Flash-Next?

Key differences include LLM Stats Score (51.8 vs 49.1), licensing (MIT vs Qwen Community License 1.0). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash and Qwen3.8-Flash-Next?

DeepSeek-V4.1-Flash is developed by DeepSeek and Qwen3.8-Flash-Next is developed by Alibaba Cloud / Qwen Team.

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