Model comparison
LFM2.5-VL-1.6B-Extract vs Ternary Bonsai 1.7B
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 Ternary Bonsai 1.7B share 0 comparable benchmark results. 0 of 8 categories are comparable. 15 results are unique to LFM2.5-VL-1.6B-Extract; 0 to Ternary Bonsai 1.7B.
Updated July 23, 2026- Shared results
- 0
- LFM2.5-VL-1.6B-Extract only
- 15
- Ternary Bonsai 1.7B only
- 0
- Comparable categories
- 0 / 8
Benchmark data for LFM2.5-VL-1.6B-Extract and Ternary Bonsai 1.7B 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 does not have sourced benchmark coverage for Ternary Bonsai 1.7B yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.
LFM2.5-VL-1.6B-Extract has the larger context window at 128K, compared with 32K for Ternary Bonsai 1.7B.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | LFM2.5-VL-1.6B-Extract | Ternary Bonsai 1.7B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | LFM2.5-VL-1.6B-ExtractNot available | Ternary Bonsai 1.7B$0 input / $0 output | A complete price comparison is not available. |
| Generation speedtokens per second | LFM2.5-VL-1.6B-ExtractNot available | Ternary Bonsai 1.7BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | LFM2.5-VL-1.6B-ExtractNot available | Ternary Bonsai 1.7BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | LFM2.5-VL-1.6B-Extract128K | Ternary Bonsai 1.7B32K | LFM2.5-VL-1.6B-Extract lists the larger context window. |
Benchmark Deep Dive
Agentic1 benchmarks
| Benchmark | LFM2.5-VL-1.6B-Extract | Ternary Bonsai 1.7B | Result |
|---|---|---|---|
| τ²-bench resultsSource | 8.5% | — | Not comparable |
Coding1 benchmarks
| Benchmark | LFM2.5-VL-1.6B-Extract | Ternary Bonsai 1.7B | Result |
|---|---|---|---|
| AA-SciCodeSource | 3.0% | — | Not comparable |
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | LFM2.5-VL-1.6B-Extract | Ternary Bonsai 1.7B | 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 |
Multimodal4 benchmarks
Inst. Following1 benchmarks
| Benchmark | LFM2.5-VL-1.6B-Extract | Ternary Bonsai 1.7B | Result |
|---|---|---|---|
| AA-IFBenchSource | 33.1% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare LFM2.5-VL-1.6B-Extract and Ternary Bonsai 1.7B 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 LFM2.5-VL-1.6B-Extract and Ternary Bonsai 1.7B today?
Ternary Bonsai 1.7B: $0.00 input / $0.00 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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