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