Model comparison
LFM2.5-VL-1.6B-Extract vs Mellum2-12B-A2.5B-Thinking
Head-to-head evidence from 0 shared benchmark results across 0 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Evidence parity. LFM2.5-VL-1.6B-Extract and Mellum2-12B-A2.5B-Thinking share 0 comparable benchmark results. 0 of 8 categories are comparable. 15 results are unique to LFM2.5-VL-1.6B-Extract; 5 to Mellum2-12B-A2.5B-Thinking.
Updated July 23, 2026- Shared results
- 0
- LFM2.5-VL-1.6B-Extract only
- 15
- Mellum2-12B-A2.5B-Thinking only
- 5
- Comparable categories
- 0 / 8
Benchmark data for LFM2.5-VL-1.6B-Extract and Mellum2-12B-A2.5B-Thinking 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 | LFM2.5-VL-1.6B-Extract | Mellum2-12B-A2.5B-Thinking | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | LFM2.5-VL-1.6B-ExtractNot available | Mellum2-12B-A2.5B-ThinkingNot available | A complete price comparison is not available. |
| Generation speedtokens per second | LFM2.5-VL-1.6B-ExtractNot available | Mellum2-12B-A2.5B-ThinkingNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | LFM2.5-VL-1.6B-ExtractNot available | Mellum2-12B-A2.5B-ThinkingNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | LFM2.5-VL-1.6B-Extract128K | Mellum2-12B-A2.5B-Thinking128K | Listed context windows are equal. |
Benchmark Deep Dive
Agentic2 benchmarks
Coding1 benchmarks
| Benchmark | LFM2.5-VL-1.6B-Extract | Mellum2-12B-A2.5B-Thinking | Result |
|---|---|---|---|
| AA-SciCodeSource | 3.0% | — | Not comparable |
Reasoning2 benchmarks
Knowledge9 benchmarks
| Benchmark | LFM2.5-VL-1.6B-Extract | Mellum2-12B-A2.5B-Thinking | 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 |
| MMLU-ReduxSource | — | 86.2% | Not comparable |
| GPQASource | — | 57.6% | Not comparable |
| GPQA-DSource | — | 57.6% | Not comparable |
Multimodal4 benchmarks
Frequently Asked Questions (2)
Can I compare LFM2.5-VL-1.6B-Extract and Mellum2-12B-A2.5B-Thinking 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.
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