Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
1-bit Bonsai 4B
~44
Winner · 0/8 categoriesHyperClova X Think 32B
~0
0/8 categories1-bit Bonsai 4B· HyperClova X Think 32B
Benchmark data for 1-bit Bonsai 4B and HyperClova X Think 32B is coming soon on BenchLM.
BenchLM has partial data for these models, but not enough overlapping benchmark coverage to produce a fair score-level comparison yet.
HyperClova X Think 32B has the larger context window at 128K, compared with 32K for 1-bit Bonsai 4B.
BenchLM keeps the benchmark table and the operator tradeoffs on the same page so a better score does not hide a materially slower, pricier, or smaller-context model.
Runtime metrics show N/A when BenchLM does not have a sourced snapshot for that exact model. The scoring rules and freshness policy are documented on the methodology page.
| Benchmark | 1-bit Bonsai 4B | HyperClova X Think 32B |
|---|---|---|
| Agentic | ||
| Coming soon | ||
| Coding | ||
| Coming soon | ||
| Multimodal & Grounded | ||
| Coming soon | ||
| Reasoning | ||
| MuSR | 41.4% | — |
| Knowledge | ||
| GPQA | 28.7% | — |
| Instruction Following | ||
| IFEval | 69.6% | — |
| Multilingual | ||
| Coming soon | ||
| Mathematics | ||
| MATH-500 | 65.8% | — |
Not fully yet. BenchLM is tracking both models, but the sourced benchmark breakdown for this comparison is still 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.
1-bit Bonsai 4B: $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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