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 Palmyra X6 for enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents or writer says its harness upgrades cut agent-workflow token costs by roughly 52% and improve speed by roughly 48% (writer's own figures).
MAI-Thinking-1 (Microsoft) and Palmyra X6 (Writer) 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. Palmyra X6 is writer's enterprise agentic flagship - a GLM-5.2-based model with harness upgrades Writer says cut agent token costs by roughly half. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.
Key differences
Context window: MAI-Thinking-1 holds 2× more — 256K (~384 pages) vs 128K (~192 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Specifications
Spec
MAI-Thinking-1
Palmyra X6
Provider
Microsoft (US)
Writer (US)
Released
August 12, 2026
August 13, 2026
Context window
256K (~384 pages)
128K (~192 pages)
Price (in/out)
Not published
Not published
Open weight?
No — API only
No — API only
Modalities
text, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%): MAI-Thinking-1 — Microsoft's first fully in-house flagship reasoning model — a Claude-class reasoner built independently to cut its OpenAI dependence — and it carries the larger 256K context.
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; Palmyra X6 does not.
Efficient reasoning at low token cost for its class: MAI-Thinking-1 — Its 256K window holds about 2× more than Palmyra X6's 128K in a single prompt.
Enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents: Palmyra X6 — Writer's enterprise agentic flagship - a GLM-5.2-based model with harness upgrades Writer says cut agent token costs by roughly half — and it is the newer of the two.
Writer says its harness upgrades cut agent-workflow token costs by roughly 52% and improve speed by roughly 48% (Writer's own figures): Palmyra X6 — Palmyra X6 lists writer says its harness upgrades cut agent-workflow token costs by roughly 52% and improve speed by roughly 48% (Writer's own figures) among its strengths; MAI-Thinking-1 does not.
A post-trained variant built on Z.ai's open-weight GLM-5.2, tuned specifically for business agent use: Palmyra X6 — MAI-Thinking-1 is comparatively weak here — closed and in private preview — no open weights, no published pricing, thin availability
Largest single-prompt input: MAI-Thinking-1 — Its 256K window is about 2× larger than Palmyra X6's 128K, fitting roughly 384 pages in one prompt.
Which should you pick?
Someone analysing very long documents or codebases: MAI-Thinking-1 — Larger 256K 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 enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents: Palmyra X6 — 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.
Palmyra X6: where it fits
Writer's enterprise agentic flagship - a GLM-5.2-based model with harness upgrades Writer says cut agent token costs by roughly half. Released August 13, 2026 by Writer, it is built for enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents, writer says its harness upgrades cut agent-workflow token costs by roughly 52% and improve speed by roughly 48% (Writer's own figures), and a post-trained variant built on Z.ai's open-weight GLM-5.2, tuned specifically for business agent use.
Its trade-offs: no public per-token API price - sold through Writer's enterprise platform, not a self-serve API, not independently benchmarked on general leaderboards like SWE-bench or Artificial Analysis, and built for a narrower enterprise-agent use case rather than general-purpose chat.
The bottom line for this matchup
MAI-Thinking-1 and Palmyra X6 overlap enough that the right pick depends on your specific job. MAI-Thinking-1 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%), Palmyra X6 for enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents. 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 Palmyra X6 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 Palmyra X6 leans toward enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, MAI-Thinking-1 or Palmyra X6?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
MAI-Thinking-1 — 256K vs 128K, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both MAI-Thinking-1 and Palmyra X6 together?
Yes — a multi-model platform like LumiChats gives you MAI-Thinking-1, Palmyra X6 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 Palmyra X6?
Palmyra X6 — released August 13, 2026, about 1 days after MAI-Thinking-1.
MAI-Thinking-1 vs Palmyra X6
Microsoft · US | Writer · 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 Palmyra X6 for enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents or writer says its harness upgrades cut agent-workflow token costs by roughly 52% and improve speed by roughly 48% (writer's own figures).
MAI-Thinking-1 (Microsoft) and Palmyra X6 (Writer) 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. Palmyra X6 is writer's enterprise agentic flagship - a GLM-5.2-based model with harness upgrades Writer says cut agent token costs by roughly half. Their biggest split is context window, and the breakdown below shows exactly how that plays out for your workload.
Key differences at a glance
▸Context window: MAI-Thinking-1 holds 2× more — 256K (~384 pages) vs 128K (~192 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Side-by-side specs
Spec
MAI-Thinking-1
Palmyra X6
Provider
Microsoft (US)
Writer (US)
Released
August 12, 2026
August 13, 2026
Context window
256K (~384 pages)
128K (~192 pages)
Price (in/out)
Not published
Not published
Open weight?
No — API only
No — API only
Modalities
text, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%)
MAI-Thinking-1
Microsoft's first fully in-house flagship reasoning model — a Claude-class reasoner built independently to cut its OpenAI dependence — and it carries the larger 256K context.
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; Palmyra X6 does not.
Efficient reasoning at low token cost for its class
MAI-Thinking-1
Its 256K window holds about 2× more than Palmyra X6's 128K in a single prompt.
Enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents
Palmyra X6
Writer's enterprise agentic flagship - a GLM-5.2-based model with harness upgrades Writer says cut agent token costs by roughly half — and it is the newer of the two.
Writer says its harness upgrades cut agent-workflow token costs by roughly 52% and improve speed by roughly 48% (Writer's own figures)
Palmyra X6
Palmyra X6 lists writer says its harness upgrades cut agent-workflow token costs by roughly 52% and improve speed by roughly 48% (Writer's own figures) among its strengths; MAI-Thinking-1 does not.
A post-trained variant built on Z.ai's open-weight GLM-5.2, tuned specifically for business agent use
Palmyra X6
MAI-Thinking-1 is comparatively weak here — closed and in private preview — no open weights, no published pricing, thin availability
Largest single-prompt input
MAI-Thinking-1
Its 256K window is about 2× larger than Palmyra X6's 128K, fitting roughly 384 pages in one prompt.
Which should you pick?
Someone analysing very long documents or codebases
→ MAI-Thinking-1
Larger 256K 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 enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents
→ Palmyra X6
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.
Palmyra X6: where it fits
Writer's enterprise agentic flagship - a GLM-5.2-based model with harness upgrades Writer says cut agent token costs by roughly half. Released August 13, 2026 by Writer, it is built for enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents, writer says its harness upgrades cut agent-workflow token costs by roughly 52% and improve speed by roughly 48% (Writer's own figures), and a post-trained variant built on Z.ai's open-weight GLM-5.2, tuned specifically for business agent use.
Its trade-offs: no public per-token API price - sold through Writer's enterprise platform, not a self-serve API, not independently benchmarked on general leaderboards like SWE-bench or Artificial Analysis, and built for a narrower enterprise-agent use case rather than general-purpose chat.
The bottom line for this matchup
MAI-Thinking-1 and Palmyra X6 overlap enough that the right pick depends on your specific job. MAI-Thinking-1 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%), Palmyra X6 for enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both MAI-Thinking-1 and Palmyra X6 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 Palmyra X6 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 Palmyra X6 leans toward enterprise agentic workflows - built specifically for marketing/revenue teams running multi-step agents, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, MAI-Thinking-1 or Palmyra X6?
They are priced almost identically, so cost will not decide between them.
Which has the bigger context window?
MAI-Thinking-1 — 256K vs 128K, about 2× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both MAI-Thinking-1 and Palmyra X6 together?
Yes — a multi-model platform like LumiChats gives you MAI-Thinking-1, Palmyra X6 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 Palmyra X6?
Palmyra X6 — released August 13, 2026, about 1 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.