Model comparison
GPT-4.1 nano vs LFM2.5-8B-A1B
Head-to-head evidence from 12 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-4.1 nano #161 (Estimated); LFM2.5-8B-A1B #166 (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 12 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 23, 2026- Shared results
- 12
- GPT-4.1 nano only
- 9
- LFM2.5-8B-A1B only
- 5
- Comparable categories
- 2 / 8
Pick GPT-4.1 nano if you want the stronger benchmark profile. LFM2.5-8B-A1B only becomes the better choice if mathematics is the priority or you want the cheaper token bill.
Confidence note. This is a partial-evidence comparison with 12 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
GPT-4.1 nano has the cleaner BenchAlign overall profile here, landing at 42.06 versus 41.42. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
GPT-4.1 nano's sharpest advantage is in instruction following, where it averages 83.2 against 68.8. The single biggest benchmark swing on the page is IFEval, 83.2% to 91.8%. LFM2.5-8B-A1B does hit back in mathematics, 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
Coding2 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?
GPT-4.1 nano is ahead on BenchLM's BenchAlign leaderboard, 42.06 to 41.42. 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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