DeepSeek-V4-Pro-0813 vs Qwen3.7-Plus
DeepSeek-V4-Pro-0813 leads the LLM Stats Score 52.5 to 42.7. DeepSeek-V4-Pro-0813 is 1.0x cheaper per token.
DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
DeepSeek-V4-Pro-0813 leads the overall LLM Stats Score 52.5 to 42.7, ranking #10 overall.
In the 2 individual benchmarks reported for both models, DeepSeek-V4-Pro-0813 wins 2; 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 2 of 2 exact shared results
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Aug 2026
- you need open weights you can self-host or fine-tune
Choose Qwen3.7-Plus
- you want predictable pricing at $0.32/M input and $1.28/M output
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 · 70 for Qwen3.7-Plus
DeepSeek-V4-Pro-0813 outperforms in 2 benchmarks (Humanity's Last Exam, NL2Repo), while Qwen3.7-Plus is better at 0 benchmarks.
DeepSeek-V4-Pro-0813 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Pro-0813 ($0.43/1M tokens) is 1.4x more expensive than Qwen3.7-Plus ($0.32/1M tokens).
For output processing, DeepSeek-V4-Pro-0813 ($0.87/1M tokens) is 1.5x cheaper than Qwen3.7-Plus ($1.28/1M tokens).
In conclusion, Qwen3.7-Plus is more expensive than DeepSeek-V4-Pro-0813.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
DeepSeek-V4-Pro-0813 accepts 1,048,576 input tokens compared to Qwen3.7-Plus's 1,000,000 tokens. DeepSeek-V4-Pro-0813 can generate longer responses up to 393,216 tokens, while Qwen3.7-Plus is limited to 65,536 tokens.
Input capabilities
Documented input modalities across available providers
Qwen3.7-Plus supports multimodal inputs, whereas DeepSeek-V4-Pro-0813 does not.
Qwen3.7-Plus can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Pro-0813
Qwen3.7-Plus
License
Usage and distribution terms
DeepSeek-V4-Pro-0813 is licensed under MIT, while Qwen3.7-Plus uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-V4-Pro-0813 was released on 2026-08-13, while Qwen3.7-Plus was released on 2026-05-31.
DeepSeek-V4-Pro-0813 is 2 months newer than Qwen3.7-Plus.
Aug 13, 2026
3 weeks ago
2mo newerMay 31, 2026
3 months ago
Knowledge 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. Qwen3.7-Plus is available from Together, Fireworks.
DeepSeek-V4-Pro-0813
Qwen3.7-Plus
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Pro-0813 and Qwen3.7-Plus side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Pro-0813 vs Qwen3.7-Plus.