Pick GPT-5.3-Codex for dedicated coding agent or cli and ide integration. 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-5.3-Codex (OpenAI) and MAI-Thinking-1 (Microsoft) are two of the models people most often weigh against each other in 2026. GPT-5.3-Codex is openAI's coding-specialized agent model for autonomous software engineering. 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-5.3-Codex 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-5.3-Codex
MAI-Thinking-1
Provider
OpenAI (US)
Microsoft (US)
Released
February 24, 2026
June 2, 2026
Context window
400K (~600 pages)
256K (~384 pages)
Price (in/out)
$1.75/$14 per 1M tokens
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
Dedicated coding agent: GPT-5.3-Codex — A core design strength of GPT-5.3-Codex.
CLI and IDE integration: GPT-5.3-Codex — A core design strength of GPT-5.3-Codex.
Autonomous software tasks: GPT-5.3-Codex — A core design strength of GPT-5.3-Codex.
Very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%): MAI-Thinking-1 — A core design strength of MAI-Thinking-1.
Microsoft's first in-house flagship reasoner, trained without OpenAI distillation: MAI-Thinking-1 — A core design strength of MAI-Thinking-1.
Efficient reasoning at low token cost for its class: MAI-Thinking-1 — A core design strength of MAI-Thinking-1.
Lowest cost at scale: MAI-Thinking-1 — At Not published, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: GPT-5.3-Codex — Its 400K window is about 1.6× larger, 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-5.3-Codex, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GPT-5.3-Codex — Larger 400K window fits more in one prompt.
Anyone whose priority is dedicated coding agent: GPT-5.3-Codex — 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-5.3-Codex: where it fits
OpenAI's coding-specialized agent model for autonomous software engineering. Released February 24, 2026 by OpenAI, it is built for dedicated coding agent, cLI and IDE integration, autonomous software tasks, and tool calling.
Its trade-offs are real: coding-specialized, narrower general use, and retired in favor of GPT-5.5 Codex. At $1.75 in / $14 out per million tokens, it sits in the mid 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-5.3-Codex and MAI-Thinking-1 overlap enough that the right pick depends on your specific job. MAI-Thinking-1 costs less per token; GPT-5.3-Codex holds the larger context; and each leads in its own area — GPT-5.3-Codex for dedicated coding agent, 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-5.3-Codex 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-5.3-Codex leans toward dedicated coding agent 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-5.3-Codex or MAI-Thinking-1?
MAI-Thinking-1 is cheaper — $1.75/$14 per 1M tokens vs Not published.
Which has the bigger context window?
GPT-5.3-Codex — 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-5.3-Codex and MAI-Thinking-1 together?
Yes — a multi-model platform like LumiChats gives you GPT-5.3-Codex, 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-5.3-Codex or MAI-Thinking-1?
MAI-Thinking-1 — released June 2, 2026, about 3 months after GPT-5.3-Codex.
GPT-5.3-Codex vs MAI-Thinking-1
OpenAI · US | Microsoft · US · Updated June 2026
Quick verdict
Pick GPT-5.3-Codex for dedicated coding agent or cli and ide integration. 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-5.3-Codex (OpenAI) and MAI-Thinking-1 (Microsoft) are two of the models people most often weigh against each other in 2026. GPT-5.3-Codex is openAI's coding-specialized agent model for autonomous software engineering. 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-5.3-Codex 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-5.3-Codex
MAI-Thinking-1
Provider
OpenAI (US)
Microsoft (US)
Released
February 24, 2026
June 2, 2026
Context window
400K (~600 pages)
256K (~384 pages)
Price (in/out)
$1.75/$14 per 1M tokens
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
Dedicated coding agent
GPT-5.3-Codex
A core design strength of GPT-5.3-Codex.
CLI and IDE integration
GPT-5.3-Codex
A core design strength of GPT-5.3-Codex.
Autonomous software tasks
GPT-5.3-Codex
A core design strength of GPT-5.3-Codex.
Very strong math reasoning (AIME 2025 97%, AIME 2026 94.5%)
MAI-Thinking-1
A core design strength of MAI-Thinking-1.
Microsoft's first in-house flagship reasoner, trained without OpenAI distillation
MAI-Thinking-1
A core design strength of MAI-Thinking-1.
Efficient reasoning at low token cost for its class
MAI-Thinking-1
A core design strength of MAI-Thinking-1.
Lowest cost at scale
MAI-Thinking-1
At Not published, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
GPT-5.3-Codex
Its 400K window is about 1.6× larger, 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-5.3-Codex, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GPT-5.3-Codex
Larger 400K window fits more in one prompt.
Anyone whose priority is dedicated coding agent
→ GPT-5.3-Codex
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-5.3-Codex: where it fits
OpenAI's coding-specialized agent model for autonomous software engineering. Released February 24, 2026 by OpenAI, it is built for dedicated coding agent, cLI and IDE integration, autonomous software tasks, and tool calling.
Its trade-offs are real: coding-specialized, narrower general use, and retired in favor of GPT-5.5 Codex. At $1.75 in / $14 out per million tokens, it sits in the mid 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-5.3-Codex and MAI-Thinking-1 overlap enough that the right pick depends on your specific job. MAI-Thinking-1 costs less per token; GPT-5.3-Codex holds the larger context; and each leads in its own area — GPT-5.3-Codex for dedicated coding agent, 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-5.3-Codex 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-5.3-Codex 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-5.3-Codex leans toward dedicated coding agent 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-5.3-Codex or MAI-Thinking-1?
MAI-Thinking-1 is cheaper — $1.75/$14 per 1M tokens vs Not published.
Which has the bigger context window?
GPT-5.3-Codex — 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-5.3-Codex and MAI-Thinking-1 together?
Yes — a multi-model platform like LumiChats gives you GPT-5.3-Codex, 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-5.3-Codex or MAI-Thinking-1?
MAI-Thinking-1 — released June 2, 2026, about 3 months after GPT-5.3-Codex.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.