Model comparison
GPT-4o vs LFM2.5-8B-A1B
Head-to-head evidence from 11 shared benchmark results across 5 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-4o #165 (Supported); LFM2.5-8B-A1B #166 (Estimated). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-4o and LFM2.5-8B-A1B share 11 comparable benchmark results. 1 of 8 categories are comparable. 2 results are unique to GPT-4o; 6 to LFM2.5-8B-A1B.
Updated July 23, 2026- Shared results
- 11
- GPT-4o only
- 2
- LFM2.5-8B-A1B only
- 6
- Comparable categories
- 1 / 8
Pick GPT-4o 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 11 shared benchmark results across 5 evidence categories; 1 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
GPT-4o has the cleaner BenchAlign overall profile here, landing at 41.49 versus 41.42. It is a real lead, but still close enough that category-level strengths matter more than the headline number.
GPT-4o is also the more expensive model on tokens at $2.50 input / $10.00 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. LFM2.5-8B-A1B is the reasoning model in the pair, while GPT-4o 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.
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-4o | Δ | LFM2.5-8B-A1B |
|---|---|---|---|
| Math | GPT-4o0.3 | Margin→ 49.7 | LFM2.5-8B-A1B50.0 |
| Inst. Following | GPT-4oNot measured | MarginNo overlap | LFM2.5-8B-A1B68.8 |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-4o | LFM2.5-8B-A1B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-4o$2.5 input / $10 output | LFM2.5-8B-A1B$0 input / $0 output | LFM2.5-8B-A1B has the lower combined listed price. |
| Generation speedtokens per second | GPT-4o131 tok/s | LFM2.5-8B-A1BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-4o0.81 s | LFM2.5-8B-A1BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-4o128K | LFM2.5-8B-A1B128K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic2 benchmarks
Coding1 benchmarks
| Benchmark | GPT-4o | LFM2.5-8B-A1B | Result |
|---|---|---|---|
| AA-SciCodeSource | 33.3% | 7.8% | GPT-4o leads |
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | GPT-4o | LFM2.5-8B-A1B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 11.2% | 8.3% | GPT-4o leads |
| AA-GPQA DiamondSource | 54.3% | 51.3% | GPT-4o leads |
| AA-HLESource | 3.3% | 6.9% | LFM2.5-8B-A1B leads |
| AA-Omniscience IndexSource | -10.7% | -33.3% | GPT-4o leads |
| AA-Omniscience AccuracySource | 19.7% | 9.4% | GPT-4o leads |
| AA-Omniscience Hallucination RateSource | 37.9% | 47.0% | GPT-4o leads |
MathLFM2.5-8B-A1B wins4 benchmarks
Multimodal1 benchmarks
| Benchmark | GPT-4o | LFM2.5-8B-A1B | Result |
|---|---|---|---|
| Design Arena WebsiteSource | 861 | — | Not comparable |
Frequently Asked Questions (2)
Which is better, GPT-4o or LFM2.5-8B-A1B?
GPT-4o is ahead on BenchLM's BenchAlign leaderboard, 41.49 to 41.42.
Which is better for math, GPT-4o or LFM2.5-8B-A1B?
LFM2.5-8B-A1B has the edge for math in this comparison, averaging 50 versus 0.3. GPT-4o stays close enough that the answer can still flip depending on your workload.
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