Model comparison
GLM-4.5-Air 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: GLM-4.5-Air #133 (Supported); 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. GLM-4.5-Air and LFM2.5-VL-1.6B-Extract share 11 comparable benchmark results. 0 of 8 categories are comparable. 1 result is unique to GLM-4.5-Air; 4 to LFM2.5-VL-1.6B-Extract.
Updated July 23, 2026- Shared results
- 11
- GLM-4.5-Air only
- 1
- LFM2.5-VL-1.6B-Extract only
- 4
- Comparable categories
- 0 / 8
Benchmark data for GLM-4.5-Air 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.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-4.5-Air | LFM2.5-VL-1.6B-Extract | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-4.5-Air$0.2 input / $1.1 output | LFM2.5-VL-1.6B-ExtractNot available | A complete price comparison is not available. |
| Generation speedtokens per second | GLM-4.5-Air106 tok/s | LFM2.5-VL-1.6B-ExtractNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-4.5-Air1.18 s | LFM2.5-VL-1.6B-ExtractNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-4.5-Air128K | LFM2.5-VL-1.6B-Extract128K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic1 benchmarks
| Benchmark | GLM-4.5-Air | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| τ²-bench resultsSource | 46.5% | 8.5% | GLM-4.5-Air leads |
Coding1 benchmarks
| Benchmark | GLM-4.5-Air | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| AA-SciCodeSource | 30.6% | 3.0% | GLM-4.5-Air leads |
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | GLM-4.5-Air | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 16.5% | 1.0% | GLM-4.5-Air leads |
| AA-GPQA DiamondSource | 73.3% | 28.9% | GLM-4.5-Air leads |
| AA-HLESource | 6.8% | 5.1% | GLM-4.5-Air leads |
| AA-Omniscience IndexSource | -62.5% | -83.9% | GLM-4.5-Air leads |
| AA-Omniscience AccuracySource | 15.5% | 5.2% | GLM-4.5-Air leads |
| AA-Omniscience Hallucination RateSource | 92.3% | 94.0% | GLM-4.5-Air leads |
Multimodal5 benchmarks
Inst. Following1 benchmarks
| Benchmark | GLM-4.5-Air | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| AA-IFBenchSource | 37.6% | 33.1% | GLM-4.5-Air leads |
Frequently Asked Questions (3)
Can I compare GLM-4.5-Air 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 GLM-4.5-Air and LFM2.5-VL-1.6B-Extract today?
GLM-4.5-Air: $0.20 input / $1.10 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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