Both are OpenAI models. GPT-5.4 Nano is the newer, generally stronger default; reach for GPT-5.4 Mini when a specific cost or latency profile matters more than the latest capabilities.
GPT-5.4 Mini and GPT-5.4 Nano are both OpenAI models, so the real question is not which lab to trust but which tier fits your workload and budget. GPT-5.4 Mini is openAI's free, fast workhorse — capable general AI with no subscription needed. 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. Since both come from the same lab, the comparison below focuses on the tier-and-cost trade-offs that actually separate them.
Key differences
Price: GPT-5.4 Nano is about 3.8× cheaper on input ($0.2/$1.25 per 1M tokens vs $0.75/$4.5 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: both advertise 400K (~600 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Specifications
Spec
GPT-5.4 Mini
GPT-5.4 Nano
Provider
OpenAI (US)
OpenAI (US)
Released
March 17, 2026
March 17, 2026
Context window
400K (~600 pages)
400K (~600 pages)
Price (in/out)
$0.75/$4.5 per 1M tokens
$0.2/$1.25 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Free for every ChatGPT user: GPT-5.4 Mini — GPT-5.4 Mini lists free for every ChatGPT user among its strengths; GPT-5.4 Nano does not.
Fast, low-cost general tasks: GPT-5.4 Mini — GPT-5.4 Mini lists fast, low-cost general tasks among its strengths; GPT-5.4 Nano does not.
Subagent capabilities: GPT-5.4 Mini — GPT-5.4 Mini lists subagent capabilities among its strengths; GPT-5.4 Nano does not.
Cheapest GPT-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work: GPT-5.4 Nano — At $0.2/$1.25 per 1M tokens it undercuts GPT-5.4 Mini ($0.75/$4.5 per 1M tokens), and that gap compounds at volume.
Classification, extraction, ranking and sub-agent execution at scale: 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 runs cheaper at $0.2/$1.25 per 1M tokens.
A 400K context in the smallest, fastest GPT-5.4 variant: GPT-5.4 Nano — GPT-5.4 Mini is comparatively weak here — smaller context than flagship models
Lowest cost at scale: GPT-5.4 Nano — At $0.2/$1.25 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume: GPT-5.4 Nano — At $0.2/$1.25 per 1M tokens it undercuts GPT-5.4 Mini, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is free for every chatgpt user: GPT-5.4 Mini — It is specifically built for that.
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 — That is its strongest area.
GPT-5.4 Mini: where it fits
OpenAI's free, fast workhorse — capable general AI with no subscription needed. Released March 17, 2026 by OpenAI, it is built for free for every ChatGPT user, fast, low-cost general tasks, subagent capabilities, and native multimodal reasoning.
Its trade-offs are real: smaller context than flagship models, and not for the hardest reasoning. At $0.75 in / $4.5 out per million tokens, it sits in the budget price band.
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: 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.
The bottom line for this matchup
Because GPT-5.4 Mini and GPT-5.4 Nano come from the same lab (OpenAI), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. GPT-5.4 Nano is the more capable, more recent option; the other earns its place only when its price or latency profile fits a specific job better. Most teams should default to GPT-5.4 Nano and drop down only with a concrete reason.
Frequently asked questions
Is GPT-5.4 Mini or GPT-5.4 Nano 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 Mini leans toward free for every chatgpt user while GPT-5.4 Nano leans toward cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.4 Mini or GPT-5.4 Nano?
GPT-5.4 Nano is cheaper — $0.75/$4.5 per 1M tokens vs $0.2/$1.25 per 1M tokens, roughly 3.8× apart on input.
Which has the bigger context window?
Both advertise 400K (~600 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Should I upgrade from GPT-5.4 Nano to GPT-5.4 Mini?
Since both are OpenAI models, the newer one (GPT-5.4 Nano) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, GPT-5.4 Mini or GPT-5.4 Nano?
They were released around the same time (March 17, 2026 and March 17, 2026).
GPT-5.4 Mini vs GPT-5.4 Nano
OpenAI · US | OpenAI · US · Updated June 2026
Quick verdict
Both are OpenAI models. GPT-5.4 Nano is the newer, generally stronger default; reach for GPT-5.4 Mini when a specific cost or latency profile matters more than the latest capabilities.
GPT-5.4 Mini and GPT-5.4 Nano are both OpenAI models, so the real question is not which lab to trust but which tier fits your workload and budget. GPT-5.4 Mini is openAI's free, fast workhorse — capable general AI with no subscription needed. 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. Since both come from the same lab, the comparison below focuses on the tier-and-cost trade-offs that actually separate them.
Key differences at a glance
▸Price: GPT-5.4 Nano is about 3.8× cheaper on input ($0.2/$1.25 per 1M tokens vs $0.75/$4.5 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: both advertise 400K (~600 pages). Tie on paper — test on your own long inputs, since usable recall varies by model.
Side-by-side specs
Spec
GPT-5.4 Mini
GPT-5.4 Nano
Provider
OpenAI (US)
OpenAI (US)
Released
March 17, 2026
March 17, 2026
Context window
400K (~600 pages)
400K (~600 pages)
Price (in/out)
$0.75/$4.5 per 1M tokens
$0.2/$1.25 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, image, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Free for every ChatGPT user
GPT-5.4 Mini
GPT-5.4 Mini lists free for every ChatGPT user among its strengths; GPT-5.4 Nano does not.
Fast, low-cost general tasks
GPT-5.4 Mini
GPT-5.4 Mini lists fast, low-cost general tasks among its strengths; GPT-5.4 Nano does not.
Subagent capabilities
GPT-5.4 Mini
GPT-5.4 Mini lists subagent capabilities among its strengths; GPT-5.4 Nano does not.
Cheapest GPT-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work
GPT-5.4 Nano
At $0.2/$1.25 per 1M tokens it undercuts GPT-5.4 Mini ($0.75/$4.5 per 1M tokens), and that gap compounds at volume.
Classification, extraction, ranking and sub-agent execution at scale
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 runs cheaper at $0.2/$1.25 per 1M tokens.
A 400K context in the smallest, fastest GPT-5.4 variant
GPT-5.4 Nano
GPT-5.4 Mini is comparatively weak here — smaller context than flagship models
Lowest cost at scale
GPT-5.4 Nano
At $0.2/$1.25 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GPT-5.4 Nano
At $0.2/$1.25 per 1M tokens it undercuts GPT-5.4 Mini, and on millions of tokens that margin decides the monthly bill.
Anyone whose priority is free for every chatgpt user
→ GPT-5.4 Mini
It is specifically built for that.
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
That is its strongest area.
GPT-5.4 Mini: where it fits
OpenAI's free, fast workhorse — capable general AI with no subscription needed. Released March 17, 2026 by OpenAI, it is built for free for every ChatGPT user, fast, low-cost general tasks, subagent capabilities, and native multimodal reasoning.
Its trade-offs are real: smaller context than flagship models, and not for the hardest reasoning. At $0.75 in / $4.5 out per million tokens, it sits in the budget price band.
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: 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.
The bottom line for this matchup
Because GPT-5.4 Mini and GPT-5.4 Nano come from the same lab (OpenAI), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. GPT-5.4 Nano is the more capable, more recent option; the other earns its place only when its price or latency profile fits a specific job better. Most teams should default to GPT-5.4 Nano and drop down only with a concrete reason.
Want both GPT-5.4 Mini and GPT-5.4 Nano 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 Mini or GPT-5.4 Nano 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 Mini leans toward free for every chatgpt user while GPT-5.4 Nano leans toward cheapest gpt-5.4-family tier at $0.20/$1.25 — built for high-volume, latency-sensitive work, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-5.4 Mini or GPT-5.4 Nano?
GPT-5.4 Nano is cheaper — $0.75/$4.5 per 1M tokens vs $0.2/$1.25 per 1M tokens, roughly 3.8× apart on input.
Which has the bigger context window?
Both advertise 400K (~600 pages). Remember advertised ≠ usable: recall typically degrades before the ceiling.
Should I upgrade from GPT-5.4 Nano to GPT-5.4 Mini?
Since both are OpenAI models, the newer one (GPT-5.4 Nano) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, GPT-5.4 Mini or GPT-5.4 Nano?
They were released around the same time (March 17, 2026 and March 17, 2026).
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.