Model comparison
LFM2.5-8B-A1B vs o1
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: LFM2.5-8B-A1B estimated; o1 estimated. Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. LFM2.5-8B-A1B and o1 share 13 comparable benchmark results. 2 of 8 categories are comparable. 5 results are unique to LFM2.5-8B-A1B; 4 to o1.
Updated July 16, 2026- Shared results
- 13
- LFM2.5-8B-A1B only
- 5
- o1 only
- 4
- Comparable categories
- 2 / 8
Pick o1 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 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
o1 is clearly ahead on the provisional aggregate, 55 to 37. The gap is large enough that you do not need to squint at the spreadsheet to see the difference.
o1's sharpest advantage is in instruction following, where it averages 92.2 against 68.8. The single biggest benchmark swing on the page is IFEval, 91.8% to 92.2%. 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.
o1 is also the more expensive model on tokens at $15.00 input / $60.00 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. o1 gives you the larger context window at 200K, 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 | LFM2.5-8B-A1B | Δ | o1 |
|---|---|---|---|
| Math | LFM2.5-8B-A1B50.0 | Margin← 40.7 | o19.3 |
| Inst. Following | LFM2.5-8B-A1B68.8 | Margin→ 23.4 | o192.2 |
| Knowledge | LFM2.5-8B-A1BNot measured | MarginNo overlap | o175.7 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
IFEval
Inst. FollowingA 91.8%B 92.2%Winner: o1Δ 0.4IFEval: LFM2.5-8B-A1B scored 91.8%; o1 scored 92.2%. o1 wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | LFM2.5-8B-A1B | o1 | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | LFM2.5-8B-A1B$0 input / $0 output | o1$15 input / $60 output | LFM2.5-8B-A1B has the lower combined listed price. |
| Generation speedtokens per second | LFM2.5-8B-A1BNot available | o198 tok/s | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | LFM2.5-8B-A1BNot available | o132.29 s | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | LFM2.5-8B-A1B128K | o1200K | o1 lists the larger context window. |
Benchmark Deep Dive
Agentic2 benchmarks
Coding3 benchmarks
Reasoning2 benchmarks
Knowledge8 benchmarks
| Benchmark | LFM2.5-8B-A1B | o1 | Result |
|---|---|---|---|
| AA-GPQA DiamondSource | 51.3% | 74.7% | o1 leads |
| AA-HLESource | 6.9% | 7.7% | o1 leads |
| AA-Omniscience IndexSource | -33.3% | -10.5% | o1 leads |
| AA-Omniscience AccuracySource | 9.4% | 34.7% | o1 leads |
| AA-Omniscience Hallucination RateSource | 47.0% | 69.3% | LFM2.5-8B-A1B leads |
| Artificial Analysis Intelligence IndexSource | 8.3% | 23.4% | o1 leads |
| MMLUSource | — | 91.8% | Not comparable |
| GPQASource | — | 75.7% | Not comparable |
MathLFM2.5-8B-A1B wins4 benchmarks
Frequently Asked Questions (3)
Which is better, LFM2.5-8B-A1B or o1?
o1 is ahead on BenchLM's provisional leaderboard, 55 to 37. The biggest single separator in this matchup is IFEval, where the scores are 91.8% and 92.2%.
Which is better for math, LFM2.5-8B-A1B or o1?
LFM2.5-8B-A1B has the edge for math in this comparison, averaging 50 versus 9.3. o1 stays close enough that the answer can still flip depending on your workload.
Which is better for instruction following, LFM2.5-8B-A1B or o1?
o1 has the edge for instruction following in this comparison, averaging 92.2 versus 68.8. Inside this category, AA-IFBench is the benchmark that creates the most daylight between them.
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