Model comparison
Microsoft MAI-Thinking-1 vs MiniMax M3
Microsoft against MiniMax, compared on context, price, and verified benchmark results.
Catalog record checked September 5, 2026Individual provider fields may changeEvidence confidence: High — see receipts below
Microsoft
Microsoft MAI-Thinking-1
Frontier
MiniMax
MiniMax M3
Frontier · Open weights
| Specification | Microsoft MAI-Thinking-1 | MiniMax M3 |
|---|---|---|
| Provider | Microsoft | MiniMax |
| Tier | Frontier | Frontier |
| Context window | 256K | Winner: 1M |
| Max output | 64K | Not verifiedUnverified |
| Input / 1M tokens | $2 | Winner: $0.30 |
| Output / 1M tokens | $8 | Winner: $1.20 |
| Weights | Closed | Open |
| Parameters | ~1T total / 35B active (sparse MoE) | 428B total / 23B active (MoE) |
| Reasoning levels | low, medium, high | low, high, max |
| Modalities | text | text, image, video |
| API model id | mai-thinking-1 | minimax-m3 |
| Released | June 2, 2026 | June 1, 2026 |
| Artificial Analysis Intelligence Index (2026-08-14) | Winner: 55 | 51 |
| AIME 2025 (2026-08-12) | 97 | Not verifiedUnverified |
| SWE-bench Verified (2026-06) | 73.5 | Not verifiedUnverified |
| GPQA Diamond (2026-06) | 84.2 | Not verifiedUnverified |
| Terminal-Bench 2.0 (2026-06) | 46 | Not verifiedUnverified |
| Terminal-Bench 2.1 (2026-06-01) | Not verifiedUnverified | 66 |
Prices are USD per million tokens at standard rates, excluding batch and caching discounts. Bold indicates the better figure where one is objectively better. Values we could not confirm from the provider are shown as “Not verified” rather than estimated.
Benchmark receipts
- 2026-08-14: Artificial AnalysisComposite index blending reasoning, knowledge, and coding evals into one 0–100 score. Comparability: directly comparable — AA occasionally rebaselines the index scale between snapshots — a score captured on one date is only comparable to same-snapshot scores (check measuredAt).
- 2026-08-12: Microsoft AI — Introducing MAI-Thinking-1 (vendor, 256k output)Competition mathematics: AIME 2025 exam problems, typically pass@1 with tools disallowed or single-attempt code execution per the harness. Comparability: comparable with caveat — 30-question total denominator: one problem = ~3.3 points. Tool-use policy (calculator/code interpreter) must match between compared models.
- 2026-06-01: MiniMax blog (vendor, Terminus 2 scaffolding, 2h timeout)Agentic terminal work: multi-step tasks executed in a sandboxed shell environment. Comparability: comparable with caveat — Scores across Terminal-Bench major versions (v1 vs v2) are NOT comparable; harness configuration (container, time limits) also shifts results.
- 2026-06: Microsoft AI model page (vendor, as labeled: Terminal-Bench 2.0 — NOT comparable to 2.1 observations)Real GitHub issue resolution: does the model's patch pass the hidden tests. Comparability: comparable with caveat — Post-audit vendor claims and pre-audit scores sit on different task trust levels; scaffolding (agent harness, compute budget) also dominates results. Never aggregate across scaffolds.
Pricing tiers: Microsoft MAI-Thinking-1: Global Standard $2.00/$8.00 per MTok, cached input $0.20 (Azure Retail Prices API, effective 2026-08-01, uniform across ~22 public regions; US Gov regions carry premiums). Still preview; Global Standard only, no PTU yet. 256K context with a 64K output cap that includes reasoning tokens. ~1T/35B sparse MoE; reasoning is always on (no effort levels). Microsoft's first true reasoning model, trained without OpenAI distillation. · MiniMax M3: $0.30/$1.20 per MTok; open (community license). 428B/23B active MoE, native multimodal. Rate is the ≤512K-prompt tier; higher above.
Microsoft MAI-Thinking-1
MAI-Thinking-1 is Microsoft's first in-house reasoning model, reducing dependence on OpenAI.
Best for
- Enterprise (Azure)
- Reasoning
- Microsoft ecosystem
Watch out
Foundry-gated preview; no MAI-2 exists yet. Of the Build 2026 MAI wave, only MAI-Thinking-1 and MAI-Cyber-1-Flash ($0.60/$3.50, released 2026-07-27) have published token meters.
MiniMax M3
MiniMax M3 is an open-weight (community license) 428B MoE with native multimodal and 1M context.
Best for
- Open-weight deployments
- Multimodal
- Long-context
Watch out
Community license, not fully open; verify terms.
When the cheaper one wins
MiniMax M3 is cheaper on output at $1.20 per million tokens against $8 for Microsoft MAI-Thinking-1 — about 6.7×. Use the cheaper tier for classification, extraction, summarisation, and any task where the expensive model’s extra score does not change the accepted output. The expensive one only pays if your hardest task actually fails on the cheap tier. These are standard-tier API rates, excluding batch and cache discounts.
Run the model pickerEvidence confidence: High
How strong and complete the evidence behind this comparison is — not a prediction of which model is better.
- Pricing verified on both sides — Input and output rates are verified for both models.
- 4/5 core specs verified on both sides — Not published for at least one side: max output.
- 1 shared named benchmark with differing scores — Measured on: Artificial Analysis Intelligence Index.
- Verified within the last 90 days — Newest catalog check was 6 days ago.
- Both models carry source citations — Each side has at least two catalog sources on record.
Source receipts
Each catalog figure was checked against the provider or an independent second source on the date shown.
- Microsoft MAI-Thinking-1: Azure Retail Prices API (MAI-Thinking-1 $2/$0.20 cached/$8) (accessed 2026-09-04)
- Microsoft MAI-Thinking-1: AzureSpeed — AI model pricing tracker (same figures) (accessed 2026-09-04)
- Microsoft MAI-Thinking-1: Microsoft — Introducing MAI-Thinking-1 (~1T total / 35B active MoE) (accessed 2026-09-05)
- Microsoft MAI-Thinking-1: Microsoft Foundry — MAI-Thinking-1 usage (256K context, 64K output cap) (accessed 2026-09-05)
- MiniMax M3: MiniMax — M3 (accessed 2026-08-29)
- MiniMax M3: MiniMax M3 release (accessed 2026-08-29)
Related comparisons
- Claude Fable 5.1 vs Microsoft MAI-Thinking-1
- Claude Fable 5.1 vs MiniMax M3
- Claude Fable 5 vs Microsoft MAI-Thinking-1
- Claude Fable 5 vs MiniMax M3
- Claude Mythos 5.1 vs Microsoft MAI-Thinking-1
- Claude Mythos 5.1 vs MiniMax M3
Diving deeper on one model? Microsoft MAI-Thinking-1 · MiniMax M3
Common questions
Microsoft MAI-Thinking-1 vs MiniMax M3
Answered from the verified figures on this page rather than general guidance.
Is Microsoft MAI-Thinking-1 or MiniMax M3 cheaper for input?
MiniMax M3 is cheaper at $0.30 per million input tokens, against $2 for Microsoft MAI-Thinking-1 — roughly 6.7× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; Microsoft MAI-Thinking-1 has tiered pricing: Global Standard $2.00/$8.00 per MTok, cached input $0.20 (Azure Retail Prices API, effective 2026-08-01, uniform across ~22 public regions; US Gov regions carry premiums). Still preview; Global Standard only, no PTU yet. 256K context with a 64K output cap that includes reasoning tokens. ~1T/35B sparse MoE; reasoning is always on (no effort levels). Microsoft's first true reasoning model, trained without OpenAI distillation. MiniMax M3 has tiered pricing: $0.30/$1.20 per MTok; open (community license). 428B/23B active MoE, native multimodal. Rate is the ≤512K-prompt tier; higher above.
Is Microsoft MAI-Thinking-1 or MiniMax M3 cheaper for output?
MiniMax M3 is cheaper at $1.20 per million output tokens, against $8 for Microsoft MAI-Thinking-1 — roughly 6.7× the price. Output tokens usually dominate a real bill, so weigh the output rate more heavily than the input rate. These are base rates; Microsoft MAI-Thinking-1 has tiered pricing: Global Standard $2.00/$8.00 per MTok, cached input $0.20 (Azure Retail Prices API, effective 2026-08-01, uniform across ~22 public regions; US Gov regions carry premiums). Still preview; Global Standard only, no PTU yet. 256K context with a 64K output cap that includes reasoning tokens. ~1T/35B sparse MoE; reasoning is always on (no effort levels). Microsoft's first true reasoning model, trained without OpenAI distillation. MiniMax M3 has tiered pricing: $0.30/$1.20 per MTok; open (community license). 428B/23B active MoE, native multimodal. Rate is the ≤512K-prompt tier; higher above.
Which has the larger context window, Microsoft MAI-Thinking-1 or MiniMax M3?
MiniMax M3 accepts 1M tokens against 256K for Microsoft MAI-Thinking-1. This only matters if you routinely send very long documents or large codebases.
Do Microsoft MAI-Thinking-1 and MiniMax M3 support the same reasoning levels?
Microsoft MAI-Thinking-1 exposes low, medium, high, while MiniMax M3 exposes low, high, max.
Should I use Microsoft MAI-Thinking-1 or MiniMax M3?
Both sit in the frontier tier, so the choice usually comes down to price and context rather than capability. Microsoft MAI-Thinking-1 suits enterprise (azure); MiniMax M3 suits open-weight deployments.
Can I self-host Microsoft MAI-Thinking-1 or MiniMax M3?
MiniMax M3 publishes open weights, but self-hosting and third-party provider access depend on the licence, hardware, serving support, and availability. Microsoft MAI-Thinking-1 is a closed model whose supported access paths are controlled by its provider.
Next step
Choosing between them
The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.
- Input price: MiniMax M3 costs $0.30 per 1M tokens versus $2 for Microsoft MAI-Thinking-1 — a 6.7x difference at the headline tier.
- Context: MiniMax M3 takes 1M against 256K for Microsoft MAI-Thinking-1 — only decisive if your prompts approach the smaller window.
- Measured capability: Microsoft MAI-Thinking-1 leads Artificial Analysis Intelligence Index 55 to 51 (measured 2026-08-14).
- Deployment: MiniMax M3 publishes weights you can self-host; the other is API-only.
Choosing a harness rather than a model — Cursor, Copilot, Claude Code, Windsurf, or Lovable? Compare agentic harnesses · Latest releases.