Model comparison
GLM-4.5 vs LFM2.5-VL-1.6B-Extract
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: GLM-4.5 #68 (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. GLM-4.5 and LFM2.5-VL-1.6B-Extract share 0 comparable benchmark results. 0 of 8 categories are comparable. 1 result is unique to GLM-4.5; 15 to LFM2.5-VL-1.6B-Extract.
Updated July 23, 2026- Shared results
- 0
- GLM-4.5 only
- 1
- LFM2.5-VL-1.6B-Extract only
- 15
- Comparable categories
- 0 / 8
Benchmark data for GLM-4.5 and LFM2.5-VL-1.6B-Extract is coming soon on BenchLM.
Confidence note. This is a partial-evidence comparison with 0 shared benchmark results across 0 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.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | GLM-4.5 | LFM2.5-VL-1.6B-Extract | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | GLM-4.5$0.6 input / $2.2 output | LFM2.5-VL-1.6B-ExtractNot available | A complete price comparison is not available. |
| Generation speedtokens per second | GLM-4.551 tok/s | LFM2.5-VL-1.6B-ExtractNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | GLM-4.51.45 s | LFM2.5-VL-1.6B-ExtractNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | GLM-4.5128K | LFM2.5-VL-1.6B-Extract128K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic1 benchmarks
| Benchmark | GLM-4.5 | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| τ²-bench resultsSource | — | 8.5% | Not comparable |
Coding1 benchmarks
| Benchmark | GLM-4.5 | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| AA-SciCodeSource | — | 3.0% | Not comparable |
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | GLM-4.5 | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | — | 1.0% | Not comparable |
| AA-GPQA DiamondSource | — | 28.9% | Not comparable |
| AA-HLESource | — | 5.1% | Not comparable |
| AA-Omniscience IndexSource | — | -83.9% | Not comparable |
| AA-Omniscience AccuracySource | — | 5.2% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 94.0% | Not comparable |
Multimodal5 benchmarks
Inst. Following1 benchmarks
| Benchmark | GLM-4.5 | LFM2.5-VL-1.6B-Extract | Result |
|---|---|---|---|
| AA-IFBenchSource | — | 33.1% | Not comparable |
Frequently Asked Questions (3)
Can I compare GLM-4.5 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 and LFM2.5-VL-1.6B-Extract today?
GLM-4.5: $0.60 input / $2.20 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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