Microsoft Research

40 models across 12 families · Latest: Phi-4 Mini Reasoning (2026-05)

Researched today

Advancing the state-of-the-art in AI and computing.

CodingRAGLong contextVisionClassificationJSON / Tool useBusiness

Microsoft Research's portfolio covers 39 active models across 12 current families, spanning coding, rag, and long context. Open a model detail page to compare provider routes and sourced benchmarks.
Covers 6 workload areas across 39 active tracked models; last verified 2026-09-21.

Use it for

Teams evaluating coding, rag, and long context across this lab's releases
Comparing model families before committing to a flagship
Migration and pricing follow-ups across 39 tracked models

Do not use it for

Choosing a hosting provider without opening a model page for price ladders

Active models

Current models from this lab, excluding deprecated ones

Active families

Current model families from this lab

Open catalog

36 open

34 open source / 2 open weights

Lowest output price

$0.070 /1M

Cheapest tracked output across active models, per 1M tokens

Latest dated release

2026-05-16

Phi-4 Mini Reasoning

Freshness

2026-09-21

Researched today

fresh

Information

Founded1991

Redmond, Washington, United States

Links

Website GitHub X / Twitter LinkedIn HuggingFace Crunchbase

Release cadence

Dated releases: 5
Latest model: Phi-4 Mini Reasoning
Latest date: 2026-05-16

Where this lab wins

Coding: 8 tracked models with SWE-bench / HumanEval-style scores.
RAG: 1 tracked model with ruler / needle retrieval benchmarks.
Long-context: 15 tracked models with context-token or InfiniteBench-class signal.
Vision: 6 tracked models with multimodal benchmark coverage.

Flagship quality / price signal

Flagship: Phi-2
Selection source: Best sourced coding Q/$
Coding grade: A
Benchmark / output price: humaneval 59.7 · $0.070/1M

About

Microsoft Research is a leading research institution that drives innovation in AI and computing. Their work on machine learning, natural language processing, computer vision, and human-computer interaction has led to significant advancements in these fields. Notable contributions include the development of the Microsoft Cognitive Toolkit (CNTK) for deep learning and breakthroughs in conversational AI with the Xiaoice chatbot.