Model comparison
GPT-5.4 mini vs LFM2.5-VL-1.6B-Extract
Head-to-head evidence from 12 shared benchmark results across 6 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GPT-5.4 mini #75 (Estimated); LFM2.5-VL-1.6B-Extract unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. GPT-5.4 mini and LFM2.5-VL-1.6B-Extract share 12 comparable benchmark results. 0 of 8 categories are comparable. 18 results are unique to GPT-5.4 mini; 3 to LFM2.5-VL-1.6B-Extract.
Updated July 23, 2026- Shared results
- 12
- GPT-5.4 mini only
- 18
- LFM2.5-VL-1.6B-Extract only
- 3
- Comparable categories
- 0 / 8
Benchmark data for GPT-5.4 mini and LFM2.5-VL-1.6B-Extract is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 12 shared benchmark results across 6 evidence categories; 0 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
GPT-5.4 mini has the larger context window at 400K, compared with 128K for LFM2.5-VL-1.6B-Extract.
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-5.4 mini | Δ | LFM2.5-VL-1.6B-Extract |
|---|---|---|---|
| Agentic | GPT-5.4 mini65.7 | MarginNo overlap | LFM2.5-VL-1.6B-ExtractNot measured |
| Knowledge | GPT-5.4 mini47.8 | MarginNo overlap | LFM2.5-VL-1.6B-ExtractNot measured |
| Math | GPT-5.4 mini21.7 | MarginNo overlap | LFM2.5-VL-1.6B-ExtractNot measured |
| Multimodal | GPT-5.4 mini76.6 | MarginNo overlap | LFM2.5-VL-1.6B-ExtractNot measured |
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GPT-5.4 mini | LFM2.5-VL-1.6B-Extract | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.4 mini$0.75 input / $4.5 output | LFM2.5-VL-1.6B-ExtractNot available | A complete price comparison is not available. |
| Generation speedtokens per second | GPT-5.4 mini201 tok/s | LFM2.5-VL-1.6B-ExtractNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.4 mini3.85 s | LFM2.5-VL-1.6B-ExtractNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.4 mini400K | LFM2.5-VL-1.6B-Extract128K | GPT-5.4 mini lists the larger context window. |
Benchmark Deep Dive
Agentic9 benchmarks
| Benchmark | GPT-5.4 mini | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 60% | — | Not comparable |
| OSWorld-VerifiedSource | 72.1% | — | Not comparable |
| MCP AtlasSource | 57.7% | — | Not comparable |
| ToolathlonSource | 42.9% | — | Not comparable |
| τ²-bench resultsSource | 83.3% | 8.5% | GPT-5.4 mini leads |
| AA Agentic IndexSource | 30.2% | — | Not comparable |
| APEX-Agents-AASource | 28.2% | — | Not comparable |
| GDPval-AASource | 33.6% | — | Not comparable |
| GDPval-AASource | 1171 | — | Not comparable |
Coding4 benchmarks
Reasoning2 benchmarks
Knowledge9 benchmarks
| Benchmark | GPT-5.4 mini | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| GPQASource | 88% | — | Not comparable |
| HLESource | 41.5% | — | Not comparable |
| HLE w/o toolsSource | 28.2% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 40.0% | 1.0% | GPT-5.4 mini leads |
| AA-GPQA DiamondSource | 87.5% | 28.9% | GPT-5.4 mini leads |
| AA-HLESource | 26.6% | 5.1% | GPT-5.4 mini leads |
| AA-Omniscience IndexSource | -18.7% | -83.9% | GPT-5.4 mini leads |
| AA-Omniscience AccuracySource | 37.5% | 5.2% | GPT-5.4 mini leads |
| AA-Omniscience Hallucination RateSource | 89.8% | 94.0% | GPT-5.4 mini leads |
Math2 benchmarks
Multimodal6 benchmarks
| Benchmark | GPT-5.4 mini | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| MMMU-ProSource | 76.6% | — | Not comparable |
| MMMU-Pro w/ PythonSource | 78% | — | Not comparable |
| AA-MMMU-ProSource | 73.3% | 26.5% | GPT-5.4 mini leads |
| Liquid Extract JSON ValiditySource | — | 99.6% | Not comparable |
| Liquid Extract F1Source | — | 99.6% | Not comparable |
| Liquid Extract VLM JudgeSource | — | 90.6% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GPT-5.4 mini | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| AA-IFBenchSource | 73.3% | 33.1% | GPT-5.4 mini leads |
Frequently Asked Questions (3)
Can I compare GPT-5.4 mini and LFM2.5-VL-1.6B-Extract on BenchLM yet?
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still coming soon.
Why does this comparison show “coming soon”?
BenchLM only shows category winners and benchmark-level calls when we have sourced results that can be compared fairly. For these models, the public benchmark coverage is not complete enough yet.
What data is available for GPT-5.4 mini and LFM2.5-VL-1.6B-Extract today?
GPT-5.4 mini: $0.75 input / $4.50 output per 1M tokens Both model pages still include creator, context window, reasoning mode, and other metadata while benchmark coverage fills in.
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