DeepSeek V4 FlashvsQwen Plus 0728 (thinking)
DeepSeek V4 Flash is cheaper than Qwen Plus 0728 (thinking) at $0.14/M vs $0.4/M input tokens.
| Spec | DeepSeek V4 Flash | Qwen Plus 0728 (thinking) |
|---|---|---|
| Input price | $0.14/M tokens | $0.4/M tokens |
| Output price | $0.28/M tokens | $4/M tokens |
| Context window | 1.0M tokens | 1.0M tokens |
| Weights | Open | — |
| Free API (OpenRouter) | No | No |
| Released | Apr 2026 | Sep 2025 |
Our Verdict
DeepSeek V4 Flash
Qwen Plus 0728 (thinking)Runner-up
Not enough votes to call it. On the specs, DeepSeek V4 Flash has the edge: newer, major provider backing.
DeepSeek V4 Flash costs 14x less per token.
Too close to call
Reviewing agent-written code?See a Brief PR report
API pricing
Cost per 1M tokens
DeepSeek V4 Flash
Input
$0.14
2.9× cheaper
Output
$0.28
14× cheaper
Qwen Plus 0728 (thinking)
Input
$0.40
Output
$4.00
DeepSeek V4 Flash is cheaper on both: 2.9× input, 14× output.
Where to run it
17 hosts, cheapest first
DeepSeek V4 Flash17 hosts
OpenInferencefp8$0.05 in$0.12 out1M93.9% upStreamLakefp8$0.07 in$0.13 out1M98.8% upBaidu Qianfanfp8$0.07 in$0.13 out1M100% upDigitalOcean$0.07 in$0.17 out1M99.9% upDeepInfrafp8$0.09 in$0.18 out1M99.4% upGMI Cloudfp8$0.09 in$0.18 out1M99.8% up
11 more hostsFewer hosts
Venice$0.10 in$0.19 out1M99.2% upWafer$0.10 in$0.25 out1M100% upSiliconFlowfp8$0.13 in$0.28 out1M99.6% upAlibaba Cloudfp8$0.13 in$0.27 out1M99.8% upAtlasCloudfp4$0.14 in$0.28 out1M99.9% upNovitafp8$0.14 in$0.28 out1M100% upParasailfp8$0.14 in$0.28 out1M99.9% upNextBitfp8$0.15 in$0.35 out1M99.9% upMancerfp8$0.19 in$0.50 out1M97.6% upPhala$0.20 in$0.40 out1M100% upAzure AI Foundry$0.21 in$0.56 out1M98.6% up
Qwen Plus 0728 (thinking)
No hosts listed on OpenRouter.
Per million tokens. Prices and uptime via OpenRouter, checked 13 Sep 2026.
Writing DNA
Style Comparison
Similarity
37%
Qwen Plus 0728 (thinking) uses 34.0x more emoji
DeepSeek V4 Flash
Qwen Plus 0728 (thinking)
54%Vocabulary54%
17wSentence Length15w
0.52Hedging0.36
3.6Bold7.0
2.6Lists4.6
0.00Emoji0.34
0.41Headings0.94
0.19Transitions0.09
Based on 27 + 18 text responses
Research
What we learned reading every model
FAQ
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