Model comparison
GPT-4.1 vs GPT-4.1 nano
Head-to-head evidence from 17 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 #108 (Supported); 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 and GPT-4.1 nano share 17 comparable benchmark results. 3 of 8 categories are comparable. 3 results are unique to GPT-4.1; 4 to GPT-4.1 nano.
Updated July 22, 2026- Shared results
- 17
- GPT-4.1 only
- 3
- GPT-4.1 nano only
- 4
- Comparable categories
- 3 / 8
GPT-4.1 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 17 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 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 is clearly ahead on the BenchAlign aggregate, 51.11 to 42.06. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
GPT-4.1's sharpest advantage is in knowledge, where it averages 66.3 against 50.3. The single biggest benchmark swing on the page is GPQA, 66.3% to 50.3%.
GPT-4.1 is also the more expensive model on tokens at $2.00 input / $8.00 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for GPT-4.1 nano. That is roughly 20.0x 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 | Δ | GPT-4.1 nano |
|---|---|---|---|
| Knowledge | GPT-4.166.3 | Margin← 16.0 | GPT-4.1 nano50.3 |
| Inst. Following | GPT-4.187.4 | Margin← 4.2 | GPT-4.1 nano83.2 |
| Math | GPT-4.14.1 | Margin← 3.1 | GPT-4.1 nano1.0 |
| Coding | GPT-4.154.6 | 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 66.3%B 50.3%Winner: GPT-4.1Δ 16GPQA: GPT-4.1 scored 66.3%; GPT-4.1 nano scored 50.3%. GPT-4.1 wins this benchmark. - Source ↗
FrontierMath v2 (Tiers 1-3)
MathA 5.517%B 1.034%Winner: GPT-4.1Δ 4.5FrontierMath v2 (Tiers 1-3): GPT-4.1 scored 5.517%; GPT-4.1 nano scored 1.034%. GPT-4.1 wins this benchmark. - Source ↗
IFEval
Inst. FollowingA 87.4%B 83.2%Winner: GPT-4.1Δ 4.2IFEval: GPT-4.1 scored 87.4%; GPT-4.1 nano scored 83.2%. GPT-4.1 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-4.1 | GPT-4.1 nano | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-4.1$2 input / $8 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-4.1108 tok/s | GPT-4.1 nano181 tok/s | GPT-4.1 nano has the higher measured throughput. |
| First-answer latencyseconds to first token | GPT-4.11.02 s | GPT-4.1 nano0.63 s | GPT-4.1 nano reaches the first token sooner. |
| Context windowmaximum listed tokens | GPT-4.11M | GPT-4.1 nano1M | Listed context windows are equal. |
Benchmark Deep Dive
Agentic5 benchmarks
Coding3 benchmarks
Reasoning2 benchmarks
KnowledgeGPT-4.1 wins8 benchmarks
| Benchmark | GPT-4.1 | GPT-4.1 nano | Result |
|---|---|---|---|
| MMLUSource | 90.2% | 80.1% | GPT-4.1 leads |
| GPQASource | 66.3% | 50.3% | GPT-4.1 leads |
| Artificial Analysis Intelligence IndexSource | 19.4% | 9.6% | GPT-4.1 leads |
| AA-GPQA DiamondSource | 66.6% | 51.2% | GPT-4.1 leads |
| AA-HLESource | 4.6% | 3.9% | GPT-4.1 leads |
| AA-Omniscience IndexSource | -36.2% | -56.4% | GPT-4.1 leads |
| AA-Omniscience AccuracySource | 24.2% | 13.3% | GPT-4.1 leads |
| AA-Omniscience Hallucination RateSource | 79.6% | 80.4% | GPT-4.1 leads |
MathGPT-4.1 wins2 benchmarks
Multimodal2 benchmarks
Frequently Asked Questions (4)
Which is better, GPT-4.1 or GPT-4.1 nano?
GPT-4.1 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 is ahead on BenchLM's BenchAlign leaderboard 51.11 to 42.06.
Which is better for knowledge tasks, GPT-4.1 or GPT-4.1 nano?
GPT-4.1 has the edge for knowledge tasks in this comparison, averaging 66.3 versus 50.3. Inside this category, AA-Omniscience Index is the benchmark that creates the most daylight between them.
Which is better for math, GPT-4.1 or GPT-4.1 nano?
GPT-4.1 has the edge for math in this comparison, averaging 4.1 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 or GPT-4.1 nano?
GPT-4.1 has the edge for instruction following in this comparison, averaging 87.4 versus 83.2. Inside this category, AA-IFBench is the benchmark that creates the most daylight between them.
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