Side-by-side benchmark comparison across agentic, coding, multimodal, knowledge, reasoning, and math workflows.
1-bit Bonsai 1.7B
~39
1/8 categoriesPhi-4
40
Winner · 2/8 categories1-bit Bonsai 1.7B· Phi-4
Pick Phi-4 if you want the stronger benchmark profile. 1-bit Bonsai 1.7B only becomes the better choice if reasoning is the priority or you need the larger 32K context window.
Phi-4 finishes one point ahead overall, 40 to 39. That is enough to call, but not enough to treat as a blowout. This matchup comes down to a few meaningful edges rather than one model dominating the board.
Phi-4's sharpest advantage is in mathematics, where it averages 94.6 against 34.4. The single biggest benchmark swing on the page is MATH-500, 34.4% to 94.6%. 1-bit Bonsai 1.7B does hit back in reasoning, so the answer changes if that is the part of the workload you care about most.
1-bit Bonsai 1.7B gives you the larger context window at 32K, compared with 16K for Phi-4.
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 1.7B | Phi-4 |
|---|---|---|
| Agentic | ||
| Terminal-Bench 2.0 | — | 44% |
| BrowseComp | — | 35% |
| OSWorld-Verified | — | 34% |
| Coding | ||
| HumanEval | — | 82.6% |
| SWE-bench Pro | — | 55% |
| Multimodal & Grounded | ||
| MMMU-Pro | — | 54% |
| OfficeQA Pro | — | 38% |
| Reasoning1-bit Bonsai 1.7B wins | ||
| MuSR | 45.1% | — |
| LongBench v2 | — | 30% |
| MRCRv2 | — | 33% |
| KnowledgePhi-4 wins | ||
| GPQA | 20.7% | 56.1% |
| MMLU | — | 84.8% |
| FrontierScience | — | 52% |
| Instruction Following | ||
| IFEval | 63% | — |
| Multilingual | ||
| MGSM | — | 80.6% |
| MMLU-ProX | — | 60% |
| MathematicsPhi-4 wins | ||
| MATH-500 | 34.4% | 94.6% |
Phi-4 is ahead overall, 40 to 39. The biggest single separator in this matchup is MATH-500, where the scores are 34.4% and 94.6%.
Phi-4 has the edge for knowledge tasks in this comparison, averaging 53.6 versus 20.7. Inside this category, GPQA is the benchmark that creates the most daylight between them.
Phi-4 has the edge for math in this comparison, averaging 94.6 versus 34.4. Inside this category, MATH-500 is the benchmark that creates the most daylight between them.
1-bit Bonsai 1.7B has the edge for reasoning in this comparison, averaging 45.1 versus 31.4. Phi-4 stays close enough that the answer can still flip depending on your workload.
Get notified when new models drop, benchmark scores change, or the leaderboard shifts. One email per week.
Free. No spam. Unsubscribe anytime. We only store derived location metadata for consent routing.