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  5. DeepSeek V4 ProvsKimi K2 0905
Updated Apr 2026

DeepSeek V4 ProvsKimi K2 0905

Kimi K2 0905 is cheaper than DeepSeek V4 Pro at $0.6/M vs $1.74/M input tokens.

DeepSeek V4 Pro and Kimi K2 0905 compared across 54 shared prompts
SpecDeepSeek V4 ProKimi K2 0905
Input price$1.74/M tokens$0.6/M tokens
Output price$3.48/M tokens$2.5/M tokens
Context window1.0M tokens262K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedApr 2026Sep 2025
Our Verdict
DeepSeek V4 Pro
DeepSeek V4 Pro
Kimi K2 0905
Kimi K2 0905Runner-up

Not enough votes to call it. On the specs, DeepSeek V4 Pro has the edge: newer, bigger context window, major provider backing.

Too close to call
API pricing

Cost per 1M tokens

DeepSeek V4 Pro
Input
$1.74
Output
$3.48
Kimi K2 0905
Input
$0.60
2.9× cheaper
Output
$2.50
1.4× cheaper

Kimi K2 0905 is cheaper on both: 2.9× input, 1.4× output.

Where to run it

16 hosts, cheapest first

DeepSeek V4 Pro15 hosts
HostInOutContextUptime
DDigitalOcean$0.87 in·$1.74 out·1M·98.8% upSStreamLakefp8$0.95 in·$1.89 out·1M·98.9% upBaidu Qianfanfp8$0.95 in·$1.90 out·1M·99.3% upGGMI Cloudfp8$0.96 in·$1.91 out·1M·96.8% upDDeepInfrafp8$1.30 in·$2.60 out·1M·99.3% upAlibaba Cloudfp8$1.42 in·$2.83 out·1M·99.9% up
9 more hostsFewer hosts
SSiliconFlowfp8$1.50 in·$3.13 out·1M·98.3% upNNovitafp8$1.60 in·$3.20 out·1M·100% upVVenice$1.65 in·$3.30 out·1M·97.1% upAAtlasCloudfp4$1.68 in·$3.38 out·1M·97.4% upBBasetenfp4$1.74 in·$3.48 out·1M·99.6% upPParasailfp8$1.74 in·$3.48 out·1M·99.4% upNNextBitfp8$1.80 in·$3.55 out·1M·99.8% upAzure AI Foundry$1.91 in·$3.83 out·1M·98.9% upFFireworksdegraded$1.20 in·$1.20 out·1M·0% up
Kimi K2 09051 host
HostInOutContextUptime
NNovitafp8$0.60 in·$2.50 out·262k·100% up

Per million tokens. Prices and uptime via OpenRouter, checked 8 Sep 2026.

Writing DNA

Style Comparison

Similarity
54%

Kimi K2 0905 uses 3.3x more emoji

DeepSeek V4 Pro
Kimi K2 0905
57%Vocabulary65%
18wSentence Length21w
0.52Hedging0.16
3.3Bold2.8
2.3Lists3.0
0.04Emoji0.11
0.45Headings0.69
0.15Transitions0.06
Based on 27 + 28 text responses
Research

What we learned reading every model

FAQ

Common questions

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