DeepSeek-V4-Flash-0731 vs Qwen3.8-Flash-Next
DeepSeek-V4-Flash-0731 and Qwen3.8-Flash-Next are closely matched at 45.1 and 49.2 on the LLM Stats Score.
DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
DeepSeek-V4-Flash-0731 and Qwen3.8-Flash-Next are closely matched on the overall LLM Stats Score at 45.1 and 49.2.
In the 3 individual benchmarks reported for both models, Qwen3.8-Flash-Next wins 2; 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-Flash-0731
- you want predictable pricing at $0.09/M input and $0.18/M output
Choose Qwen3.8-Flash-Next
- you value its reported benchmark strengths — it wins 2 of 3 exact shared results
- 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
9 reported for DeepSeek-V4-Flash-0731 · 22 for Qwen3.8-Flash-Next
DeepSeek-V4-Flash-0731 outperforms in 1 benchmarks (NL2Repo), while Qwen3.8-Flash-Next is better at 2 benchmarks (Agents' Last Exam, Toolathlon).
Qwen3.8-Flash-Next 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-Flash-0731 has 179.0B more parameters than Qwen3.8-Flash-Next, making it 143.2% larger.
Context Window
Maximum input and output token capacity
Only DeepSeek-V4-Flash-0731 specifies input context (1,048,576 tokens). Only DeepSeek-V4-Flash-0731 specifies output context (384,000 tokens).
Input capabilities
Documented input modalities across available providers
Qwen3.8-Flash-Next supports multimodal inputs, whereas DeepSeek-V4-Flash-0731 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-Flash-0731
Qwen3.8-Flash-Next
License
Usage and distribution terms
DeepSeek-V4-Flash-0731 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-Flash-0731 was released on 2026-07-31, while Qwen3.8-Flash-Next was released on 2026-08-26.
Qwen3.8-Flash-Next is 1 month newer than DeepSeek-V4-Flash-0731.
Jul 31, 2026
1 months ago
Aug 26, 2026
1 weeks ago
3w 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-Flash-0731 and Qwen3.8-Flash-Next side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Flash-0731 vs Qwen3.8-Flash-Next.