What is MAI-Thinking-1?

MAI-Thinking-1 is Microsoft's first in-house reasoning model, announced at Build 2026 on June 2, 2026. It's a mid-sized sparse Mixture-of-Experts model with 35 billion active parameters out of roughly 1 trillion total, a 256K-token context window, and was trained entirely on commercially licensed data without distillation from OpenAI or any third-party model. It's available in private preview via Microsoft Foundry.

How does MAI-Thinking-1 compare to Claude Opus 4.7 and GPT-5.5?

MAI-Thinking-1 matches Claude Opus 4.6 on SWE-Bench Pro coding benchmarks at a fraction of the computational cost. It's designed for efficiency — a 35B active MoE model competing with models that have far more active parameters. Claude Opus 4.7 still leads on complex reasoning and agentic coding, while GPT-5.5 excels at terminal-coding and long-horizon agent runs. MAI-Thinking-1's main advantage is low-token cost and deep Microsoft ecosystem integration.

Is MAI-Thinking-1 better than GPT-5.5?

In blind tests, independent raters preferred MAI-Thinking-1 over Claude Sonnet 4.6. Direct GPT-5.5 comparisons haven't been published yet. MAI-Thinking-1 wins on cost-efficiency and Microsoft integration (Azure, Copilot, Foundry). GPT-5.5 leads on raw capability and breadth of tooling. For teams already on Azure, MAI-Thinking-1 is compelling. For pure performance, GPT-5.5 and Claude Opus 4.7 remain the benchmarks.

When will MAI-Thinking-1 be generally available?

MAI-Thinking-1 is in private preview via Microsoft Foundry as of June 2, 2026. General availability timeline has not been announced. The model is expected to roll out through Microsoft's existing enterprise channels before wider API access.

Quick Answer

MAI-Thinking-1 vs Claude Opus 4.7 vs GPT-5.5: June 2026 Guide

Published: June 3, 2026

MAI-Thinking-1 vs Claude Opus 4.7 vs GPT-5.5: June 2026 Guide

Microsoft unveiled MAI-Thinking-1 at Build 2026 on June 2, 2026 — its first in-house reasoning model trained entirely without OpenAI data. This guide compares it with the current frontier models from Anthropic and OpenAI.

Last verified: June 3, 2026

TL;DR

Dimension	Winner
Raw reasoning capability	Claude Opus 4.7
Coding benchmarks	GPT-5.5 (Expert-SWE 20h: 73.1%)
Cost efficiency	MAI-Thinking-1 (35B active MoE)
Microsoft ecosystem	MAI-Thinking-1 (Azure, Foundry, Copilot)
Agentic coding	Claude Opus 4.7 (Dynamic Workflows)
Long-horizon tasks	GPT-5.5
Context window	MAI-Thinking-1 (256K) / Claude Opus 4.7 (200K)

Model specifications

Spec	MAI-Thinking-1	Claude Opus 4.7	GPT-5.5
Active params	35B (MoE, ~1T total)	Unknown	Unknown
Context window	256K tokens	200K tokens	128K tokens
Release date	June 2, 2026	April 7, 2026	April 24, 2026
Architecture	Sparse MoE	Transformer	Transformer
Training data	Fully licensed, no distillation	Proprietary	Proprietary
Availability	Private preview (Foundry)	Public (API + Claude)	Public (API + ChatGPT)
Ecosystem	Azure, Microsoft 365, Copilot	Claude, Claude Code	ChatGPT, Codex, API

Key differences

1. Architecture philosophy

MAI-Thinking-1 is a mid-sized reasoning MoE — 35B active parameters out of ~1T total. This is the same architectural pattern DeepSeek V4 uses (MoE with sparse activation), designed to deliver frontier-level reasoning at a fraction of the compute cost.

Claude Opus 4.7 and GPT-5.5 are dense or larger-MoE frontier models. Microsoft deliberately chose a smaller-footprint approach — the model is trained to reason efficiently rather than brute-force through scale.

2. Benchmark performance

Microsoft reports that MAI-Thinking-1 matches Claude Opus 4.6 on SWE-Bench Pro in internal testing. In blind A/B tests, independent raters preferred it over Claude Sonnet 4.6.

Benchmark	MAI-Thinking-1	Claude Opus 4.7	GPT-5.5
SWE-Bench Pro	~Claude Opus 4.6 level	69.2%	58.6%
Blind preference vs Sonnet 4.6	Preferred	N/A	N/A
Expert-SWE 20h	Not published	N/A	73.1%

3. Independence from OpenAI

This is the critical strategic story: MAI-Thinking-1 was trained entirely without OpenAI data. Microsoft has historically relied on OpenAI models for its Copilot stack. MAI-Thinking-1 signals serious in-house capability — built on commercially licensed data, Microsoft’s own infrastructure, and talent from the Inflection AI acquisition.

Pricing comparison

MAI-Thinking-1 pricing hasn’t been finalized, but Microsoft’s positioning as a “low-token cost” model suggests aggressive pricing relative to Claude and GPT.

Model	Input (per 1M tokens)	Output (per 1M tokens)
MAI-Thinking-1	TBD (expected lower)	TBD (expected lower)
Claude Opus 4.7	~$15	~$75
GPT-5.5	~$1.25–$3	~$10–$20

When to use each

Choose MAI-Thinking-1 when:

You’re already on Azure / Microsoft 365
You need strong reasoning at low cost
Model provenance matters (fully licensed data)
You want tight Copilot + Foundry integration

Choose Claude Opus 4.7 when:

Agentic coding is your primary use case (Dynamic Workflows)
You need code review, refactoring, and security audits
Complex multi-file reasoning matters most

Choose GPT-5.5 when:

Long-horizon terminal-coding tasks
You need the widest API tooling ecosystem
Price-performance balance matters (cheaper than Opus)

Bottom line

MAI-Thinking-1 isn’t trying to beat Claude Opus or GPT-5.5 at everything. It’s a strategic model — Microsoft’s first viable independent reasoning engine, optimized for cost and ecosystem integration. For Azure-native teams, it’s a compelling option. For raw frontier performance, Claude Opus 4.7 and GPT-5.5 still lead.