DeepSeek V4 ProvsQwen3 30B A3B Thinking 2507
Qwen3 30B A3B Thinking 2507 is cheaper than DeepSeek V4 Pro at $0.071/M vs $1.74/M input tokens.
| Spec | DeepSeek V4 Pro | Qwen3 30B A3B Thinking 2507 |
|---|---|---|
| Input price | $1.74/M tokens | $0.071/M tokens |
| Output price | $3.48/M tokens | $0.285/M tokens |
| Context window | 1.0M tokens | 262K tokens |
| Weights | Open | Open |
| Free API (OpenRouter) | No | No |
| Released | Apr 2026 | Aug 2025 |
Our Verdict
DeepSeek V4 Pro
Qwen3 30B A3B Thinking 2507Runner-up
Not enough votes to call it. On the specs, DeepSeek V4 Pro has the edge: bigger model tier, newer, bigger context window, major provider backing.
Qwen3 30B A3B Thinking 2507 costs 12x less per token.
Slight edge
Reviewing agent-written code?See a Brief PR report
API pricing
Cost per 1M tokens
DeepSeek V4 Pro
Input
$1.74
Output
$3.48
Qwen3 30B A3B Thinking 2507
Input
$0.07
25× cheaper
Output
$0.28
12× cheaper
Qwen3 30B A3B Thinking 2507 is cheaper on both: 25× input, 12× output.
Where to run it
15 hosts, cheapest first
DeepSeek V4 Pro14 hosts
StreamLakefp8$0.65 in$1.29 out1M98.6% upBaidu Qianfanfp8$0.66 in$1.31 out1M100% upDigitalOcean$0.87 in$1.74 out1M100% upGMI Cloudfp8$0.96 in$1.91 out1M99.7% upDeepInfrafp8$1.30 in$2.60 out1M99.5% upAlibaba Cloudfp8$1.42 in$2.83 out1M100% up
8 more hostsFewer hosts
SiliconFlowfp8$1.50 in$3.13 out1M98.4% upNovitafp8$1.60 in$3.20 out1M100% upVenice$1.65 in$3.30 out1M98.4% upAtlasCloudfp4$1.68 in$3.38 out1M99.3% upBasetenfp4$1.74 in$3.48 out1M99.8% upParasailfp8$1.74 in$3.48 out1M99.8% upAzure AI Foundry$1.91 in$3.83 out1M99.3% upNextBitfp8$2.00 in$4.00 out1M99.9% up
Qwen3 30B A3B Thinking 25071 host
Per million tokens. Prices and uptime via OpenRouter, checked 13 Sep 2026.
Writing DNA
Style Comparison
Similarity
33%
Qwen3 30B A3B Thinking 2507 uses 25.5x more emoji
DeepSeek V4 Pro
Qwen3 30B A3B Thinking 2507
57%Vocabulary52%
18wSentence Length15w
0.52Hedging0.20
3.3Bold7.0
2.3Lists4.2
0.04Emoji0.89
0.45Headings0.91
0.15Transitions0.10
Based on 27 + 28 text responses
Research
What we learned reading every model
FAQ
Common questions
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