Model comparison
GPT-5.2 vs LFM2.5-VL-1.6B-Extract
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-5.2 #64 (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-5.2 and LFM2.5-VL-1.6B-Extract share 11 comparable benchmark results. 0 of 8 categories are comparable. 17 results are unique to GPT-5.2; 4 to LFM2.5-VL-1.6B-Extract.
Updated July 23, 2026- Shared results
- 11
- GPT-5.2 only
- 17
- LFM2.5-VL-1.6B-Extract only
- 4
- Comparable categories
- 0 / 8
Benchmark data for GPT-5.2 and LFM2.5-VL-1.6B-Extract is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 11 shared benchmark results across 5 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-5.2 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-5.2 | Δ | LFM2.5-VL-1.6B-Extract |
|---|---|---|---|
| Agentic | GPT-5.255.7 | MarginNo overlap | LFM2.5-VL-1.6B-ExtractNot measured |
| Coding | GPT-5.270.6 | MarginNo overlap | LFM2.5-VL-1.6B-ExtractNot measured |
| Reasoning | GPT-5.252.9 | MarginNo overlap | LFM2.5-VL-1.6B-ExtractNot measured |
| Knowledge | GPT-5.292.4 | MarginNo overlap | LFM2.5-VL-1.6B-ExtractNot measured |
| Math | GPT-5.235.2 | MarginNo overlap | LFM2.5-VL-1.6B-ExtractNot measured |
| Multimodal | GPT-5.280.4 | 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-5.2 | LFM2.5-VL-1.6B-Extract | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GPT-5.2$1.75 input / $14 output | LFM2.5-VL-1.6B-ExtractNot available | A complete price comparison is not available. |
| Generation speedtokens per second | GPT-5.273 tok/s | LFM2.5-VL-1.6B-ExtractNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GPT-5.2130.34 s | LFM2.5-VL-1.6B-ExtractNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GPT-5.2400K | LFM2.5-VL-1.6B-Extract128K | GPT-5.2 lists the larger context window. |
Benchmark Deep Dive
Agentic5 benchmarks
Coding4 benchmarks
Reasoning3 benchmarks
Knowledge7 benchmarks
| Benchmark | GPT-5.2 | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| GPQASource | 92.4% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 42.2% | 1.0% | GPT-5.2 leads |
| AA-GPQA DiamondSource | 90.3% | 28.9% | GPT-5.2 leads |
| AA-HLESource | 35.4% | 5.1% | GPT-5.2 leads |
| AA-Omniscience IndexSource | -1.0% | -83.9% | GPT-5.2 leads |
| AA-Omniscience AccuracySource | 43.8% | 5.2% | GPT-5.2 leads |
| AA-Omniscience Hallucination RateSource | 79.7% | 94.0% | GPT-5.2 leads |
Math3 benchmarks
Multimodal9 benchmarks
| Benchmark | GPT-5.2 | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| MMMU-ProSource | 79.5% | — | Not comparable |
| MathVisionSource | 83.0% | — | Not comparable |
| CharXivSource | 82.1% | — | Not comparable |
| V*Source | 75.9% | — | Not comparable |
| Design Arena WebsiteSource | 1224 | — | Not comparable |
| Liquid Extract JSON ValiditySource | — | 99.6% | Not comparable |
| Liquid Extract F1Source | — | 99.6% | Not comparable |
| Liquid Extract VLM JudgeSource | — | 90.6% | Not comparable |
| AA-MMMU-ProSource | — | 26.5% | Not comparable |
Inst. Following1 benchmarks
| Benchmark | GPT-5.2 | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| AA-IFBenchSource | 75.4% | 33.1% | GPT-5.2 leads |
Frequently Asked Questions (3)
Can I compare GPT-5.2 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-5.2 and LFM2.5-VL-1.6B-Extract today?
GPT-5.2: $1.75 input / $14.00 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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