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  5. DeepSeek R1vsDeepSeek V3.2
Updated Dec 2025

DeepSeek R1vsDeepSeek V3.2

DeepSeek V3.2 is cheaper than DeepSeek R1 at $0.28/M vs $0.55/M input tokens.

DeepSeek R1 and DeepSeek V3.2 compared across 54 shared prompts
SpecDeepSeek R1DeepSeek V3.2
Input price$0.55/M tokens$0.28/M tokens
Output price$2.19/M tokens$0.42/M tokens
Context window128K tokens131K tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedFeb 2025Dec 2025
SWE-bench Verified49.2%73.1%
Our Verdict
DeepSeek R1
DeepSeek R1
DeepSeek V3.2
DeepSeek V3.2

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

DeepSeek V3.2 costs 5.2x less per token.

Too close to call
API pricing

Cost per 1M tokens

DeepSeek R1
Input
$0.55
Output
$2.19
DeepSeek V3.2
Input
$0.28
2.0× cheaper
Output
$0.42
5.2× cheaper

DeepSeek V3.2 is cheaper on both: 2.0× input, 5.2× output.

Where to run it

16 hosts, cheapest first

DeepSeek R11 host
HostInOutContextUptime
NNovitafp8$0.70 in·$2.50 out·64k·100% up
DeepSeek V3.215 hosts
HostInOutContextUptime
GGMI Cloudfp8$0.21 in·$0.31 out·164k·100% upSStreamLakefp8$0.21 in·$0.32 out·128k·99.6% upDDigitalOcean$0.25 in·$0.80 out·164k·97.5% upSSiliconFlowfp8$0.26 in·$0.42 out·164k·99.1% upAAtlasCloudfp8$0.26 in·$0.38 out·164k·99.7% upDDeepInfrafp4$0.26 in·$0.38 out·164k·99.5% up
9 more hostsFewer hosts
NNovitafp8$0.27 in·$0.40 out·164k·100% upBaidu Qianfanfp8$0.28 in·$0.42 out·131k·99.9% upVVenice$0.33 in·$0.48 out·160k·99.3% upAlibaba Cloudfp8$0.37 in·$1.11 out·131k·99.6% upFFriendli$0.50 in·$1.50 out·164k·100% upGoogle Vertex AI$0.56 in·$1.68 out·164k·99.1% upPPhala$1.00 in·$1.00 out·164k·99.4% upMMara$3.00 in·$4.50 out·33k·91.6% upSSambaNova$3.00 in·$4.50 out·33k·93.2% up

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

Writing DNA

Style Comparison

Similarity
61%

DeepSeek R1 uses 26.7x more emoji

DeepSeek R1
DeepSeek V3.2
64%Vocabulary54%
15wSentence Length29w
0.48Hedging0.58
7.2Bold5.9
4.9Lists4.8
0.27Emoji0.00
0.57Headings0.74
0.25Transitions0.12
Based on 28 + 28 text responses
Research

What we learned reading every model

FAQ

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