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  5. Dots3-Note PreviewvsGPT OSS 120B
Updated Aug 2026

Dots3-Note PreviewvsGPT OSS 120B

Dots3-Note Preview is cheaper than GPT OSS 120B at $0/M vs $0.18/M input tokens.

Dots3-Note Preview and GPT OSS 120B compared across 52 shared prompts
SpecDots3-Note PreviewGPT OSS 120B
Input priceFree$0.18/M tokens
Output priceFree$0.8/M tokens
Context window512K tokens131K tokens
Weights—Open
Free API (OpenRouter)Yes (1 provider)No
ReleasedAug 2026Aug 2025
Our Verdict
Dots3-Note Preview
Dots3-Note Preview
GPT OSS 120B
GPT OSS 120B

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

Too close to call
API pricing

Cost per 1M tokens

Dots3-Note Preview
Input
$0.000
Output
$0.000
GPT OSS 120B
Input
$0.18
Output
$0.80
Where to run it

19 hosts, cheapest first

Dots3-Note Preview1 host
HostInOutContextUptime
AAtlasCloudfp8$0 in·$0 out·512k·100% up
GPT OSS 120B18 hosts
HostInOutContextUptime
AAkashMLbf16$0.03 in·$0.17 out·131k·99.9% upCCoreWeavefp4$0.03 in·$0.17 out·131k·99.9% upDDeepInfrabf16$0.04 in·$0.17 out·131k·99.4% upDDigitalOcean$0.06 in·$0.39 out·128k·99.7% upMMancerfp8$0.06 in·$0.50 out·131k·99.6% upGoogle Vertex AI$0.09 in·$0.36 out·131k·99.9% up
12 more hostsFewer hosts
BBasetenfp4$0.10 in·$0.50 out·128k·100% upPParasailfp4$0.10 in·$0.75 out·131k·100% upSSambaNova$0.14 in·$0.95 out·131k·96.9% upAmazon Bedrock$0.15 in·$0.60 out·131k·98.1% upGroq$0.15 in·$0.60 out·131k·100% upNNebiusfp4$0.15 in·$0.60 out·131k·96.2% upTTogether$0.15 in·$0.60 out·131k·98.8% upCCerebrasfp16$0.35 in·$0.75 out·131k·100% upNNovitafp4degraded$0.05 in·$0.25 out·131k·86.7% upSSiliconFlowfp8degraded$0.05 in·$0.45 out·131k·84.3% upPPhaladegraded$0.15 in·$0.60 out·131k·88.8% upMMaradegraded$0.15 in·$0.75 out·131k·86% up

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

Writing DNA

Style Comparison

Similarity
63%

GPT OSS 120B uses 15.4x more emoji

Dots3-Note Preview
GPT OSS 120B
51%Vocabulary52%
17wSentence Length19w
0.60Hedging0.28
4.0Bold7.4
2.9Lists1.8
0.00Emoji0.15
0.55Headings0.73
0.21Transitions0.17
Based on 26 + 21 text responses
Research

What we learned reading every model

FAQ

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