DeepSeek-V4-Pro-0813 vs Qwen3.8-Flash-Next
DeepSeek-V4-Pro-0813 and Qwen3.8-Flash-Next are closely matched at 52.1 and 49.1 on the LLM Stats Score.
DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
DeepSeek-V4-Pro-0813 and Qwen3.8-Flash-Next are closely matched on the overall LLM Stats Score at 52.1 and 49.1.
In the 4 individual benchmarks reported for both models, DeepSeek-V4-Pro-0813 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-Pro-0813
- you value its reported benchmark strengths — it wins 3 of 4 exact shared results
Choose Qwen3.8-Flash-Next
- you want the most recent training data — it shipped Aug 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
12 reported for DeepSeek-V4-Pro-0813 · 22 for Qwen3.8-Flash-Next
DeepSeek-V4-Pro-0813 outperforms in 3 benchmarks (Humanity's Last Exam, NL2Repo, Toolathlon), while Qwen3.8-Flash-Next is better at 1 benchmark (Agents' Last Exam).
DeepSeek-V4-Pro-0813 shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
DeepSeek-V4-Pro-0813 has 1475.0B more parameters than Qwen3.8-Flash-Next, making it 1180.0% larger.
Context Window
Maximum input and output token capacity
Only DeepSeek-V4-Pro-0813 specifies input context (1,048,576 tokens). Only DeepSeek-V4-Pro-0813 specifies output context (393,216 tokens).
Input capabilities
Documented input modalities across available providers
Qwen3.8-Flash-Next supports multimodal inputs, whereas DeepSeek-V4-Pro-0813 does not.
Qwen3.8-Flash-Next can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Pro-0813
Qwen3.8-Flash-Next
License
Usage and distribution terms
DeepSeek-V4-Pro-0813 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.
MIT
Open weights
Qwen Community License 1.0
Open weights
Release Timeline
When each model was launched
DeepSeek-V4-Pro-0813 was released on 2026-08-13, while Qwen3.8-Flash-Next was released on 2026-08-26.
Qwen3.8-Flash-Next is 0 month newer than DeepSeek-V4-Pro-0813.
Aug 13, 2026
4 weeks ago
Aug 26, 2026
2 weeks ago
1w newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Pro-0813 and Qwen3.8-Flash-Next side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Pro-0813 vs Qwen3.8-Flash-Next.