Ministral 3 14B 2512
Ministral 3 14B 2512Alternatives?
CheaperAgnes 2.5 Pro Beta×3.2-25%$0.10 / $0.30
BetterGPT-6 Lunalow×2.8-77%$0.005Function calling only with none · Chat Completions+3
OpenMuse Glimmer 30Bhigh×3.2+196%$0.058Context: 262K → 131K+1
CheaperLing 3.0 Flash VLthinkingOpen×3-55%$0.06 / $0.18Memory (4-bit): 7 GB → 75 GBCheaperGPT-5.6 Lunamedium×2.8-20%$0.016Agnes 2.5 Pro Beta×3.2-25%$0.10 / $0.30Ling 3.0 Flash VLthinkingOpen×3-55%$0.06 / $0.18Memory (4-bit): 7 GB → 75 GBGPT-6 Lunamedium×3-10%$0.017Function calling only with none · Chat Completions+3GPT-5.6 Lunamedium×2.8-20%$0.016
MiMo v2 Omnithinking×2.8-13%$0.14 / $0.28GPT-6 Lunalow×2.8-77%$0.005Function calling only with none · Chat Completions+3
Gemma 4 E4BthinkingOpen+22%-58%$0.008Context: 262K → 128KGPT-5.6 Lunalow×2.7-49%$0.01GPT OSS 20BhighOpen+32%-46%$0.011Context: 262K → 131K+2
Nemotron 3 Nano 30B A3BthinkingOpen+44%-14%$0.017Context: 262K → 131K+2Muse Glimmer 30BhighOpen×3.2+196%$0.058Context: 262K → 131K+1
Qwen3.8 27BxhighOpen×3.1+5,798%$1.15Memory (4-bit): 7 GB → 17 GB+5Qwen 3.5 27BthinkingOpen×2.9+312%$0.30 / $2.40Memory (4-bit): 7 GB → 17 GBQwen3.6 27BthinkingOpen×2.9+3,096%$0.62Memory (4-bit): 7 GB → 17 GBQwen 3.5 9BthinkingOpen×2.7+994%$0.21Mistral Large 4thinking×3.1+8,162%$1.61Infinite whitespace stream+4Mistral Medium 3.5highOpen×2.6+2,105%$0.43Memory (4-bit): 7 GB → 77 GBMistral Small 4thinkingOpen+89%-12%$0.017Memory (4-bit): 7 GB → 72 GBMistral Large 3non-thinkingOpen+37%+60%$0.031Memory (4-bit): not verifiedDevstral Mediumnon-thinkingOpen+22%—$0.40 / $2Context: 262K → 128K+2Ministral 3 8B 2512Opensame-43%$0.011Ministral 3 3B 2512Open-35%-60%$0.008Context: 262K → 131KMagistral Medium 1thinking-100%——Context: 262K → 40K+1All Mistral models →Run it yourself
estimateBenchmarks
in Chat & KnowledgeFAQ
How much does Ministral 3 14B 2512 cost?›
$0.20 per 1M input tokens and $0.20 per 1M output tokens; cached input $0.02 per 1M. A typical benchmark task costs about $0.019 at default effort.
Is Ministral 3 14B 2512 free to use?›
There is no free API; the cheapest paid price is $0.20 per 1M input tokens. The weights are open, so you can run it yourself.
How good is Ministral 3 14B 2512, and what is it best at?›
#290 of 336 in Chat & Knowledge, #77 of 134 in Coding, #120 of 135 in Agents & Tool Use, #87 of 96 in Writing & Language, #112 of 125 in Vision & Documents.
Is Ministral 3 14B 2512 better than Llama 4 Scout?›
On AA-LCR (long context) 1.1, Ministral 3 14B 2512 scores 26.3 vs 27.7 — lower. It is 83% cheaper per task.
How can I use Ministral 3 14B 2512?›
Through the API of Mistral.
What is the context window of Ministral 3 14B 2512?›
262K tokens, with up to 210K output tokens.
When was Ministral 3 14B 2512 released? Is there a newer version?›
Released 2025-12-02. It is the current version in its line.
Is Ministral 3 14B 2512 open source?›
Yes, the weights are open (Apache-2.0 licence).
Can I run Ministral 3 14B 2512 locally?›
The weights are open and can be self-hosted; hardware needs are not confirmed yet.
Can Ministral 3 14B 2512 read images?›
It accepts text and images as input.
What is Ministral 3 14B 2512?›
Ministral 3 14B 2512 is an open-weights language model from Mistral, released Dec 2025.
What are the best alternatives to Ministral 3 14B 2512?›
Agnes 2.5 Pro Beta (cheaper), GPT-6 Luna (better), Muse Glimmer 30B (open weights).