AIREITERMAI-Thinking-1 entered public preview on Microsoft Foundry on August 12, 2026 — Microsoft's first reasoning model built entirely from scratch, a 35B-active / ~1T-total sparse MoE with a 256K context window. The headline claim is competitive math and coding performance at a fraction of the inference footprint, but the numbers tell a more nuanced story: it matches Claude Opus 4.6 on SWE-Bench Pro (52.8% vs 53.4%) yet trails badly on Terminal-Bench 2.0 (46.0% vs GPT-5.4's 75.1%), and Microsoft has not published per-token pricing despite repeated "mid-weight price" promises.
What MAI-Thinking-1 Is
MAI-Thinking-1 is a sparse Mixture-of-Experts reasoning model with 35 billion active parameters out of approximately 1 trillion total, developed entirely in-house at Microsoft AI. The technical report specifies 34.7B active / 962B total for the base model, with 78 layers and 8 selected experts out of 512 per routed token. The context window is 256,000 tokens — roughly 600 pages of text — which puts it in the same range as Claude Sonnet 4.6 and GPT-5.4.
On the API side, MAI-Thinking-1 supports the widely used Chat Completions API format, along with function calling, developer instructions, and structured output. This means existing code targeting OpenAI's chat endpoints can be adapted with minimal changes. It is text-only — no vision, audio, or video input or output. Microsoft positions MAI-Image 2.5 and MAI-Voice 2 as separate models for those modalities.
Microsoft's central differentiator is the training process. The technical paper describes 30T pre-training tokens of commercially licensed and public human-generated data, with 3.55T mid-training tokens, on 8,000 GB200 GPUs (RL phase: 4,600 GB300s). Microsoft claims the model was trained without third-party-model distillation, excluding synthetic data generated by other labs' models.
The model was first announced at Microsoft Build on June 2, 2026, as part of a seven-model MAI family. It remained in private preview until August 12, 2026.
Benchmark Results: Where It Actually Lands
Microsoft's own technical paper provides the most complete benchmark picture. All MAI-Thinking-1 results are averages across four runs at temperature 1, top-p 0.97, using a 256K total context length for agentic-coding tests. Competitor values come from the respective official model cards, not independent reproduction.
| Benchmark | MAI-Thinking-1 | Sonnet 4.6 | Opus 4.6 | GPT-5.4 | Kimi K2.6 | DeepSeek V4 | GLM-5.1 |
|---|---|---|---|---|---|---|---|
| AIME 2025 | 97.0 | 95.6 | 99.8 | — | — | — | — |
| AIME 2026 | 94.5 | — | — | — | 96.4 | — | 95.3 |
| GPQA Diamond | 84.2 | 89.9 | 91.3 | 92.8 | 90.5 | 90.1 | 85.2 |
| LiveCodeBench v6 | 87.7 | — | — | — | 89.6 | 93.5 | — |
| SWE-Bench Verified | 73.5 | 79.6 | 80.8 | — | 80.2 | 80.6 | — |
| SWE-Bench Pro | 52.8 | — | 53.4 | 57.7 | 58.6 | 55.4 | 58.4 |
| Terminal-Bench 2.0 | 46.0 | 59.1 | 65.4 | 75.1 | 66.7 | 67.9 | 69.0 |
The pattern is clear. On pure math, MAI-Thinking-1 is strong. The 97.0% on AIME 2025 beats Sonnet 4.6's 95.6%, though it falls short of Opus 4.6's 99.8%. On AIME 2026 (94.5%), it trails both Kimi K2.6 (96.4%) and GLM-5.1 (95.3%).
On agentic coding, the gap widens. SWE-Bench Pro at 52.8% is close to Opus 4.6's 53.4%, the specific comparison Microsoft highlights. But GPT-5.4 (57.7%), Kimi K2.6 (58.6%), DeepSeek V4 (55.4%), and GLM-5.1 (58.4%) all score higher. On Terminal-Bench 2.0, which measures multi-step terminal-agent performance, MAI-Thinking-1's 46.0% trails Sonnet 4.6 (59.1%) by 13 points and GPT-5.4 (75.1%) by 29 points.
The technical paper itself acknowledges the model "does not lead the field." MAI-Thinking-1 is competitive for its 35B-active footprint, not competitive at the top of the leaderboard.
Additional benchmark data from the technical paper, compared against Sonnet 4.6:
| Area | MAI-Thinking-1 | Sonnet 4.6 |
|---|---|---|
| MMLU-Pro | 85 | 87 |
| SimpleQA Verified | 31 | 29 |
| BFCL v3 (tool calling) | 72 | 76 |
| CyberSecEval Instruct | 63 | 62 |
| GraphWalks (≤128K) | 90 | 96 |
The Sonnet 4.6 Preference Claim
Microsoft's most heavily marketed result is a blind side-by-side human evaluation conducted with Surge professional raters across 1,276 tasks (30% multi-turn). The technical paper provides exact figures that the launch blog omits:
Against Claude Sonnet 4.6:
- MAI-Thinking-1 wins: 49%, ties: 6%, losses: 45%
- Overall preference delta: +0.07 ± 0.06
- Strongest advantage: conciseness/relevance (+0.11 ± 0.02) and style/tone (+0.08 ± 0.02)
- Statistically tied on instruction following, factuality, and completeness
Against Claude Opus 4.6:
- MAI-Thinking-1 wins: 43%, ties: 5%, losses: 52%
- Overall preference delta: -0.07 ± 0.06
The Sonnet comparison passes the bar of "preferred" in aggregate, but the +0.07 margin with a ±0.06 confidence interval means the edge is real but narrow. The Opus comparison is a clear loss. The tasks skew toward open Q&A, content authoring, and summarization, not the heavy coding and multi-step reasoning workloads where MAI-Thinking-1's benchmark scores are weakest.
On Reddit, r/LocalLLaMA users debate whether MAI-Thinking-1 effectively succeeds Microsoft's Phi line, noting the family is not open-weight. The strategic context matters: per reporting from Bloomberg, Microsoft has begun replacing OpenAI and Anthropic models with MAI in Excel and Outlook, suggesting MAI-Thinking-1's real value is cost control for Microsoft's own products.
Pricing and Access Reality
There is no public MAI-Thinking-1 token pricing. Microsoft uses qualitative language — "mid-weight price," "cost-efficient," "smaller inference footprint" — without a single dollar figure across the launch announcement, model page, or technical report. This is the single biggest blocker for anyone evaluating it for production use.
For context, here is what comparable reasoning models charge (OpenAI pricing, Google AI pricing):
| Model | Input ($/1M tokens) | Output ($/1M tokens) |
|---|---|---|
| OpenAI o3 | ~$10 | ~$40 |
| Gemini 2.5 Pro | ~$1.25 | ~$10 |
| Claude Sonnet 4.6* | ~$3 | ~$15 |
\*Claude pricing varies by tier; approximate mid-range from Anthropic pricing.
Microsoft's "mid-weight" positioning suggests MAI-Thinking-1 will likely land between Gemini 2.5 Pro and Claude Sonnet on cost, but until a rate is published, budgeting is speculative.
On access: MAI-Thinking-1 is available in public preview through Microsoft Foundry, with a playground link provided on the model page. The June announcement named OpenRouter, Fireworks AI, and Baseten as planned distribution partners, but none are live as of this review. The model is closed-weight, with no Hugging Face release, GGUF, or self-hosting path.
To actually use MAI-Thinking-1 today:
- Sign in to Microsoft Foundry with an Azure account
- Navigate to the MAI-Thinking-1 model page within Foundry
- Use the playground for testing, or deploy via the Chat Completions-compatible endpoint
- Billing flows through Azure subscription; rates remain undisclosed in preview
Who Should Use MAI-Thinking-1 Now
It makes sense for:
- Teams already standardized on Azure or Microsoft Foundry who want a first-party reasoning model with enterprise governance controls
- Workloads dominated by math, formal reasoning, or competition-style problems — the 97% AIME 2025 score is genuine
- Organizations that need clean data provenance for compliance reasons — Microsoft's "no distillation, licensed data" claim matters for regulated industries
- Teams doing code review and analysis where the model's conciseness advantage (noted in the human eval) is valuable
Skip it for now if you need:
- Multimodal input/output — it is text-only
- Long-horizon agentic tasks — Terminal-Bench 2.0 at 46% is a dealbreaker for terminal automation
- Self-hosting or open weights — the model is proprietary and locked to Foundry
- Predictable production costs — no pricing means no budgeting
- Top-tier coding-agent performance — Kimi K2.6, GPT-5.4, and DeepSeek V4 all score higher on SWE-Bench Pro and Verified
FAQ
Is MAI-Thinking-1 open source?
No. The model is proprietary and closed-weight. There are no downloadable weights, no Hugging Face release, and no self-hosting path. Access is through Microsoft Foundry only.
Is MAI-Thinking-1 powering Copilot?
Microsoft has reportedly started replacing OpenAI and Anthropic models with MAI models in Excel and Outlook, per reporting from Bloomberg. However, MAI-Thinking-1 is not confirmed as the model behind GitHub Copilot or Microsoft 365 Copilot for end users.
Is MAI-Thinking-1 the successor to Microsoft Phi?
It is not positioned that way, but the community sees it as a directional shift. Phi was Microsoft's open-weight small-model family. MAI is Microsoft's new proprietary family. The key difference: MAI-Thinking-1 is closed and larger (35B active vs Phi's 3-14B), targeting enterprise deployment rather than local execution.
Does MAI-Thinking-1 support vision, audio, or video?
No. It is text-only for both input and output. Microsoft offers separate MAI-Image 2.5 (text-to-image), MAI-Transcribe-1.5 (speech-to-text), and MAI-Voice-2 (speech generation) for other modalities.
What is MAI-Thinking-1's training data cutoff?
The model card lists a July 2025 training cutoff, but the technical report indicates source collection extended into early 2026 (web HTML through September 2025, web PDFs through December 2025, books and journals through March 2026). This discrepancy suggests the cutoff refers to when post-training data collection stopped, not when all sources were gathered.
Can I use MAI-Thinking-1 through OpenRouter?
Not yet. Microsoft named OpenRouter, Fireworks AI, and Baseten as planned distribution partners at the June 2 launch, but none are live as of August 2026. The only current access path is Microsoft Foundry public preview.
| Your workload | Better choice today |
|---|---|
| Competition math, formal proofs | MAI-Thinking-1 (97% AIME) or Claude Opus 4.6 (99.8%) |
| Agentic coding, terminal automation | GPT-5.4 (75.1% Terminal-Bench) or Kimi K2.6 (66.7%) |
| Code review, bug detection | Claude Sonnet 4.6 (79.6% SWE-Verified) or Opus 4.6 (80.8%) |
| Enterprise Azure-native reasoning | MAI-Thinking-1 (first-party, Foundry governance) |
| Budget-constrained production | Gemini 2.5 Pro ($1.25/$10) |
| Self-hosting or open weights | Not available from MAI; consider DeepSeek V4 or Qwen3.8 open weights |