---
license: apache-2.0
library_name: transformers
base_model:
  - mistralai/Mistral-Small-3.2-24B-Instruct-2506
  - mistralai/Magistral-Small-2509
tags:
  - merge
  - mergekit
  - slerp
  - mistral
  - reasoning
  - 24b
language:
  - en
  - fr
  - de
  - es
  - it
  - pt
  - zh
  - ja
  - ko
  - ar
---

# Taipei 2

A 50/50 SLERP merge of `Mistral-Small-3.2-24B-Instruct-2506` and `Magistral-Small-2509`, both 24B Mistral-3 architecture models sharing the same base. This has resulted in our best model, Taipei 3.1

The goal: combine the conversational polish, tool-calling reliability, and low-latency response style of Mistral Small 3.2 with the explicit reasoning capability (SFT + RL on Magistral Medium traces) of Magistral Small 1.2. The merged model retains the `[THINK]/[/THINK]` reasoning tokens from Magistral via `tokenizer_source: union`, so it can operate in either fast-response or deep-reasoning mode depending on system prompt.

## Use

Works with vLLM, transformers, and llama.cpp (after GGUF conversion). Use Magistral's system prompt format to enable reasoning traces; use a standard Mistral system prompt for fast chat.

## Tokenizer

This repo ships Mistral's canonical `tekken.json` rather than a serialized HF `tokenizer.json`. transformers' `AutoTokenizer.from_pretrained` auto-converts it on load. For best fidelity in production, use [`mistral-common`](https://github.com/mistralai/mistral-common) or vLLM, which read tekken directly. The `[THINK]` / `[/THINK]` reasoning tokens are preserved (ranks 34 / 35).

## Merge config

```yaml
merge_method: slerp
base_model: mistralai/Mistral-Small-3.2-24B-Instruct-2506
slices:
  - sources:
      - model: mistralai/Mistral-Small-3.2-24B-Instruct-2506
        layer_range: [0, 40]
      - model: mistralai/Magistral-Small-2509
        layer_range: [0, 40]
parameters:
  t:
    - filter: self_attn
      value: [0, 0.5, 0.3, 0.7, 1]
    - filter: mlp
      value: [1, 0.5, 0.7, 0.3, 0]
    - value: 0.5
embed_slerp: true
dtype: bfloat16
tokenizer_source: union
```

Part of the Tripplet Taipei model series.