---
tags:
  - mic
  - test-artifact
base_model: MiniMaxAI/MiniMax-M2.5
---

# MiniMax-M2.5-mic

Slim model weights, executable usage and framework expectations in one repository.

- [Contract manifest](integration.json)
- [Transformers usage](integrations/transformers/usage.md)
- [Transformers expectations](integrations/transformers/expectations)
- [Fixture provenance](build.json)
- [How the fixture was shrunk](https://huggingface-mic-mic-coverage.static.hf.space/shrink/MiniMax-M2.5-mic.html)

## Contract

### MiniMax-M2.5 causal LM

Runnable usage and the framework expectations directory are linked above.

## Slim model

### Slim fixture: MiniMax-M2.5-mic

A 25.8M-parameter fixture for the [MiniMaxM2 MIC](https://huggingface.co/huggingface-mic/MiniMax-M2.5-mic), covering [`MiniMaxAI/MiniMax-M2.5`](https://huggingface.co/MiniMaxAI/MiniMax-M2.5). It is a test artifact, not a usable model, tagged `test-artifact` to keep it out of candidate-model search.

- **Fixture key `caec3890e5c1`.** It covers every checkpoint whose processor files are byte-identical and whose config matches after shrinking.
- **Same architecture, smaller config:** `MiniMaxM2ForCausalLM`, shrunk by the generic rule in [`sweep.py`](https://github.com/huggingface/transformers-mic/blob/main/experiments/sweep.py) (num_hidden_layers 2).
- **Processor files copied byte for byte** from `MiniMaxAI/MiniMax-M2.5`: `LICENSE-MODEL`, `chat_template.jinja`, `configuration_minimax_m2.py`, `generation_config.json`, `merges.txt`, `modeling_minimax_m2.py`, `tokenizer.json`, `tokenizer_config.json`, `vocab.json`.
- **Random weights (seed 17).** They passed the input-sensitivity gate: every perturbation of the contract's inputs moved the logits by at least 0.001 (weakest: `input_ids:roll_batch`, 0.635), so no training was needed.
- **Same tensor names as the real checkpoint.** The real checkpoint has every parameter, and so does the fixture.
- **Saved in float32**, the dtype `MiniMaxAI/MiniMax-M2.5` loads in by default.
- **Finite in float32, bfloat16, and float16** (forward, loss, gradients).

Built by [`build_fixtures.py`](https://github.com/huggingface/transformers-mic/blob/main/example/build_fixtures.py); [`build.json`](build.json) records the pinned sources, gate results, and file hashes. This repository includes the slim weights, usage and framework expectations; rebuild the other files with `python example/build_fixtures.py --fixture MiniMax-M2.5-mic`.