Ministral 3 14B 2512
5506°
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Mistral | 262,144 token context | $0.20/M input, $0.20/M output. The largest model in the Ministral 3 family, Ministral 3 14B offers frontier capabilities and performance comparable to its larger Mistral Small 3.2 24B counterpart. A powerful and efficient language model with vision capabilities.
Guides for this model
Ollama vs LM Studio (2026): which local AI app to use, and which top models each one runs
How much VRAM do I actually need for local AI?
What is a GGUF file? Quantized models explained (Q4, Q8, fp8, NF4)
Captain's notes
Notes from 2026-10-13
Ministral 3 14B 2512 is Mistral's largest edge-optimised model, pairing a 13.5B language model with a 0.4B vision encoder to deliver performance Mistral claims is comparable to its Mistral Small 3.2 24B. It ships under Apache 2.0, fits in 24 GB of VRAM at FP8, and brings native function calling, a 256 k-token context and multilingual support to hardware that would choke on bigger models.
Known for
- Fits in 24 GB VRAM at FP8; quantise further for tighter hardware
- Native function calling and JSON output for agentic pipelines
- Vision encoder handles image analysis alongside text
- 256 k-token context window for long documents
- Apache 2.0 licence: commercial use, fine-tuning, modification all permitted
Watch out for
- FP8 weights only in the instruct version; base models in the family use BF16
- Vision quality degrades with very wide or narrow images — crop to near 1:1 before sending
- Mistral recommends temperature below 0.1 for production; higher values need careful testing
Prompts to try
Agentic tool-use plan
You have two tools: search_web(query: str) and send_email(to: str, subject: str, body: str). A user asks: 'Find the current CEO of Mistral AI and send me a summary email at user@example.com.' Write the exact sequence of tool calls you would make, with arguments, and explain your reasoning between each step.
Describe an attached image
Attach a photo of any product, document or scene. Describe what you see in detail: identify the main subject, read any visible text, note colours and layout, and suggest two ways this image could be used in a marketing context.
Multilingual contract clause
Translate the following clause into French, Spanish, German and Japanese, keeping legal register intact. Then flag any term that may not have a direct legal equivalent in one of those languages and suggest a local alternative: 'The licensor grants a non-exclusive, royalty-free, worldwide licence to use, reproduce and distribute the software in source or binary form.'
Compare with
- Mistral Large 4API-only model1,048,576 token context · $0.68/M input, $2.09/M output
- Mistral Medium 3.5API-only model262,144 token context · $1.50/M input, $7.50/M output
- Mistral Large 3 2512API-only model262,144 token context · $0.50/M input, $1.50/M output
- Mistral Large 2407API-only model131,072 token context · $2.00/M input, $6.00/M output
More text models from mistralai
Questions people ask
- Can I run Ministral 3 14B locally?
- Yes — the weights are open under Apache 2.0 and available on Hugging Face. The FP8 instruct model fits in 24 GB of VRAM, and quantised versions will run on less.
- What does it cost via API, and how long is the context?
- Mistral prices it at $0.20 per million tokens for both input and output, with a 262,144-token context window.
- How does it compare to Mistral Small 3.2 24B?
- Mistral says performance is comparable despite the smaller parameter count, making the 14B the better choice when you need to stay within tighter memory or cost constraints.
Captain's verdictA rare edge model that takes vision, long context and agents seriously — worth running locally if you have a 24 GB card.
Model card on Hugging Face
Captain writes these notes from the model's own description and model card. Prices and context sizes are the provider's at the time of writing and can change.
Ranking badge
Updated Oct 22, 2026
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How this score adds up
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Glossary: the terms used here
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- Download-equivalents
- Everything the score treats as a download, added up: downloads themselves, each torrent seeder as 1,000, each AI Horde image and each run on a generation site as one.
- Log scale
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- Seeder
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- Full model (checkpoint)
- The weights themselves, the file that generates on its own. It gets a bonus because add-ons depend on it.
- LoRA and embedding
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- Family boost
- A small, bounded nudge for LoRAs of a family this site is pushing forward right now, always listed in the breakdown.
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- A stable number below the floor given to a model no source reports on yet, so lists stay complete. It never ranks above a model with data.
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- Trend
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- Typical model
- The middle of the catalog: half the models with a figure grew faster over the period, half slower.
Ministral 3 14B 2512 is a text model for the Text / LLM family listed on ModelTrends.ai, a read-only catalog of open source AI image, video and text models. Compare it with other Text / LLM models and check its heat score to see how it is trending.
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