Pick MAI-Thinking-1 for very strong math reasoning (aime 2025 97%, aime 2026 94.5%) or microsoft's first in-house flagship reasoner, trained without openai distillation. Pick Muse Spark 1.3 for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2 or deepswe v1.1 long-horizon software engineering (75.4). On a tight budget at scale, MAI-Thinking-1 is the value pick.
MAI-Thinking-1 (Microsoft) and Muse Spark 1.3 (Meta) are two of the models people most often weigh against each other in 2026. MAI-Thinking-1 is microsoft's first fully in-house flagship reasoning model — a Claude-class reasoner built independently to cut its OpenAI dependence. Muse Spark 1.3 is meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Context window: Muse Spark 1.3 holds 3.9× more — 1M tokens (~1,500 pages) vs 256K (~384 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Muse Spark 1.3 is the newer model by about 21 days (released September 2, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
MAI-Thinking-1
Muse Spark 1.3
Provider
Microsoft (US)
Meta (US)
Released
August 12, 2026
September 2, 2026
Context window
256K (~384 pages)
1M tokens (~1,500 pages)
Price (in/out)
Not published
$1.25/$4.25 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, code
text, image, video
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
98.1%
Who wins what
Very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%): MAI-Thinking-1 — Muse Spark 1.3 is comparatively weak here — strongest 'max' reasoning configuration still gated pending additional safety testing
Microsoft's first in-house flagship reasoner, trained without OpenAI distillation: MAI-Thinking-1 — MAI-Thinking-1 lists microsoft's first in-house flagship reasoner, trained without OpenAI distillation among its strengths; Muse Spark 1.3 does not.
Efficient reasoning at low token cost for its class: MAI-Thinking-1 — MAI-Thinking-1 lists efficient reasoning at low token cost for its class among its strengths; Muse Spark 1.3 does not.
Agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2: Muse Spark 1.3 — Its 1M tokens window holds about 3.9× more than MAI-Thinking-1's 256K in a single prompt.
DeepSWE v1.1 long-horizon software engineering (75.4): Muse Spark 1.3 — Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review — and it carries the larger 1M tokens context.
Near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1): Muse Spark 1.3 — Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review — and it is the newer of the two.
Lowest cost at scale: MAI-Thinking-1 — Its weights are open, so at volume you pay for your own hardware instead of Muse Spark 1.3's $1.25/$4.25 per 1M tokens.
Largest single-prompt input: Muse Spark 1.3 — Its 1M tokens window is about 3.9× larger than MAI-Thinking-1's 256K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: MAI-Thinking-1 — At Not published it undercuts Muse Spark 1.3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Muse Spark 1.3 — Larger 1M tokens window fits more in one prompt.
Anyone whose priority is very strong math reasoning (aime 2025 97%, aime 2026 94.5%): MAI-Thinking-1 — It is specifically built for that.
Anyone whose priority is agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2: Muse Spark 1.3 — That is its strongest area.
MAI-Thinking-1: where it fits
Microsoft's first fully in-house flagship reasoning model — a Claude-class reasoner built independently to cut its OpenAI dependence. Released August 12, 2026 by Microsoft, it is built for very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%), microsoft's first in-house flagship reasoner, trained without OpenAI distillation, efficient reasoning at low token cost for its class, and competitive with Claude Opus 4.6 on SWE-Bench Pro (vendor-reported).
Its trade-offs are real: closed and in private preview — no open weights, no published pricing, thin availability, and benchmarks are largely self-reported.
Muse Spark 1.3: where it fits
Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review. Released September 2, 2026 by Meta, it is built for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2, deepSWE v1.1 long-horizon software engineering (75.4), near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1), and ranks third overall on the Artificial Analysis Intelligence Index (score 61, xhigh variant; the limited-preview max variant scores 62) - behind only Claude Fable 5.1 and Claude Opus 5.
Its trade-offs: strongest 'max' reasoning configuration still gated pending additional safety testing, not yet open-weight, despite Meta roadmapping a future Muse Spark weights release, and no official SWE-bench Verified score published. At $1.25 in / $4.25 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
MAI-Thinking-1 and Muse Spark 1.3 overlap enough that the right pick depends on your specific job. MAI-Thinking-1 costs less per token; Muse Spark 1.3 holds the larger context; and each leads in its own area — MAI-Thinking-1 for very strong math reasoning (aime 2025 97%, aime 2026 94.5%), Muse Spark 1.3 for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is MAI-Thinking-1 or Muse Spark 1.3 better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, MAI-Thinking-1 leans toward very strong math reasoning (aime 2025 97%, aime 2026 94.5%) while Muse Spark 1.3 leans toward agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, MAI-Thinking-1 or Muse Spark 1.3?
MAI-Thinking-1 is cheaper — Not published vs $1.25/$4.25 per 1M tokens.
Which has the bigger context window?
Muse Spark 1.3 — 1M tokens vs 256K, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both MAI-Thinking-1 and Muse Spark 1.3 together?
Yes — a multi-model platform like LumiChats gives you MAI-Thinking-1, Muse Spark 1.3 and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, MAI-Thinking-1 or Muse Spark 1.3?
Muse Spark 1.3 — released September 2, 2026, about 21 days after MAI-Thinking-1.
MAI-Thinking-1 vs Muse Spark 1.3
Microsoft · US | Meta · US · Updated June 2026
Quick verdict
Pick MAI-Thinking-1 for very strong math reasoning (aime 2025 97%, aime 2026 94.5%) or microsoft's first in-house flagship reasoner, trained without openai distillation. Pick Muse Spark 1.3 for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2 or deepswe v1.1 long-horizon software engineering (75.4). On a tight budget at scale, MAI-Thinking-1 is the value pick.
MAI-Thinking-1 (Microsoft) and Muse Spark 1.3 (Meta) are two of the models people most often weigh against each other in 2026. MAI-Thinking-1 is microsoft's first fully in-house flagship reasoning model — a Claude-class reasoner built independently to cut its OpenAI dependence. Muse Spark 1.3 is meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Context window: Muse Spark 1.3 holds 3.9× more — 1M tokens (~1,500 pages) vs 256K (~384 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Muse Spark 1.3 is the newer model by about 21 days (released September 2, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
MAI-Thinking-1
Muse Spark 1.3
Provider
Microsoft (US)
Meta (US)
Released
August 12, 2026
September 2, 2026
Context window
256K (~384 pages)
1M tokens (~1,500 pages)
Price (in/out)
Not published
$1.25/$4.25 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, code
text, image, video
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
98.1%
Who wins what
Very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%)
MAI-Thinking-1
Muse Spark 1.3 is comparatively weak here — strongest 'max' reasoning configuration still gated pending additional safety testing
Microsoft's first in-house flagship reasoner, trained without OpenAI distillation
MAI-Thinking-1
MAI-Thinking-1 lists microsoft's first in-house flagship reasoner, trained without OpenAI distillation among its strengths; Muse Spark 1.3 does not.
Efficient reasoning at low token cost for its class
MAI-Thinking-1
MAI-Thinking-1 lists efficient reasoning at low token cost for its class among its strengths; Muse Spark 1.3 does not.
Agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2
Muse Spark 1.3
Its 1M tokens window holds about 3.9× more than MAI-Thinking-1's 256K in a single prompt.
Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review — and it carries the larger 1M tokens context.
Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review — and it is the newer of the two.
Lowest cost at scale
MAI-Thinking-1
Its weights are open, so at volume you pay for your own hardware instead of Muse Spark 1.3's $1.25/$4.25 per 1M tokens.
Largest single-prompt input
Muse Spark 1.3
Its 1M tokens window is about 3.9× larger than MAI-Thinking-1's 256K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ MAI-Thinking-1
At Not published it undercuts Muse Spark 1.3, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Muse Spark 1.3
Larger 1M tokens window fits more in one prompt.
Anyone whose priority is very strong math reasoning (aime 2025 97%, aime 2026 94.5%)
→ MAI-Thinking-1
It is specifically built for that.
Anyone whose priority is agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2
→ Muse Spark 1.3
That is its strongest area.
MAI-Thinking-1: where it fits
Microsoft's first fully in-house flagship reasoning model — a Claude-class reasoner built independently to cut its OpenAI dependence. Released August 12, 2026 by Microsoft, it is built for very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%), microsoft's first in-house flagship reasoner, trained without OpenAI distillation, efficient reasoning at low token cost for its class, and competitive with Claude Opus 4.6 on SWE-Bench Pro (vendor-reported).
Its trade-offs are real: closed and in private preview — no open weights, no published pricing, thin availability, and benchmarks are largely self-reported.
Muse Spark 1.3: where it fits
Meta's September 2, 2026 agentic-coding model update, cutting tool calls and token usage versus Muse Spark 1.2 while its highest-reasoning mode remains gated for safety review. Released September 2, 2026 by Meta, it is built for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than Muse Spark 1.2, deepSWE v1.1 long-horizon software engineering (75.4), near-perfect long-context retrieval (MRCR v2 512K-1M: 98.1), and ranks third overall on the Artificial Analysis Intelligence Index (score 61, xhigh variant; the limited-preview max variant scores 62) - behind only Claude Fable 5.1 and Claude Opus 5.
Its trade-offs: strongest 'max' reasoning configuration still gated pending additional safety testing, not yet open-weight, despite Meta roadmapping a future Muse Spark weights release, and no official SWE-bench Verified score published. At $1.25 in / $4.25 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
MAI-Thinking-1 and Muse Spark 1.3 overlap enough that the right pick depends on your specific job. MAI-Thinking-1 costs less per token; Muse Spark 1.3 holds the larger context; and each leads in its own area — MAI-Thinking-1 for very strong math reasoning (aime 2025 97%, aime 2026 94.5%), Muse Spark 1.3 for agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both MAI-Thinking-1 and Muse Spark 1.3 without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
Is MAI-Thinking-1 or Muse Spark 1.3 better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, MAI-Thinking-1 leans toward very strong math reasoning (aime 2025 97%, aime 2026 94.5%) while Muse Spark 1.3 leans toward agentic coding with ~20% fewer tool calls and ~25% fewer tokens than muse spark 1.2, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, MAI-Thinking-1 or Muse Spark 1.3?
MAI-Thinking-1 is cheaper — Not published vs $1.25/$4.25 per 1M tokens.
Which has the bigger context window?
Muse Spark 1.3 — 1M tokens vs 256K, about 3.9× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both MAI-Thinking-1 and Muse Spark 1.3 together?
Yes — a multi-model platform like LumiChats gives you MAI-Thinking-1, Muse Spark 1.3 and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, MAI-Thinking-1 or Muse Spark 1.3?
Muse Spark 1.3 — released September 2, 2026, about 21 days after MAI-Thinking-1.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.