Pick GPT-5.4 Nano for cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work or classification, extraction, ranking and sub-agent execution at scale. 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.
GPT-5.4 Nano (OpenAI) and MAI-Thinking-1 (Microsoft) are two of the models people most often weigh against each other in 2026. GPT-5.4 Nano is openAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning. 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: GPT-5.4 Nano holds 1.6× more — 400K (~600 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 3 months (released June 2, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
GPT-5.4 Nano
MAI-Thinking-1
Provider
OpenAI (US)
Microsoft (US)
Released
March 17, 2026
June 2, 2026
Context window
400K (~600 pages)
256K (~384 pages)
Price (in/out)
$0.2/$1.25 per 1M tokens
Not published
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Cheapest GPT-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work: GPT-5.4 Nano — OpenAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning — and it carries the larger 400K context.
Classification, extraction, ranking and sub-agent execution at scale: GPT-5.4 Nano — GPT-5.4 Nano lists classification, extraction, ranking and sub-agent execution at scale among its strengths; MAI-Thinking-1 does not.
A 400K context in the smallest, fastest GPT-5.4 variant: GPT-5.4 Nano — Its 400K window holds about 1.6× more than MAI-Thinking-1's 256K in a single prompt.
Very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%): MAI-Thinking-1 — GPT-5.4 Nano is comparatively weak here — a nano tier — not built for hard reasoning or frontier coding
Microsoft's first in-house flagship reasoner, trained without OpenAI distillation: MAI-Thinking-1 — GPT-5.4 Nano is comparatively weak here — no published SWE-Bench Verified score (OpenAI reported SWE-Bench Pro instead)
Efficient reasoning at low token cost for its class: 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.
Lowest cost at scale: MAI-Thinking-1 — Its weights are open, so at volume you pay for your own hardware instead of GPT-5.4 Nano's $0.2/$1.25 per 1M tokens.
Largest single-prompt input: GPT-5.4 Nano — Its 400K window is about 1.6× larger than MAI-Thinking-1's 256K, fitting roughly 600 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: MAI-Thinking-1 — At Not published it undercuts GPT-5.4 Nano, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GPT-5.4 Nano — Larger 400K window fits more in one prompt.
Anyone whose priority is cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work: GPT-5.4 Nano — 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.
GPT-5.4 Nano: where it fits
OpenAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning. Released March 17, 2026 by OpenAI, it is built for cheapest GPT-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work, classification, extraction, ranking and sub-agent execution at scale, a 400K context in the smallest, fastest GPT-5.4 variant, and text and image input for cheap multimodal pipelines.
Its trade-offs are real: a nano tier — not built for hard reasoning or frontier coding, no published SWE-Bench Verified score (OpenAI reported SWE-Bench Pro instead), outclassed by GPT-5.4 and GPT-5.4 Mini whenever a task needs real depth, and image input only — no audio or video. At $0.2 in / $1.25 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
GPT-5.4 Nano and MAI-Thinking-1 overlap enough that the right pick depends on your specific job. MAI-Thinking-1 costs less per token; GPT-5.4 Nano holds the larger context; and each leads in its own area — GPT-5.4 Nano for cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work, 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 GPT-5.4 Nano 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, GPT-5.4 Nano leans toward cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work 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, GPT-5.4 Nano or MAI-Thinking-1?
MAI-Thinking-1 is cheaper — $0.2/$1.25 per 1M tokens vs Not published.
Which has the bigger context window?
GPT-5.4 Nano — 400K vs 256K, about 1.6× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-5.4 Nano and MAI-Thinking-1 together?
Yes — a multi-model platform like LumiChats gives you GPT-5.4 Nano, 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, GPT-5.4 Nano or MAI-Thinking-1?
MAI-Thinking-1 — released June 2, 2026, about 3 months after GPT-5.4 Nano.
GPT-5.4 Nano vs MAI-Thinking-1
OpenAI · US | Microsoft · US · Updated June 2026
Quick verdict
Pick GPT-5.4 Nano for cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work or classification, extraction, ranking and sub-agent execution at scale. 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.
GPT-5.4 Nano (OpenAI) and MAI-Thinking-1 (Microsoft) are two of the models people most often weigh against each other in 2026. GPT-5.4 Nano is openAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning. 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: GPT-5.4 Nano holds 1.6× more — 400K (~600 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 3 months (released June 2, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GPT-5.4 Nano
MAI-Thinking-1
Provider
OpenAI (US)
Microsoft (US)
Released
March 17, 2026
June 2, 2026
Context window
400K (~600 pages)
256K (~384 pages)
Price (in/out)
$0.2/$1.25 per 1M tokens
Not published
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Cheapest GPT-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work
GPT-5.4 Nano
OpenAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning — and it carries the larger 400K context.
Classification, extraction, ranking and sub-agent execution at scale
GPT-5.4 Nano
GPT-5.4 Nano lists classification, extraction, ranking and sub-agent execution at scale among its strengths; MAI-Thinking-1 does not.
A 400K context in the smallest, fastest GPT-5.4 variant
GPT-5.4 Nano
Its 400K window holds about 1.6× more than MAI-Thinking-1's 256K in a single prompt.
Very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%)
MAI-Thinking-1
GPT-5.4 Nano is comparatively weak here — a nano tier — not built for hard reasoning or frontier coding
Microsoft's first in-house flagship reasoner, trained without OpenAI distillation
MAI-Thinking-1
GPT-5.4 Nano is comparatively weak here — no published SWE-Bench Verified score (OpenAI reported SWE-Bench Pro instead)
Efficient reasoning at low token cost for its class
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.
Lowest cost at scale
MAI-Thinking-1
Its weights are open, so at volume you pay for your own hardware instead of GPT-5.4 Nano's $0.2/$1.25 per 1M tokens.
Largest single-prompt input
GPT-5.4 Nano
Its 400K window is about 1.6× larger than MAI-Thinking-1's 256K, fitting roughly 600 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ MAI-Thinking-1
At Not published it undercuts GPT-5.4 Nano, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GPT-5.4 Nano
Larger 400K window fits more in one prompt.
Anyone whose priority is cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work
→ GPT-5.4 Nano
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.
GPT-5.4 Nano: where it fits
OpenAI's cheapest GPT-5.4 variant at $0.20/$1.25 with a 400K window — a speed-and-cost tier for high-volume tasks, not deep reasoning. Released March 17, 2026 by OpenAI, it is built for cheapest GPT-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work, classification, extraction, ranking and sub-agent execution at scale, a 400K context in the smallest, fastest GPT-5.4 variant, and text and image input for cheap multimodal pipelines.
Its trade-offs are real: a nano tier — not built for hard reasoning or frontier coding, no published SWE-Bench Verified score (OpenAI reported SWE-Bench Pro instead), outclassed by GPT-5.4 and GPT-5.4 Mini whenever a task needs real depth, and image input only — no audio or video. At $0.2 in / $1.25 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
GPT-5.4 Nano and MAI-Thinking-1 overlap enough that the right pick depends on your specific job. MAI-Thinking-1 costs less per token; GPT-5.4 Nano holds the larger context; and each leads in its own area — GPT-5.4 Nano for cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work, 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 GPT-5.4 Nano 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 GPT-5.4 Nano 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, GPT-5.4 Nano leans toward cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work 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, GPT-5.4 Nano or MAI-Thinking-1?
MAI-Thinking-1 is cheaper — $0.2/$1.25 per 1M tokens vs Not published.
Which has the bigger context window?
GPT-5.4 Nano — 400K vs 256K, about 1.6× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both GPT-5.4 Nano and MAI-Thinking-1 together?
Yes — a multi-model platform like LumiChats gives you GPT-5.4 Nano, 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, GPT-5.4 Nano or MAI-Thinking-1?
MAI-Thinking-1 — released June 2, 2026, about 3 months after GPT-5.4 Nano.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.