Both are OpenAI models. GPT-4.1 Mini is the newer, generally stronger default; reach for GPT-4o mini when its lower price or a specific cost or latency profile matters more than the latest capabilities.
GPT-4.1 Mini and GPT-4o mini are both OpenAI models, so the real question is not which lab to trust but which tier fits your workload and budget. GPT-4.1 Mini is a cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT. GPT-4o mini is openAI's budget small multimodal model — cheap, fast text-and-vision intelligence that outscored peer small models like Gemini 1.5 Flash and Claude 3 Haiku on MMLU and HumanEval at launch. 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-4o mini is about 2.7× cheaper on input ($0.15/$0.6 per 1M tokens vs $0.4/$1.6 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: GPT-4.1 Mini holds 8.2× more — 1M (~1,571 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.
Recency: GPT-4.1 Mini is the newer model by about 9 months (released April 14, 2025), usually meaning fresher training data and capabilities.
Specifications
Spec
GPT-4.1 Mini
GPT-4o mini
Provider
OpenAI (US)
OpenAI (US)
Released
April 14, 2025
July 18, 2024
Context window
1M (~1,571 pages)
128K (~192 pages)
Price (in/out)
$0.4/$1.6 per 1M tokens
$0.15/$0.6 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, image
SWE-Bench Verified
23.6%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Very cheap high-volume text work at $0.40 in / $1.60 out per million tokens: GPT-4.1 Mini — Its 1M window holds about 8.2× more than GPT-4o mini's 128K in a single prompt.
Instruction following above its weight class — 84.1% on IFEval, beating GPT-4o: GPT-4.1 Mini — A cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT — and it carries the larger 1M context.
Multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini: GPT-4.1 Mini — A cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT — and it is the newer of the two.
Very low cost per token for its capability tier: GPT-4o mini — At $0.15/$0.6 per 1M tokens it undercuts GPT-4.1 Mini ($0.4/$1.6 per 1M tokens), and that gap compounds at volume.
Strong coding for a small model (87.2% HumanEval): GPT-4o mini — GPT-4.1 Mini is comparatively weak here — weak at agentic coding — its 23.6% on SWE-Bench Verified sits below GPT-4o's 33.2%
Leading MMLU among peer small models (82%): GPT-4o mini — OpenAI's budget small multimodal model — cheap, fast text-and-vision intelligence that outscored peer small models like Gemini 1.5 Flash and Claude 3 Haiku on MMLU and HumanEval at launch — and it runs cheaper at $0.15/$0.6 per 1M tokens.
Lowest cost at scale: GPT-4o mini — At $0.15/$0.6 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: GPT-4.1 Mini — Its 1M window is about 8.2× larger than GPT-4o mini's 128K, fitting roughly 1,571 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: GPT-4o mini — At $0.15/$0.6 per 1M tokens it undercuts GPT-4.1 Mini, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: GPT-4.1 Mini — Larger 1M window fits more in one prompt.
Anyone whose priority is very cheap high-volume text work at $0.40 in / $1.60 out per million tokens: GPT-4.1 Mini — It is specifically built for that.
Anyone whose priority is very low cost per token for its capability tier: GPT-4o mini — That is its strongest area.
GPT-4.1 Mini: where it fits
A cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT. Released April 14, 2025 by OpenAI, it is built for very cheap high-volume text work at $0.40 in / $1.60 out per million tokens, instruction following above its weight class — 84.1% on IFEval, beating GPT-4o, multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini, and a full 1M context at flat pricing, with no long-context premium.
Its trade-offs are real: weak at agentic coding — its 23.6% on SWE-Bench Verified sits below GPT-4o's 33.2%, retired from ChatGPT in February 2026, and OpenAI's own docs now point users to GPT-5 mini instead, and a June 2024 knowledge cutoff, now roughly two years stale, and no reasoning mode. At $0.4 in / $1.6 out per million tokens, it sits in the budget price band.
GPT-4o mini: where it fits
OpenAI's budget small multimodal model — cheap, fast text-and-vision intelligence that outscored peer small models like Gemini 1.5 Flash and Claude 3 Haiku on MMLU and HumanEval at launch. Released July 18, 2024 by OpenAI, it is built for very low cost per token for its capability tier, strong coding for a small model (87.2% HumanEval), leading MMLU among peer small models (82%), and text and image (vision) understanding in the API.
Its trade-offs: only 128K context with an October 2023 knowledge cutoff, and weaker on hard reasoning and coding than frontier models. At $0.15 in / $0.6 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Because GPT-4.1 Mini and GPT-4o mini come from the same lab (OpenAI), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. GPT-4.1 Mini 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-4.1 Mini and drop down only with a concrete reason.
Frequently asked questions
Is GPT-4.1 Mini or GPT-4o mini better for coding?
Public SWE-Bench figures are not available for GPT-4o mini, so the honest test is your own repository — run an identical real bug through both. By design, GPT-4.1 Mini leans toward very cheap high-volume text work at $0.40 in / $1.60 out per million tokens while GPT-4o mini leans toward very low cost per token for its capability tier, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-4.1 Mini or GPT-4o mini?
GPT-4o mini is cheaper — $0.4/$1.6 per 1M tokens vs $0.15/$0.6 per 1M tokens, roughly 2.7× apart on input.
Which has the bigger context window?
GPT-4.1 Mini — 1M vs 128K, about 8.2× larger. Useful only if the model actually reasons over the full window, which not all do.
Should I upgrade from GPT-4o mini to GPT-4.1 Mini?
Since both are OpenAI models, the newer one (GPT-4.1 Mini) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, GPT-4.1 Mini or GPT-4o mini?
GPT-4.1 Mini — released April 14, 2025, about 9 months after GPT-4o mini.
GPT-4.1 Mini vs GPT-4o mini
OpenAI · US | OpenAI · US · Updated June 2026
Quick verdict
Both are OpenAI models. GPT-4.1 Mini is the newer, generally stronger default; reach for GPT-4o mini when its lower price or a specific cost or latency profile matters more than the latest capabilities.
GPT-4.1 Mini and GPT-4o mini are both OpenAI models, so the real question is not which lab to trust but which tier fits your workload and budget. GPT-4.1 Mini is a cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT. GPT-4o mini is openAI's budget small multimodal model — cheap, fast text-and-vision intelligence that outscored peer small models like Gemini 1.5 Flash and Claude 3 Haiku on MMLU and HumanEval at launch. 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-4o mini is about 2.7× cheaper on input ($0.15/$0.6 per 1M tokens vs $0.4/$1.6 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: GPT-4.1 Mini holds 8.2× more — 1M (~1,571 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.
▸Recency: GPT-4.1 Mini is the newer model by about 9 months (released April 14, 2025), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
GPT-4.1 Mini
GPT-4o mini
Provider
OpenAI (US)
OpenAI (US)
Released
April 14, 2025
July 18, 2024
Context window
1M (~1,571 pages)
128K (~192 pages)
Price (in/out)
$0.4/$1.6 per 1M tokens
$0.15/$0.6 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, code
text, image
SWE-Bench Verified
23.6%
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Very cheap high-volume text work at $0.40 in / $1.60 out per million tokens
GPT-4.1 Mini
Its 1M window holds about 8.2× more than GPT-4o mini's 128K in a single prompt.
Instruction following above its weight class — 84.1% on IFEval, beating GPT-4o
GPT-4.1 Mini
A cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT — and it carries the larger 1M context.
Multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini
GPT-4.1 Mini
A cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT — and it is the newer of the two.
Very low cost per token for its capability tier
GPT-4o mini
At $0.15/$0.6 per 1M tokens it undercuts GPT-4.1 Mini ($0.4/$1.6 per 1M tokens), and that gap compounds at volume.
Strong coding for a small model (87.2% HumanEval)
GPT-4o mini
GPT-4.1 Mini is comparatively weak here — weak at agentic coding — its 23.6% on SWE-Bench Verified sits below GPT-4o's 33.2%
Leading MMLU among peer small models (82%)
GPT-4o mini
OpenAI's budget small multimodal model — cheap, fast text-and-vision intelligence that outscored peer small models like Gemini 1.5 Flash and Claude 3 Haiku on MMLU and HumanEval at launch — and it runs cheaper at $0.15/$0.6 per 1M tokens.
Lowest cost at scale
GPT-4o mini
At $0.15/$0.6 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
GPT-4.1 Mini
Its 1M window is about 8.2× larger than GPT-4o mini's 128K, fitting roughly 1,571 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GPT-4o mini
At $0.15/$0.6 per 1M tokens it undercuts GPT-4.1 Mini, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ GPT-4.1 Mini
Larger 1M window fits more in one prompt.
Anyone whose priority is very cheap high-volume text work at $0.40 in / $1.60 out per million tokens
→ GPT-4.1 Mini
It is specifically built for that.
Anyone whose priority is very low cost per token for its capability tier
→ GPT-4o mini
That is its strongest area.
GPT-4.1 Mini: where it fits
A cheap, fast 1M-context workhorse with strong instruction following but weak coding — already retired from ChatGPT. Released April 14, 2025 by OpenAI, it is built for very cheap high-volume text work at $0.40 in / $1.60 out per million tokens, instruction following above its weight class — 84.1% on IFEval, beating GPT-4o, multi-turn coherence for its tier — 35.8% on MultiChallenge, roughly 1.8x GPT-4o mini, and a full 1M context at flat pricing, with no long-context premium.
Its trade-offs are real: weak at agentic coding — its 23.6% on SWE-Bench Verified sits below GPT-4o's 33.2%, retired from ChatGPT in February 2026, and OpenAI's own docs now point users to GPT-5 mini instead, and a June 2024 knowledge cutoff, now roughly two years stale, and no reasoning mode. At $0.4 in / $1.6 out per million tokens, it sits in the budget price band.
GPT-4o mini: where it fits
OpenAI's budget small multimodal model — cheap, fast text-and-vision intelligence that outscored peer small models like Gemini 1.5 Flash and Claude 3 Haiku on MMLU and HumanEval at launch. Released July 18, 2024 by OpenAI, it is built for very low cost per token for its capability tier, strong coding for a small model (87.2% HumanEval), leading MMLU among peer small models (82%), and text and image (vision) understanding in the API.
Its trade-offs: only 128K context with an October 2023 knowledge cutoff, and weaker on hard reasoning and coding than frontier models. At $0.15 in / $0.6 out per million tokens, it sits in the budget price band.
The bottom line for this matchup
Because GPT-4.1 Mini and GPT-4o mini come from the same lab (OpenAI), they share the same training philosophy and ecosystem — the decision is purely tier vs. cost. GPT-4.1 Mini 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-4.1 Mini and drop down only with a concrete reason.
Want both GPT-4.1 Mini and GPT-4o mini 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.
Public SWE-Bench figures are not available for GPT-4o mini, so the honest test is your own repository — run an identical real bug through both. By design, GPT-4.1 Mini leans toward very cheap high-volume text work at $0.40 in / $1.60 out per million tokens while GPT-4o mini leans toward very low cost per token for its capability tier, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, GPT-4.1 Mini or GPT-4o mini?
GPT-4o mini is cheaper — $0.4/$1.6 per 1M tokens vs $0.15/$0.6 per 1M tokens, roughly 2.7× apart on input.
Which has the bigger context window?
GPT-4.1 Mini — 1M vs 128K, about 8.2× larger. Useful only if the model actually reasons over the full window, which not all do.
Should I upgrade from GPT-4o mini to GPT-4.1 Mini?
Since both are OpenAI models, the newer one (GPT-4.1 Mini) is usually the better default unless you need a specific cost or latency profile from the other.
Which is newer, GPT-4.1 Mini or GPT-4o mini?
GPT-4.1 Mini — released April 14, 2025, about 9 months after GPT-4o mini.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.