DeepSeek-V4-Flash-0731 vs Qwen3.7-Plus
DeepSeek-V4-Flash-0731 significantly outperforms across most benchmarks. DeepSeek-V4-Flash-0731 is 5.0x cheaper per token.
DeepSeek · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
DeepSeek-V4-Flash-0731 outperforms in 1 benchmarks (NL2Repo), while Qwen3.7-Plus is better at 0 benchmarks. DeepSeek-V4-Flash-0731 significantly outperforms across most benchmarks.
On price, DeepSeek-V4-Flash-0731 is roughly 5.0x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-V4-Flash-0731 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 benchmark, pricing, and model metadata for 2026.
Choose DeepSeek-V4-Flash-0731
- you want the strongest raw capability — it leads on 1 of 1 shared benchmarks
- cost matters — it's about 5.0x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Jul 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.
Performance Benchmarks
Comparative analysis across standard metrics
DeepSeek-V4-Flash-0731 outperforms in 1 benchmarks (NL2Repo), while Qwen3.7-Plus is better at 0 benchmarks.
DeepSeek-V4-Flash-0731 significantly outperforms across most benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4-Flash-0731 ($0.09/1M tokens) is 3.6x cheaper than Qwen3.7-Plus ($0.32/1M tokens).
For output processing, DeepSeek-V4-Flash-0731 ($0.18/1M tokens) is 7.1x cheaper than Qwen3.7-Plus ($1.28/1M tokens).
In conclusion, Qwen3.7-Plus is more expensive than DeepSeek-V4-Flash-0731.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
DeepSeek-V4-Flash-0731 accepts 1,048,576 input tokens compared to Qwen3.7-Plus's 1,000,000 tokens. Both models can generate responses up to 65,536 tokens.
Input Capabilities
Supported data types and modalities
Qwen3.7-Plus supports multimodal inputs, whereas DeepSeek-V4-Flash-0731 does not.
Qwen3.7-Plus can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Flash-0731
Qwen3.7-Plus
License
Usage and distribution terms
DeepSeek-V4-Flash-0731 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-Flash-0731 was released on 2026-07-31, while Qwen3.7-Plus was released on 2026-05-31.
DeepSeek-V4-Flash-0731 is 2 months newer than Qwen3.7-Plus.
Jul 31, 2026
3 weeks ago
2mo newerMay 31, 2026
2 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-Flash-0731 is available from DeepInfra, Novita, Fireworks. Qwen3.7-Plus is available from Together, Fireworks.
DeepSeek-V4-Flash-0731
Qwen3.7-Plus
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-0731 and Qwen3.7-Plus side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Flash-0731 vs Qwen3.7-Plus.