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  5. GPT OSS 20BvsMistral Nemo
Updated Aug 2025

GPT OSS 20BvsMistral Nemo

GPT OSS 20B is cheaper than Mistral Nemo at $0.02/M vs $0.03/M input tokens.

GPT OSS 20B and Mistral Nemo compared across 53 shared prompts
SpecGPT OSS 20BMistral Nemo
Input price$0.02/M tokens$0.03/M tokens
Output price$0.1/M tokens$0.07/M tokens
Context window131K tokens128K tokens
Parameters21B (3.6B active)12B
WeightsOpenOpen
Free API (OpenRouter)NoNo
ReleasedAug 2025Jul 2024
Our Verdict
GPT OSS 20B
GPT OSS 20B
Mistral Nemo
Mistral NemoRunner-up

Not enough votes to call it. On the specs, GPT OSS 20B has the edge: newer, major provider backing.

Too close to call
API pricing

Cost per 1M tokens

GPT OSS 20B
Input
$0.02
1.5× cheaper
Output
$0.10
Mistral Nemo
Input
$0.03
Output
$0.07
1.4× cheaper

GPT OSS 20B wins input (1.5× cheaper)·Mistral Nemo wins output (1.4× cheaper)

Where to run it

16 hosts, cheapest first

GPT OSS 20B12 hosts
HostInOutContextUptime
AAkashMLfp4$0.02 in·$0.10 out·131k·92.3% upDDarkbloomfp8$0.02 in·$0.10 out·131k·99.7% upCCoreWeavefp4$0.03 in·$0.13 out·131k·100% upDDeepInfrabf16$0.03 in·$0.14 out·131k·100% upPParasailfp4$0.03 in·$0.15 out·131k·99.9% upNNovitafp4$0.04 in·$0.15 out·131k·99.9% up
6 more hostsFewer hosts
PPhala$0.04 in·$0.15 out·131k·100% upSSiliconFlowfp8$0.04 in·$0.18 out·131k·97.2% upTTogether$0.05 in·$0.20 out·131k·96.9% upAmazon Bedrock$0.07 in·$0.15 out·131k·99.9% upGoogle Vertex AI$0.07 in·$0.25 out·131k·99.7% upGroq$0.07 in·$0.30 out·131k·99.8% up
Mistral Nemo4 hosts
HostInOutContextUptime
DDeepInfrafp8$0.02 in·$0.03 out·131k·100% upIio.netfp16$0.04 in·$0.16 out·128k·93.4% upPParasailfp8degraded$0.03 in·$0.03 out·131k·99% upNNovitafp8degraded$0.04 in·$0.17 out·60k·70.9% up

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

Writing DNA

Style Comparison

Similarity
38%

GPT OSS 20B uses 10.2x more emoji

GPT OSS 20B
Mistral Nemo
54%Vocabulary53%
17wSentence Length17w
0.26Hedging0.72
5.9Bold2.9
3.3Lists5.1
0.10Emoji0.00
0.75Headings0.00
0.32Transitions0.14
Based on 21 + 27 text responses
Research

What we learned reading every model

FAQ

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