AI model comparison
DeepSeek V4 Flash 0731 vs Qwen3.7 Max
Pricing, context window, benchmarks, and features compared side by side. Or skip the guesswork and send one prompt to both.
DeepSeek
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 is a sparse mixture-of-experts model from DeepSeek, with 13B active parameters out of 284B total.
- Input / 1M
- $0.00
- Output / 1M
- $1.28
- Context
- 1.05M
Qwen
Qwen3.7 Max
Qwen3.7-Max is the flagship model in Alibaba's Qwen3.7 series.
- Input / 1M
- $1.48
- Output / 1M
- $4.43
- Context
- 1M
At a glance
Quick verdict
How the two models stack up on the things people ask about most.
Lower price
DeepSeek V4 Flash 0731
7.9x cheaper for a typical chat
Higher intelligence score
DeepSeek V4 Flash 0731
34.3 vs 29.5 on Artificial Analysis
Larger context window
DeepSeek V4 Flash 0731
1.05M vs 1M tokens
Newer release
DeepSeek V4 Flash 0731
Released July 31, 2026
Benchmarks
Benchmark scores
Independent scores from Artificial Analysis. Higher is better.
Intelligence index
Coding index
Agentic index
Pricing
DeepSeek V4 Flash 0731 vs Qwen3.7 Max API pricing
Per-token API rates. Cheaper option highlighted.
| Metric | ||
|---|---|---|
| Input tokensPer 1M tokens | $0.00 | $1.48 |
| Output tokensPer 1M tokens | $1.28 | $4.43 |
| Cached input (read)Per 1M tokens | $0.00 | $0.30 |
| Cache writePer 1M tokens | Not available | $1.84 |
What it costs in practice
Estimated cost per 1,000 requests at standard rates. Coding and long-document figures also show the cost when the input is already cached.
Chat message
2K in, 500 out
Coding task
30K in, 4K out
Long document summary
150K in, 2K out
Specs
Context window and capabilities
How much each model can read, how much it can write, and what it accepts as input.
| Metric | ||
|---|---|---|
| Context window | 1.05M tokens | 1M tokens |
| Max output | 944K tokens | 131K tokens |
| Input types | Text | Text |
| Output types | Text | Text |
| Reasoning effort levels | Max, High, Low | Not available |
| Default reasoning effort | High | Not available |
| Release date | July 31, 2026 | May 21, 2026 |
Features
Supported features
API features available for each model.
| Metric | ||
|---|---|---|
| Tool calling | Supported | Supported |
| Structured outputs | Supported | Supported |
| JSON mode | Supported | Supported |
| Reasoning | Supported | Supported |
| Temperature | Supported | Supported |
| Stop sequences | Supported | Supported |
| Deterministic seed | Supported | Supported |
| Verbosity control | Not supported | Not supported |
Our take
DeepSeek V4 Flash 0731 is 7.9x cheaper for a typical chat. DeepSeek V4 Flash 0731 scores higher on the Artificial Analysis Intelligence Index (34.3 vs 29.5). DeepSeek V4 Flash 0731 has the larger context window (1.05M vs 1M tokens). The right pick depends on your workload, so the quickest way to settle it is to send the same prompt to both and compare.
FAQ
Frequently asked questions
Is DeepSeek V4 Flash 0731 or Qwen3.7 Max cheaper?
DeepSeek V4 Flash 0731 is cheaper for a typical chat (2K input tokens and 500 output tokens). DeepSeek V4 Flash 0731 costs $0.00 per 1M input tokens and $1.28 per 1M output tokens, while Qwen3.7 Max costs $1.48 per 1M input tokens and $4.43 per 1M output tokens.
Which has a bigger context window, DeepSeek V4 Flash 0731 or Qwen3.7 Max?
DeepSeek V4 Flash 0731 supports up to 1.05M tokens of context, compared with 1M for Qwen3.7 Max.
Is DeepSeek V4 Flash 0731 smarter than Qwen3.7 Max?
On the Artificial Analysis Intelligence Index, DeepSeek V4 Flash 0731 scores 34.3 and Qwen3.7 Max scores 29.5, putting DeepSeek V4 Flash 0731 ahead. Benchmarks don't capture everything, so the best test is running your own prompts through both.
Can I use DeepSeek V4 Flash 0731 and Qwen3.7 Max at the same time?
Yes. Shortcut Chat sends one prompt to multiple models at once, so you can see DeepSeek V4 Flash 0731 and Qwen3.7 Max answer side by side and keep the better response.
Why choose? Ask both.
Send one prompt to DeepSeek V4 Flash 0731 and Qwen3.7 Max at the same time. Compare the answers side by side and keep the best one.