# Ministral-3-14B-Base-2512 [Canonical model page](https://headlessthrones.com/models/mistral-ai-ministral-3-14b-base-2512) · [Model library](https://headlessthrones.com/models) Public catalog reference from Headless Thrones. Exact catalog ID: `mistral-ai-ministral-3-14b-base-2512`. Catalog source-check date: 2026-10-23. This brief contains the public catalog answers and any catalog guide, not private drafts, historical editorial revisions or independently measured rankings. The canonical HTML page may also display separately published editorial. Current catalog answers ## What to know about Ministral-3-14B-Base-2512 AI-compiled from linked model documentation. This is a catalog reference, not an independent performance review. Catalog checked October 23, 2026. [Exact model](https://headlessthrones.com/models/mistral-ai-ministral-3-14b-base-2512#model-answer-identity) · [Access](https://headlessthrones.com/models/mistral-ai-ministral-3-14b-base-2512#model-answer-access) · [Token limits](https://headlessthrones.com/models/mistral-ai-ministral-3-14b-base-2512#model-answer-context) · [Inputs & outputs](https://headlessthrones.com/models/mistral-ai-ministral-3-14b-base-2512#model-answer-modalities) · [License](https://headlessthrones.com/models/mistral-ai-ministral-3-14b-base-2512#model-answer-license) · [Model details](https://headlessthrones.com/models/mistral-ai-ministral-3-14b-base-2512#model-answer-research) · [Weight details](https://headlessthrones.com/models/mistral-ai-ministral-3-14b-base-2512#model-answer-repository) ### Which Ministral-3-14B-Base-2512 does this page describe? Ministral-3-14B-Base-2512 is a model record from **Mistral AI** in the Ministral family. [Source](https://huggingface.co/mistralai/Ministral-3-14B-Base-2512) A separate version identifier is not documented in this record; the model name alone does not establish which snapshot a service runs. ### How can you access Ministral-3-14B-Base-2512? The catalog documents **Open weights** access for Ministral-3-14B-Base-2512. [Source](https://huggingface.co/mistralai/Ministral-3-14B-Base-2512) As of the catalog check, this version was listed without confirmed general availability. [Source](https://huggingface.co/mistralai/Ministral-3-14B-Base-2512) Open weights means the model weights are distributed for use under their stated terms. It does not establish a hosted API, an open-source license, or a hardware requirement. ### What are Ministral-3-14B-Base-2512's context and output limits? The publisher reports the context window as **256k tokens**. [Source](https://huggingface.co/mistralai/Ministral-3-14B-Base-2512/resolve/5b0ceedbb42dff466ae60b258ba296f32da51384/README.md) We retain the publisher's notation and qualifiers; no exact token count or hosted serving allowance is inferred from it. A separate maximum-output value is not established in this record. The context or input figure should not be used as an output allowance. Context, input and output limits describe different constraints. Do not add the figures together to infer a larger window. Check the endpoint's accounting for conversation history, system instructions, tools, media and generated tokens; a documented maximum is not a guarantee of answer quality or a measured usable capacity. ### What can Ministral-3-14B-Base-2512 receive and generate? Documented inputs: **Text and Image**. [Source](https://huggingface.co/mistralai/Ministral-3-14B-Base-2512/resolve/5b0ceedbb42dff466ae60b258ba296f32da51384/README.md) Input support and output generation are separate capabilities. Reading an image does not establish image generation; a text output listing does not establish speech output. File sizes, formats and media limits depend on the documented implementation. ### What license is recorded for Ministral-3-14B-Base-2512? The recorded license label is **apache-2.0**. [Source](https://huggingface.co/mistralai/Ministral-3-14B-Base-2512) Read the linked license and associated use terms for this exact version before redistribution, commercial deployment or fine-tuning. A label alone does not establish every permission, restriction or obligation, and it does not determine the terms of a separate hosted service. ### What distinguishes Ministral-3-14B-Base-2512? These details come from the linked publisher material for this model. Reported capabilities and training descriptions are publisher statements, not independent test results. **Checkpoint training stage**: Pretrained base checkpoint, without instruction or reasoning post-training. [Source](https://huggingface.co/mistralai/Ministral-3-14B-Base-2512/resolve/5b0ceedbb42dff466ae60b258ba296f32da51384/README.md) **Nominal model components**: 13.5B language model plus 0.4B vision encoder. [Source](https://huggingface.co/mistralai/Ministral-3-14B-Base-2512/resolve/5b0ceedbb42dff466ae60b258ba296f32da51384/README.md) **Context window as documented**: Publisher documents a 256k-token context window. [Source](https://huggingface.co/mistralai/Ministral-3-14B-Base-2512/resolve/5b0ceedbb42dff466ae60b258ba296f32da51384/README.md) **Publisher deployment guidance**: Publisher deployment estimate: 32GB VRAM at BF16, or under 24GB RAM/VRAM when quantized. Actual needs also depend on context and runtime. [Source](https://huggingface.co/mistralai/Ministral-3-14B-Base-2512/resolve/5b0ceedbb42dff466ae60b258ba296f32da51384/README.md) ### What is documented about the Ministral-3-14B-Base-2512 checkpoint? This evidence refers to `mistralai/Ministral-3-14B-Base-2512` at recorded revision `5b0ceedbb42dff466ae60b258ba296f32da51384`, checked October 23, 2026. [Repository metadata](https://huggingface.co/api/models/mistralai/Ministral-3-14B-Base-2512) Safetensors metadata records **13,945,031,680 stored parameters**. This is a stored-weight count, not necessarily the number activated per token, a download size or a GPU-memory requirement. [Repository metadata](https://huggingface.co/api/models/mistralai/Ministral-3-14B-Base-2512) Recorded architecture class: `Mistral3ForConditionalGeneration`. [Repository metadata](https://huggingface.co/api/models/mistralai/Ministral-3-14B-Base-2512) Listed library: `vllm`. Check that library's version and model support before loading the weights. [Repository metadata](https://huggingface.co/api/models/mistralai/Ministral-3-14B-Base-2512) Repository language labels: en, fr, es, de, it, pt, nl, zh, ja, ko, and ar. These labels are not independent evaluations of language quality. [Repository metadata](https://huggingface.co/api/models/mistralai/Ministral-3-14B-Base-2512) Repository access gate: `false`. This records the repository's gate setting when checked; licensing and use terms still apply. [Repository metadata](https://huggingface.co/api/models/mistralai/Ministral-3-14B-Base-2512) #### What the configuration file says The pinned `config.json` section `text_config` contains these values. [Pinned configuration](https://huggingface.co/mistralai/Ministral-3-14B-Base-2512/resolve/5b0ceedbb42dff466ae60b258ba296f32da51384/config.json) `max_position_embeddings`: 262,144 `torch_dtype`: bfloat16 `num_attention_heads`: 32 `num_key_value_heads`: 8 `num_hidden_layers`: 40 `hidden_size`: 5,120 Configuration values describe the checkpoint and its implementation. In particular, max\_position\_embeddings, sliding\_window and rope\_scaling do not independently establish an API context limit, tested usable length or hardware requirement. Runtime, quantization, cache, batch size and input length affect deployment behavior. Read the retrieved model card for setup and qualifications. [Model card](https://huggingface.co/mistralai/Ministral-3-14B-Base-2512/resolve/5b0ceedbb42dff466ae60b258ba296f32da51384/README.md) **Catalog qualifications:** Official publisher model repository; listed status confirms a catalog entry, not a verified hosted API service. [Source 1](https://huggingface.co/api/models/mistralai/Ministral-3-14B-Base-2512) · [Source 2](https://huggingface.co/mistralai/Ministral-3-14B-Base-2512/resolve/5b0ceedbb42dff466ae60b258ba296f32da51384/README.md) · [Source 3](https://huggingface.co/mistralai/Ministral-3-14B-Base-2512/resolve/5b0ceedbb42dff466ae60b258ba296f32da51384/config.json) **Evidence still missing here:** knowledge and training-data cutoffs and tested hardware requirements. Missing documentation is not evidence that a feature is unavailable. Headless Thrones has not independently benchmarked this model for this reference. Evaluate it on representative work before choosing it; these facts do not rank its accuracy, reliability, speed or suitability against another model. Keep the exact version in view ## Other Ministral models from Mistral AI. These are separate records in the same publisher family. A shared family name does not establish equal capabilities or interchangeable licenses. ### [Ministral-3-14B-Instruct-2512](https://headlessthrones.com/models/mistral-ai-ministral-3-14b-instruct-2512) API · Open weights · 256,000 context tokens ### [Ministral-3-3B-Instruct-2512](https://headlessthrones.com/models/mistral-ai-ministral-3-3b-instruct-2512) API · Open weights · 256,000 context tokens ### [Ministral-3-8B-Instruct-2512](https://headlessthrones.com/models/mistral-ai-ministral-3-8b-instruct-2512) API · Open weights · 256,000 context tokens ### [Ministral 3B](https://headlessthrones.com/models/mistral-ai-ministral-3b-24-1) API · 128,000 context tokens ### [Ministral-8B-Instruct-2410](https://headlessthrones.com/models/mistral-ai-ministral-8b-instruct-2410) API · Open weights · 128,000 context tokens ### [Ministral-3-14B-Reasoning-2512](https://headlessthrones.com/models/mistral-ai-ministral-3-14b-reasoning-2512) Open weights