DeepSeek-V4-Pro-0813 vs Qwen3.8-27B
DeepSeek-V4-Pro-0813 leads the LLM Stats Score 52.5 to 45.2.
DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
DeepSeek-V4-Pro-0813 leads the overall LLM Stats Score 52.5 to 45.2, ranking #10 overall.
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.
DeepSeek-V4-Pro-0813 also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose DeepSeek-V4-Pro-0813
- overall performance matters — it scores 52.5 and ranks #10 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 3 of 4 exact shared results
- you process long inputs — it offers a 1,048,576 token context window
Choose Qwen3.8-27B
- 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 · 26 for Qwen3.8-27B
DeepSeek-V4-Pro-0813 outperforms in 3 benchmarks (Humanity's Last Exam, NL2Repo, Terminal-Bench 2.1), while Qwen3.8-27B 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 1572.2B more parameters than Qwen3.8-27B, making it 5659.2% larger.
Context Window
Maximum input and output token capacity
DeepSeek-V4-Pro-0813 accepts 1,048,576 input tokens compared to Qwen3.8-27B's 262,144 tokens. DeepSeek-V4-Pro-0813 can generate longer responses up to 393,216 tokens, while Qwen3.8-27B is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Qwen3.8-27B supports multimodal inputs, whereas DeepSeek-V4-Pro-0813 does not.
Qwen3.8-27B can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Pro-0813
Qwen3.8-27B
License
Usage and distribution terms
DeepSeek-V4-Pro-0813 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.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek-V4-Pro-0813 was released on 2026-08-13, while Qwen3.8-27B was released on 2026-08-14.
Qwen3.8-27B is 0 month newer than DeepSeek-V4-Pro-0813.
Aug 13, 2026
3 weeks ago
Aug 14, 2026
3 weeks ago
1d newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-V4-Pro-0813 is available from DeepSeek, DeepInfra, Novita, Together. Qwen3.8-27B is available from FriendliAI.
DeepSeek-V4-Pro-0813
Qwen3.8-27B
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Pro-0813 and Qwen3.8-27B side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Pro-0813 vs Qwen3.8-27B.