Model comparison
GPT-4.1 nano vs o3-mini
Head-to-head evidence from 8 shared benchmark results across 4 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-4.1 nano #161 (Estimated); o3-mini #136 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-4.1 nano and o3-mini share 8 comparable benchmark results. 2 of 8 categories are comparable. 13 results are unique to GPT-4.1 nano; 2 to o3-mini.
Updated July 24, 2026- Shared results
- 8
- GPT-4.1 nano only
- 13
- o3-mini only
- 2
- Comparable categories
- 2 / 8
Pick o3-mini if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if you want the cheaper token bill or you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 8 shared benchmark results across 4 evidence categories; 2 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
o3-mini is clearly ahead on the BenchAlign aggregate, 47.41 to 42.06. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o3-mini's sharpest advantage is in knowledge, where it averages 77.2 against 50.3. The single biggest benchmark swing on the page is GPQA, 50.3% to 77.2%.
o3-mini is also the more expensive model on tokens at $1.10 input / $4.40 output per 1M tokens, versus $0.10 input / $0.40 output per 1M tokens for GPT-4.1 nano. That is roughly 11.0x on output cost alone. o3-mini is the reasoning model in the pair, while GPT-4.1 nano is not. That usually helps on harder chain-of-thought-heavy tests, but it can also mean more latency and more token spend in real use. GPT-4.1 nano gives you the larger context window at 1M, compared with 200K for o3-mini.
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 nano | Δ | o3-mini |
|---|---|---|---|
| Knowledge | GPT-4.1 nano50.3 | Margin→ 26.9 | o3-mini77.2 |
| Inst. Following | GPT-4.1 nano83.2 | Margin→ 10.7 | o3-mini93.9 |
| Coding | GPT-4.1 nanoNot measured | MarginNo overlap | o3-mini49.3 |
| Math | GPT-4.1 nano1.0 | MarginNo overlap | o3-miniNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-4.1 nano | o3-mini | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-4.1 nano$0.1 input / $0.4 output | o3-mini$1.1 input / $4.4 output | GPT-4.1 nano has the lower combined listed price. |
| Generation speedtokens per second | GPT-4.1 nano181 tok/s | o3-mini160 tok/s | GPT-4.1 nano has the higher measured throughput. |
| First-answer latencyseconds to first token | GPT-4.1 nano0.63 s | o3-mini7.12 s | GPT-4.1 nano reaches the first token sooner. |
| Context windowmaximum listed tokens | GPT-4.1 nano1M | o3-mini200K | GPT-4.1 nano lists the larger context window. |
Benchmark Deep Dive
Agentic4 benchmarks
Coding3 benchmarks
Reasoning2 benchmarks
Knowledgeo3-mini wins8 benchmarks
| Benchmark | GPT-4.1 nano | o3-mini | Result |
|---|---|---|---|
| MMLUSource | 80.1% | 86.9% | o3-mini leads |
| GPQASource | 50.3% | 77.2% | o3-mini leads |
| Artificial Analysis Intelligence IndexSource | 9.6% | 19.0% | o3-mini leads |
| AA-GPQA DiamondSource | 51.2% | 74.8% | o3-mini leads |
| AA-HLESource | 3.9% | 8.7% | o3-mini leads |
| AA-Omniscience IndexSource | -56.4% | — | Not comparable |
| AA-Omniscience AccuracySource | 13.3% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 80.4% | — | Not comparable |
Math2 benchmarks
Multimodal2 benchmarks
Frequently Asked Questions (3)
Which is better, GPT-4.1 nano or o3-mini?
o3-mini is ahead on BenchLM's BenchAlign leaderboard, 47.41 to 42.06. The biggest single separator in this matchup is GPQA, where the scores are 50.3% and 77.2%.
Which is better for knowledge tasks, GPT-4.1 nano or o3-mini?
o3-mini has the edge for knowledge tasks in this comparison, averaging 77.2 versus 50.3. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Which is better for instruction following, GPT-4.1 nano or o3-mini?
o3-mini has the edge for instruction following in this comparison, averaging 93.9 versus 83.2. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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