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  5. Claude Opus 4vsDeepSeek V4 Flash
Updated Apr 2026

Claude Opus 4vsDeepSeek V4 Flash

DeepSeek V4 Flash is cheaper than Claude Opus 4 at $0.14/M vs $15/M input tokens.

Claude Opus 4 and DeepSeek V4 Flash compared across 53 shared prompts
SpecClaude Opus 4DeepSeek V4 Flash
Input price$15/M tokens$0.14/M tokens
Output price$75/M tokens$0.28/M tokens
Context window200K tokens1.0M tokens
WeightsClosedOpen
Free API (OpenRouter)NoNo
ReleasedMay 2025Apr 2026
Our Verdict
Claude Opus 4
Claude Opus 4
DeepSeek V4 Flash
DeepSeek V4 Flash

Not enough votes to call it. On the specs, nothing separates them.

DeepSeek V4 Flash costs 268x less per token.

Too close to call
API pricing

Cost per 1M tokens

Claude Opus 4
Input
$15.00
Output
$75.00
DeepSeek V4 Flash
Input
$0.14
107× cheaper
Output
$0.28
268× cheaper

DeepSeek V4 Flash is cheaper on both: 107× input, 268× output.

Where to run it

16 hosts, cheapest first

Claude Opus 41 host
HostInOutContextUptime
Google Vertex AI$15.00 in·$75.00 out·200k·100% up
DeepSeek V4 Flash15 hosts
HostInOutContextUptime
Baidu Qianfanfp8$0.07 in·$0.14 out·1M·98.7% upDDigitalOcean$0.07 in·$0.17 out·1M·99.7% upSStreamLakefp8$0.07 in·$0.14 out·1M·96.8% upDDeepInfrafp8$0.09 in·$0.18 out·1M·99.2% upGGMI Cloudfp8$0.09 in·$0.18 out·1M·99.1% upSSiliconFlowfp8$0.13 in·$0.28 out·1M·99.5% up
9 more hostsFewer hosts
Alibaba Cloudfp8$0.13 in·$0.27 out·1M·92.7% upVVenice$0.14 in·$0.28 out·1M·96.8% upAAtlasCloudfp4$0.14 in·$0.28 out·1M·99.6% upNNovitafp8$0.14 in·$0.28 out·1M·99.9% upPParasailfp8$0.14 in·$0.28 out·1M·99.7% upNNextBitfp8$0.15 in·$0.35 out·1M·99.9% upMMancerfp8$0.19 in·$0.50 out·1M·98% upPPhala$0.20 in·$0.40 out·1M·99.8% upAzure AI Foundry$0.21 in·$0.56 out·1M·93.5% up

Per million tokens. Prices and uptime via OpenRouter, checked 9 Sep 2026.

Writing DNA

Style Comparison

Similarity
26%

Claude Opus 4 uses 118.4x more emoji

Claude Opus 4
DeepSeek V4 Flash
65%Vocabulary54%
57wSentence Length17w
0.67Hedging0.52
3.8Bold3.6
6.8Lists2.6
1.18Emoji0.00
1.42Headings0.41
0.22Transitions0.19
Based on 27 + 27 text responses
Research

What we learned reading every model

FAQ

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