Pick Amazon Nova Pro for multimodal input across text, image and video at $0.80/$3.20 or deep aws and bedrock integration for enterprise pipelines. 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. On a tight budget at scale, MAI-Thinking-1 is the value pick.
Amazon Nova Pro (Amazon) and MAI-Thinking-1 (Microsoft) are two of the models people most often weigh against each other in 2026. Amazon Nova Pro is amazon's multimodal Bedrock model at $0.80/$3.20 with a 300K window — an enterprise-integrated generalist, not a frontier model. MAI-Thinking-1 is microsoft's first fully in-house flagship reasoning model — a Claude-class reasoner built independently to cut its OpenAI dependence. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Context window: Amazon Nova Pro holds 1.2× more — 300K (~450 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: MAI-Thinking-1 is the newer model by about 18 months (released June 2, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Amazon Nova Pro
MAI-Thinking-1
Provider
Amazon (US)
Microsoft (US)
Released
December 5, 2024
June 2, 2026
Context window
300K (~450 pages)
256K (~384 pages)
Price (in/out)
$0.8/$3.2 per 1M tokens
Not published
Open weight?
No — API only
No — API only
Modalities
text, image, video, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Multimodal input across text, image and video at $0.80/$3.20: Amazon Nova Pro — Amazon's multimodal Bedrock model at $0.80/$3.20 with a 300K window — an enterprise-integrated generalist, not a frontier model — and it carries the larger 300K context.
Deep AWS and Bedrock integration for enterprise pipelines: Amazon Nova Pro — Amazon Nova Pro lists deep AWS and Bedrock integration for enterprise pipelines among its strengths; MAI-Thinking-1 does not.
Balanced cost-to-capability for general business tasks: Amazon Nova Pro — Amazon Nova Pro lists balanced cost-to-capability for general business tasks among its strengths; MAI-Thinking-1 does not.
Very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%): MAI-Thinking-1 — Amazon Nova Pro is comparatively weak here — not a frontier reasoning or coding model against 2026 flagships
Microsoft's first in-house flagship reasoner, trained without OpenAI distillation: 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 is the newer of the two.
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; Amazon Nova Pro does not.
Lowest cost at scale: MAI-Thinking-1 — Its weights are open, so at volume you pay for your own hardware instead of Amazon Nova Pro's $0.8/$3.2 per 1M tokens.
Largest single-prompt input: Amazon Nova Pro — Its 300K window is about 1.2× larger than MAI-Thinking-1's 256K, fitting roughly 450 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: MAI-Thinking-1 — At Not published it undercuts Amazon Nova Pro, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Amazon Nova Pro — Larger 300K window fits more in one prompt.
Anyone whose priority is multimodal input across text, image and video at $0.80/$3.20: Amazon Nova Pro — It is specifically built for that.
Anyone whose priority is very strong math reasoning (aime 2025 97%, aime 2026 94.5%): MAI-Thinking-1 — That is its strongest area.
Amazon Nova Pro: where it fits
Amazon's multimodal Bedrock model at $0.80/$3.20 with a 300K window — an enterprise-integrated generalist, not a frontier model. Released December 5, 2024 by Amazon, it is built for multimodal input across text, image and video at $0.80/$3.20, deep AWS and Bedrock integration for enterprise pipelines, balanced cost-to-capability for general business tasks, and a 300K context for long documents and mixed media.
Its trade-offs are real: not a frontier reasoning or coding model against 2026 flagships, no published SWE-Bench Verified score, best value is realised inside the AWS ecosystem, and late-2024 model — older than most of the field here. At $0.8 in / $3.2 out per million tokens, it sits in the budget price band.
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 June 2, 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: closed and in private preview — no open weights, no published pricing, thin availability, and benchmarks are largely self-reported.
The bottom line for this matchup
Amazon Nova Pro and MAI-Thinking-1 overlap enough that the right pick depends on your specific job. MAI-Thinking-1 costs less per token; Amazon Nova Pro holds the larger context; and each leads in its own area — Amazon Nova Pro for multimodal input across text, image and video at $0.80/$3.20, MAI-Thinking-1 for very strong math reasoning (aime 2025 97%, aime 2026 94.5%). Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Amazon Nova Pro or MAI-Thinking-1 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, Amazon Nova Pro leans toward multimodal input across text, image and video at $0.80/$3.20 while MAI-Thinking-1 leans toward very strong math reasoning (aime 2025 97%, aime 2026 94.5%), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Amazon Nova Pro or MAI-Thinking-1?
MAI-Thinking-1 is cheaper — $0.8/$3.2 per 1M tokens vs Not published.
Which has the bigger context window?
Amazon Nova Pro — 300K vs 256K, about 1.2× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Amazon Nova Pro and MAI-Thinking-1 together?
Yes — a multi-model platform like LumiChats gives you Amazon Nova Pro, MAI-Thinking-1 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, Amazon Nova Pro or MAI-Thinking-1?
MAI-Thinking-1 — released June 2, 2026, about 18 months after Amazon Nova Pro.
Amazon Nova Pro vs MAI-Thinking-1
Amazon · US | Microsoft · US · Updated June 2026
Quick verdict
Pick Amazon Nova Pro for multimodal input across text, image and video at $0.80/$3.20 or deep aws and bedrock integration for enterprise pipelines. 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. On a tight budget at scale, MAI-Thinking-1 is the value pick.
Amazon Nova Pro (Amazon) and MAI-Thinking-1 (Microsoft) are two of the models people most often weigh against each other in 2026. Amazon Nova Pro is amazon's multimodal Bedrock model at $0.80/$3.20 with a 300K window — an enterprise-integrated generalist, not a frontier model. MAI-Thinking-1 is microsoft's first fully in-house flagship reasoning model — a Claude-class reasoner built independently to cut its OpenAI dependence. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Context window: Amazon Nova Pro holds 1.2× more — 300K (~450 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: MAI-Thinking-1 is the newer model by about 18 months (released June 2, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Amazon Nova Pro
MAI-Thinking-1
Provider
Amazon (US)
Microsoft (US)
Released
December 5, 2024
June 2, 2026
Context window
300K (~450 pages)
256K (~384 pages)
Price (in/out)
$0.8/$3.2 per 1M tokens
Not published
Open weight?
No — API only
No — API only
Modalities
text, image, video, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Multimodal input across text, image and video at $0.80/$3.20
Amazon Nova Pro
Amazon's multimodal Bedrock model at $0.80/$3.20 with a 300K window — an enterprise-integrated generalist, not a frontier model — and it carries the larger 300K context.
Deep AWS and Bedrock integration for enterprise pipelines
Amazon Nova Pro
Amazon Nova Pro lists deep AWS and Bedrock integration for enterprise pipelines among its strengths; MAI-Thinking-1 does not.
Balanced cost-to-capability for general business tasks
Amazon Nova Pro
Amazon Nova Pro lists balanced cost-to-capability for general business tasks among its strengths; MAI-Thinking-1 does not.
Very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%)
MAI-Thinking-1
Amazon Nova Pro is comparatively weak here — not a frontier reasoning or coding model against 2026 flagships
Microsoft's first in-house flagship reasoner, trained without OpenAI distillation
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 is the newer of the two.
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; Amazon Nova Pro does not.
Lowest cost at scale
MAI-Thinking-1
Its weights are open, so at volume you pay for your own hardware instead of Amazon Nova Pro's $0.8/$3.2 per 1M tokens.
Largest single-prompt input
Amazon Nova Pro
Its 300K window is about 1.2× larger than MAI-Thinking-1's 256K, fitting roughly 450 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ MAI-Thinking-1
At Not published it undercuts Amazon Nova Pro, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Amazon Nova Pro
Larger 300K window fits more in one prompt.
Anyone whose priority is multimodal input across text, image and video at $0.80/$3.20
→ Amazon Nova Pro
It is specifically built for that.
Anyone whose priority is very strong math reasoning (aime 2025 97%, aime 2026 94.5%)
→ MAI-Thinking-1
That is its strongest area.
Amazon Nova Pro: where it fits
Amazon's multimodal Bedrock model at $0.80/$3.20 with a 300K window — an enterprise-integrated generalist, not a frontier model. Released December 5, 2024 by Amazon, it is built for multimodal input across text, image and video at $0.80/$3.20, deep AWS and Bedrock integration for enterprise pipelines, balanced cost-to-capability for general business tasks, and a 300K context for long documents and mixed media.
Its trade-offs are real: not a frontier reasoning or coding model against 2026 flagships, no published SWE-Bench Verified score, best value is realised inside the AWS ecosystem, and late-2024 model — older than most of the field here. At $0.8 in / $3.2 out per million tokens, it sits in the budget price band.
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 June 2, 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: closed and in private preview — no open weights, no published pricing, thin availability, and benchmarks are largely self-reported.
The bottom line for this matchup
Amazon Nova Pro and MAI-Thinking-1 overlap enough that the right pick depends on your specific job. MAI-Thinking-1 costs less per token; Amazon Nova Pro holds the larger context; and each leads in its own area — Amazon Nova Pro for multimodal input across text, image and video at $0.80/$3.20, MAI-Thinking-1 for very strong math reasoning (aime 2025 97%, aime 2026 94.5%). Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Amazon Nova Pro and MAI-Thinking-1 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 Amazon Nova Pro or MAI-Thinking-1 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, Amazon Nova Pro leans toward multimodal input across text, image and video at $0.80/$3.20 while MAI-Thinking-1 leans toward very strong math reasoning (aime 2025 97%, aime 2026 94.5%), and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Amazon Nova Pro or MAI-Thinking-1?
MAI-Thinking-1 is cheaper — $0.8/$3.2 per 1M tokens vs Not published.
Which has the bigger context window?
Amazon Nova Pro — 300K vs 256K, about 1.2× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Amazon Nova Pro and MAI-Thinking-1 together?
Yes — a multi-model platform like LumiChats gives you Amazon Nova Pro, MAI-Thinking-1 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, Amazon Nova Pro or MAI-Thinking-1?
MAI-Thinking-1 — released June 2, 2026, about 18 months after Amazon Nova Pro.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.