# Mistral Small 4 — One MoE Unifies Reasoning, Vision and Coding

Times of AI Desk · 2026-03-16 · Models

[https://timesof.ai/2026/03/mistral-small-4-unified-multimodal-reasoning-model](https://timesof.ai/2026/03/mistral-small-4-unified-multimodal-reasoning-model)

> Mistral Small 4 (March 16): 119B MoE (6B active/token, 8B with emb/out), 256k context, Apache 2.0 — unifies reasoning (Magistral), vision (Pixtral), agentic coding (Devstral) with configurable reasoning_effort. Claims 40% lower latency / 3× throughput vs Small 3; AA LCR/LiveCodeBench vs GPT-OSS 120B are lab/partner — vendor-reported.

Open-weight shops usually ship a zoo. Mistral’s proprietary move with **Small 4**: **one Apache 2.0 MoE** that absorbs Magistral reasoning, Pixtral vision, and Devstral coding — plus a **reasoning_effort** dial instead of three endpoints.

**Mistral AI** (March 16) released **Small 4**: hybrid MoE, **119B** total parameters, **6B** active per token (**8B** including embeddings and output), **256k** context, text+image. `reasoning_effort`: **none** (fast, prior Small-like) vs **high** (Magistral-class step-by-step). Company: **40%** lower end-to-end latency in optimized setups and **3×** throughput vs Mistral Small 3; on AA LCR and LiveCodeBench with reasoning, matches/exceeds larger opens such as GPT-OSS 120B while producing **3.5–4×** fewer characters than the cited Qwen models on AA LCR and **20%** less output than GPT-OSS 120B on LiveCodeBench. Available via Mistral API, AI Studio, Hugging Face; NVIDIA NIM; optimized for vLLM, SGLang, Transformers, llama.cpp. Mistral joined **NVIDIA Nemotron Coalition** as founding member.

## Claims vs checks

Architecture, license, and availability are **Mistral primary**. Latency/throughput and bench comparisons are **vendor/partner**. The vendor/partner results alone do not establish an independent open-weight ranking.

## Limits

- “Unified” still means MoE routing quality varies by task.
- Shorter outputs can help cost but are not automatically better answers.
- Coalition membership ≠ shared training compute guarantees.

**Correction and source review — October 14, 2026:** Specified which output-length comparison applies to Qwen on AA LCR and which applies to GPT-OSS 120B on LiveCodeBench.

## Sources

- [Mistral AI: “Introducing Mistral Small 4”](https://mistral.ai/news/mistral-small-4) (March 16, 2026).