Model comparison
Microsoft MAI-Thinking-1 vs Muse Spark 1.3
Microsoft against Meta, compared on context, price, and verified benchmark results.
Catalog record checked September 5, 2026Individual provider fields may changeEvidence confidence: Medium — see receipts below
Microsoft
Microsoft MAI-Thinking-1
Frontier
Meta
Muse Spark 1.3
Frontier
| Specification | Microsoft MAI-Thinking-1 | Muse Spark 1.3 |
|---|---|---|
| Provider | Microsoft | Meta |
| Tier | Frontier | Frontier |
| Context window | 256K | Winner: 1M |
| Max output | 64K | Winner: 131K |
| Input / 1M tokens | $2 | Winner: $1.25 |
| Output / 1M tokens | $8 | Winner: $4.25 |
| Weights | Closed | Closed |
| Parameters | ~1T total / 35B active (sparse MoE) | Meta frontier model |
| Reasoning levels | low, medium, high | low, medium, high |
| Modalities | text | text, image |
| API model id | mai-thinking-1 | muse-spark-1.3 |
| Released | June 2, 2026 | September 2, 2026 |
| Artificial Analysis Intelligence Index (2026-08-14) | 55 | Not verifiedUnverified |
| 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 |
| DeepSWE 1.1 (2026-09-02) | Not verifiedUnverified | 75.4 |
| Terminal-Bench 2.1 (2026-09-03) | Not verifiedUnverified | 88.8 |
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
- 2026-09-03: Meta launch table (transcribed by explainx.ai) (Vendor self-report; absent from the official tbench.ai leaderboard)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.
- 2026-09-02: Meta launch table (Thinking mode: max — self-reported; not broadly available and NOT on the official Datacurve leaderboard)Agentic software engineering: pass@1 on real repo tasks with reported cost per completed task. Comparability: directly comparable
- 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: 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. · Muse Spark 1.3: $1.25/$4.25 per MTok on Meta's Model API (cached input $0.15); a $0.10/$0.20 'contributor' tier applies when your data is used for training. Third-party reports put list at $1.50/$7.50 from 2027-01-01 — confirm before long-term commits.
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.
Muse Spark 1.3
Muse Spark 1.3 is Meta's September 2026 frontier refresh — a self-reported DeepSWE 1.1 field leader at $1.25/$4.25, with a 1M-token context aimed at autonomous agent workflows.
Best for
- Long-horizon coding agents
- Frontier quality below frontier pricing
- Meta ecosystem
Watch out
The headline 75.4% DeepSWE score comes from the 'max' thinking mode, which is not broadly available yet and is pending independent verification. The 131,072 output cap is per third-party API docs — Meta's own spec page does not publish it. Closed weights, unlike Muse Spark 1.1.
When the cheaper one wins
Muse Spark 1.3 is cheaper on output at $4.25 per million tokens against $8 for Microsoft MAI-Thinking-1 — about 1.9×. 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: Medium
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.
- 5/5 core specs verified on both sides — All core specifications verified for both models.
- No shared named benchmark — No benchmark has been measured on both models.
- 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)
- Muse Spark 1.3: Meta — Introducing Muse Spark 1.3 (accessed 2026-09-03)
- Muse Spark 1.3: Meta developer — Muse Spark pricing ($1.25/$4.25) (accessed 2026-09-03)
- Muse Spark 1.3: VentureBeat — Muse Spark 1.3 best results need a config developers can't broadly use yet (accessed 2026-09-03)
- Muse Spark 1.3: HaiMaker — muse-spark-1.3 (131,072 max output tokens) (accessed 2026-09-05)
- Muse Spark 1.3: Promptfoo — Meta provider docs (muse-spark-1.3 max_tokens ceiling) (accessed 2026-09-05)
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Diving deeper on one model? Microsoft MAI-Thinking-1 · Muse Spark 1.3
Common questions
Microsoft MAI-Thinking-1 vs Muse Spark 1.3
Answered from the verified figures on this page rather than general guidance.
Is Microsoft MAI-Thinking-1 or Muse Spark 1.3 cheaper for input?
Muse Spark 1.3 is cheaper at $1.25 per million input tokens, against $2 for Microsoft MAI-Thinking-1 — roughly 1.6× 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. Muse Spark 1.3 has tiered pricing: $1.25/$4.25 per MTok on Meta's Model API (cached input $0.15); a $0.10/$0.20 'contributor' tier applies when your data is used for training. Third-party reports put list at $1.50/$7.50 from 2027-01-01 — confirm before long-term commits.
Is Microsoft MAI-Thinking-1 or Muse Spark 1.3 cheaper for output?
Muse Spark 1.3 is cheaper at $4.25 per million output tokens, against $8 for Microsoft MAI-Thinking-1 — roughly 1.9× 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. Muse Spark 1.3 has tiered pricing: $1.25/$4.25 per MTok on Meta's Model API (cached input $0.15); a $0.10/$0.20 'contributor' tier applies when your data is used for training. Third-party reports put list at $1.50/$7.50 from 2027-01-01 — confirm before long-term commits.
Which has the larger context window, Microsoft MAI-Thinking-1 or Muse Spark 1.3?
Muse Spark 1.3 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 Muse Spark 1.3 support the same reasoning levels?
Yes — both accept the same effort settings: "low", "medium", "high". Higher effort costs more and takes longer, so start low and raise it only where output quality actually improves.
Should I use Microsoft MAI-Thinking-1 or Muse Spark 1.3?
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); Muse Spark 1.3 suits long-horizon coding agents.
Next step
Choosing between them
The verified figures that separate this pair, computed from the catalog rather than restated boilerplate.
- Input price: Muse Spark 1.3 costs $1.25 per 1M tokens versus $2 for Microsoft MAI-Thinking-1 — a 1.6x difference at the headline tier.
- Context: Muse Spark 1.3 takes 1M against 256K for Microsoft MAI-Thinking-1 — only decisive if your prompts approach the smaller window.
Choosing a harness rather than a model — Cursor, Copilot, Claude Code, Windsurf, or Lovable? Compare agentic harnesses · Latest releases.