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  5. Bert-Nebulon AlphavsDeepSeek V4 Pro 0813
Updated Aug 2026

Bert-Nebulon AlphavsDeepSeek V4 Pro 0813

DeepSeek V4 Pro 0813 is the newer model, released after Bert-Nebulon Alpha.

Bert-Nebulon Alpha and DeepSeek V4 Pro 0813 compared across 34 shared prompts
SpecBert-Nebulon AlphaDeepSeek V4 Pro 0813
Input price—$0.66/M tokens
Output price—$1.98/M tokens
Context window—1.0M tokens
Weights—Open
Free API (OpenRouter)NoNo
ReleasedNov 2025Aug 2026
Our Verdict
DeepSeek V4 Pro 0813
DeepSeek V4 Pro 0813
Bert-Nebulon Alpha
Bert-Nebulon AlphaRunner-up

Not enough votes to call it. On the specs, DeepSeek V4 Pro 0813 has the edge: bigger model tier, newer, bigger context window, major provider backing.

Slight edge
API pricing

Cost per 1M tokens

Bert-Nebulon Alpha
Input
—
Output
—
DeepSeek V4 Pro 0813
Input
$0.66
Output
$1.98
Where to run it

19 hosts, cheapest first

Bert-Nebulon Alpha

No hosts listed on OpenRouter.

DeepSeek V4 Pro 081319 hosts
HostInOutContextUptime
Baidu Qianfanfp8$0.58 in·$1.74 out·1M·99.9% upAlibaba Cloud$0.58 in·$1.74 out·1M·99.9% upDeepSeek$0.66 in·$1.98 out·1M·100% upSStreamLake$0.66 in·$1.98 out·1M·99.8% upNNovitafp8$0.99 in·$2.97 out·1M·100% upGGMI Cloudfp8$1.06 in·$3.17 out·1M·99.1% up
13 more hostsFewer hosts
IIonstreamfp4$1.10 in·$3.30 out·1M·100% upNNextBitfp8$1.12 in·$3.37 out·1M·99.9% upDDeepInfrafp8$1.30 in·$2.60 out·1M·99.3% upCCoreWeavefp8$1.31 in·$3.96 out·1M·99.9% upBBasetenfp4$1.32 in·$3.96 out·1M·99.9% upCloudflare Workers AI$1.32 in·$3.96 out·1M·99.5% upDDigitalOcean$1.32 in·$3.96 out·1M·99.9% upFFireworks$1.32 in·$3.96 out·1M·99.7% upPParasailfp8$1.32 in·$3.96 out·1M·99.7% upSSail Researchfp4$1.32 in·$3.96 out·1M·99.9% upSSiliconFlowfp8$1.32 in·$3.96 out·1M·100% upTTogether$1.32 in·$3.96 out·1M·99.3% upPPhala$1.45 in·$4.36 out·1M·99.8% up

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

Writing DNA

Style Comparison

Similarity
41%

Bert-Nebulon Alpha uses 42.4x more emoji

Bert-Nebulon Alpha
DeepSeek V4 Pro 0813
55%Vocabulary57%
21wSentence Length17w
0.28Hedging0.49
10.9Bold3.2
5.7Lists3.2
0.42Emoji0.00
1.40Headings1.08
0.04Transitions0.04
Based on 14 + 27 text responses
Research

What we learned reading every model

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