Model comparison
GPT-4.1 mini vs GPT-4.1 nano
Head-to-head evidence from 21 shared benchmark results across 7 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Sibling matchup inside the GPT-4.1 family.
Public leaderboard positions: GPT-4.1 mini #152 (Estimated); GPT-4.1 nano #161 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-4.1 mini and GPT-4.1 nano share 21 comparable benchmark results. 3 of 8 categories are comparable. 1 result is unique to GPT-4.1 mini; 0 to GPT-4.1 nano.
Updated July 23, 2026- Shared results
- 21
- GPT-4.1 mini only
- 1
- GPT-4.1 nano only
- 0
- Comparable categories
- 3 / 8
GPT-4.1 mini makes more sense if knowledge is the priority, while GPT-4.1 nano is the cleaner fit if you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 21 shared benchmark results across 7 evidence categories; 3 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-4.1 mini and GPT-4.1 nano sit in the same GPT-4.1 family. This page is less about two unrelated model lineages and more about how the siblings trade off on benchmark shape, token costs, and practical limits like context window.
GPT-4.1 mini has the cleaner BenchAlign overall profile here, landing at 44.19 versus 42.06. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
GPT-4.1 mini's sharpest advantage is in knowledge, where it averages 64.2 against 50.3. The single biggest benchmark swing on the page is GPQA, 64.2% to 50.3%.
GPT-4.1 mini is also the more expensive model on tokens at $0.40 input / $1.60 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for GPT-4.1 nano. That is roughly 4.0x on output cost alone.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | GPT-4.1 mini | Δ | GPT-4.1 nano |
|---|---|---|---|
| Knowledge | GPT-4.1 mini64.2 | Margin← 13.9 | GPT-4.1 nano50.3 |
| Inst. Following | GPT-4.1 mini88.5 | Margin← 5.3 | GPT-4.1 nano83.2 |
| Math | GPT-4.1 mini4.5 | Margin← 3.5 | GPT-4.1 nano1.0 |
| Coding | GPT-4.1 mini23.6 | MarginNo overlap | GPT-4.1 nanoNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
GPQA
KnowledgeA 64.2%B 50.3%Winner: GPT-4.1 miniΔ 13.9GPQA: GPT-4.1 mini scored 64.2%; GPT-4.1 nano scored 50.3%. GPT-4.1 mini wins this benchmark. - Source ↗
IFEval
Inst. FollowingA 88.5%B 83.2%Winner: GPT-4.1 miniΔ 5.3IFEval: GPT-4.1 mini scored 88.5%; GPT-4.1 nano scored 83.2%. GPT-4.1 mini wins this benchmark. - Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 4.483%B 1.034%Winner: GPT-4.1 miniΔ 3.4FrontierMath v2 (Tiers 1-3): GPT-4.1 mini scored 4.483%; GPT-4.1 nano scored 1.034%. GPT-4.1 mini wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-4.1 mini | GPT-4.1 nano | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-4.1 mini$0.4 input / $1.6 output | GPT-4.1 nano$0.1 input / $0.4 output | GPT-4.1 nano has the lower combined listed price. |
| Generation speedtokens per second | GPT-4.1 mini80 tok/s | GPT-4.1 nano181 tok/s | GPT-4.1 nano has the higher measured throughput. |
| First-answer latencyseconds to first token | GPT-4.1 mini0.76 s | GPT-4.1 nano0.63 s | GPT-4.1 nano reaches the first token sooner. |
| Context windowmaximum listed tokens | GPT-4.1 mini1M | GPT-4.1 nano1M | Listed context windows are equal. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding3 benchmarks
Reasoning2 benchmarks
KnowledgeGPT-4.1 mini wins8 benchmarks
| Benchmark | GPT-4.1 mini | GPT-4.1 nano | Result |
|---|---|---|---|
| MMLUSource | 87.5% | 80.1% | GPT-4.1 mini leads |
| GPQASource | 64.2% | 50.3% | GPT-4.1 mini leads |
| Artificial Analysis Intelligence IndexSource | 14.8% | 9.6% | GPT-4.1 mini leads |
| AA-GPQA DiamondSource | 66.4% | 51.2% | GPT-4.1 mini leads |
| AA-HLESource | 4.6% | 3.9% | GPT-4.1 mini leads |
| AA-Omniscience IndexSource | -50.1% | -56.4% | GPT-4.1 mini leads |
| AA-Omniscience AccuracySource | 17.5% | 13.3% | GPT-4.1 mini leads |
| AA-Omniscience Hallucination RateSource | 82.0% | 80.4% | GPT-4.1 nano leads |
MathGPT-4.1 mini wins1 benchmarks
| Benchmark | GPT-4.1 mini | GPT-4.1 nano | Result |
|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)Source | 4.483% | 1.034% | GPT-4.1 mini leads |
Multimodal2 benchmarks
Frequently Asked Questions (4)
Which is better, GPT-4.1 mini or GPT-4.1 nano?
GPT-4.1 mini and GPT-4.1 nano are sibling variants in the GPT-4.1 family, so the right pick depends on whether you value the better benchmark line, cheaper tokens, or the larger context window. GPT-4.1 mini is ahead on BenchLM's BenchAlign leaderboard 44.19 to 42.06.
Which is better for knowledge tasks, GPT-4.1 mini or GPT-4.1 nano?
GPT-4.1 mini has the edge for knowledge tasks in this comparison, averaging 64.2 versus 50.3. Inside this category, AA-GPQA Diamond is the benchmark that creates the most daylight between them.
Which is better for math, GPT-4.1 mini or GPT-4.1 nano?
GPT-4.1 mini has the edge for math in this comparison, averaging 4.5 versus 1. Inside this category, FrontierMath v2 (Tiers 1-3) is the benchmark that creates the most daylight between them.
Which is better for instruction following, GPT-4.1 mini or GPT-4.1 nano?
GPT-4.1 mini has the edge for instruction following in this comparison, averaging 88.5 versus 83.2. Inside this category, AA-IFBench is the benchmark that creates the most daylight between them.
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