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  5. DeepSeek V3 (March 2024)vsMiniMax M3
Updated Jun 2026

DeepSeek V3 (March 2024)vsMiniMax M3

DeepSeek V3 (March 2024) is cheaper than MiniMax M3 at $0.14/M vs $0.3/M input tokens.

DeepSeek V3 (March 2024) and MiniMax M3 compared across 53 shared prompts
SpecDeepSeek V3 (March 2024)MiniMax M3
Input price$0.14/M tokens$0.3/M tokens
Output price$0.28/M tokens$1.2/M tokens
Context window128K tokens1.0M tokens
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedMar 2024Jun 2026
Our Verdict
DeepSeek V3 (March 2024)
DeepSeek V3 (March 2024)
MiniMax M3
MiniMax M3

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

DeepSeek V3 (March 2024) costs 4.3x less per token.

Too close to call
API pricing

Cost per 1M tokens

DeepSeek V3 (March 2024)
Input
$0.14
2.1× cheaper
Output
$0.28
4.3× cheaper
MiniMax M3
Input
$0.30
Output
$1.20

DeepSeek V3 (March 2024) is cheaper on both: 2.1× input, 4.3× output.

Where to run it

16 hosts, cheapest first

DeepSeek V3 (March 2024)4 hosts
HostInOutContextUptime
DDeepInfrafp4$0.24 in·$0.90 out·164k·91.8% upSSiliconFlowfp8$0.25 in·$1.00 out·164k·95.4% upGGMI Cloudfp8$0.29 in·$1.14 out·164k·97.1% upCCrusoebf16$0.50 in·$1.50 out·164k·100% up
MiniMax M312 hosts
HostInOutContextUptime
CCoreWeavefp4$0.23 in·$0.96 out·262k·99.9% upGGMI Cloudfp8$0.24 in·$0.96 out·1M·98.4% upDDeepInfrafp8$0.28 in·$1.10 out·524k·98.9% upAAtlasCloudfp8$0.30 in·$1.20 out·524k·31.1% upMiniMaxfp8$0.30 in·$1.20 out·524k·99.7% upNNovitafp8$0.30 in·$1.20 out·1M·99.4% up
6 more hostsFewer hosts
PParasailfp8$0.30 in·$1.20 out·1M·98.2% upSStreamLakefp8$0.30 in·$1.20 out·1M·99.1% upTTogether$0.30 in·$1.20 out·524k·99.8% upVVenicefp8$0.30 in·$1.20 out·524k·99.9% upSSambaNova$0.60 in·$2.40 out·1M·98.4% upMModelRunfp4$0.75 in·$3.00 out·1M·99.3% up

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

Writing DNA

Style Comparison

Similarity
54%

DeepSeek V3 (March 2024) uses 3.9x more transitions

DeepSeek V3 (March 2024)
MiniMax M3
60%Vocabulary55%
20wSentence Length24w
0.71Hedging0.52
6.7Bold5.2
5.8Lists3.0
0.59Emoji1.15
1.29Headings1.21
0.09Transitions0.02
Based on 28 + 27 text responses
Research

What we learned reading every model

FAQ

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