Model comparison
GPT-4.1 nano vs LFM2.5-8B-A1B
Head-to-head evidence from 13 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
BenchAlign evidence: GPT-4.1 nano estimated; LFM2.5-8B-A1B estimated. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-4.1 nano and LFM2.5-8B-A1B share 13 comparable benchmark results. 2 of 8 categories are comparable. 9 results are unique to GPT-4.1 nano; 5 to LFM2.5-8B-A1B.
Updated July 16, 2026- Shared results
- 13
- GPT-4.1 nano only
- 9
- LFM2.5-8B-A1B only
- 5
- Comparable categories
- 2 / 8
Pick LFM2.5-8B-A1B if you want the stronger benchmark profile. GPT-4.1 nano only becomes the better choice if instruction following is the priority or you need the larger 1M context window.
Confidence note. This is a partial-evidence comparison with 13 shared benchmark results across 5 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
LFM2.5-8B-A1B is clearly ahead on the provisional aggregate, 37 to 30. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
LFM2.5-8B-A1B's sharpest advantage is in mathematics, where it averages 50 against 1. The single biggest benchmark swing on the page is IFEval, 83.2% to 91.8%. GPT-4.1 nano does hit back in instruction following, so the answer changes if that is the part of the workload you care about most.
GPT-4.1 nano is also the more expensive model on tokens at $0.10 input / $0.40 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for LFM2.5-8B-A1B. That is roughly Infinityx on output cost alone. LFM2.5-8B-A1B 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 128K for LFM2.5-8B-A1B.
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 | LFM2.5-8B-A1B |
|---|---|---|---|
| Math | GPT-4.1 nano1.0 | Margin→ 49.0 | LFM2.5-8B-A1B50.0 |
| Inst. Following | GPT-4.1 nano83.2 | Margin← 14.4 | LFM2.5-8B-A1B68.8 |
| Knowledge | GPT-4.1 nano50.3 | MarginNo overlap | LFM2.5-8B-A1BNot measured |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
IFEval
Inst. FollowingA 83.2%B 91.8%Winner: LFM2.5-8B-A1BΔ 8.6IFEval: GPT-4.1 nano scored 83.2%; LFM2.5-8B-A1B scored 91.8%. LFM2.5-8B-A1B wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-4.1 nano | LFM2.5-8B-A1B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-4.1 nano$0.1 input / $0.4 output | LFM2.5-8B-A1B$0 input / $0 output | LFM2.5-8B-A1B has the lower combined listed price. |
| Generation speedtokens per second | GPT-4.1 nano181 tok/s | LFM2.5-8B-A1BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-4.1 nano0.63 s | LFM2.5-8B-A1BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-4.1 nano1M | LFM2.5-8B-A1B128K | GPT-4.1 nano lists the larger context window. |
Benchmark Deep Dive
Agentic5 benchmarks
Coding3 benchmarks
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | GPT-4.1 nano | LFM2.5-8B-A1B | Result |
|---|---|---|---|
| MMLUSource | 80.1% | — | Not comparable |
| GPQASource | 50.3% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 9.6% | 8.3% | GPT-4.1 nano leads |
| AA-GPQA DiamondSource | 51.2% | 51.3% | LFM2.5-8B-A1B leads |
| AA-HLESource | 3.9% | 6.9% | LFM2.5-8B-A1B leads |
| AA-Omniscience IndexSource | -56.4% | -33.3% | LFM2.5-8B-A1B leads |
| AA-Omniscience AccuracySource | 13.3% | 9.4% | GPT-4.1 nano leads |
| AA-Omniscience Hallucination RateSource | 80.4% | 47.0% | LFM2.5-8B-A1B leads |
MathLFM2.5-8B-A1B wins4 benchmarks
Multimodal2 benchmarks
Frequently Asked Questions (3)
Which is better, GPT-4.1 nano or LFM2.5-8B-A1B?
LFM2.5-8B-A1B is ahead on BenchLM's provisional leaderboard, 37 to 30. The biggest single separator in this matchup is IFEval, where the scores are 83.2% and 91.8%.
Which is better for math, GPT-4.1 nano or LFM2.5-8B-A1B?
LFM2.5-8B-A1B has the edge for math in this comparison, averaging 50 versus 1. GPT-4.1 nano stays close enough that the answer can still flip depending on your workload.
Which is better for instruction following, GPT-4.1 nano or LFM2.5-8B-A1B?
GPT-4.1 nano has the edge for instruction following in this comparison, averaging 83.2 versus 68.8. Inside this category, AA-IFBench is the benchmark that creates the most daylight between them.
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