Model comparison
Phi-4 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.
Public leaderboard positions: Phi-4 #192 (Supported); Ternary Bonsai 1.7B unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Phi-4 and Ternary Bonsai 1.7B share 0 comparable benchmark results. 0 of 8 categories are comparable. 11 results are unique to Phi-4; 0 to Ternary Bonsai 1.7B.
Updated July 21, 2026- Shared results
- 0
- Phi-4 only
- 11
- Ternary Bonsai 1.7B only
- 0
- Comparable categories
- 0 / 8
Benchmark data for Phi-4 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.
Ternary Bonsai 1.7B has the larger context window at 32K, compared with 16K for Phi-4.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Phi-4 | Ternary Bonsai 1.7B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Phi-4$0 input / $0 output | Ternary Bonsai 1.7B$0 input / $0 output | Listed prices are equal. |
| Generation speedtokens per second | Phi-435 tok/s | Ternary Bonsai 1.7BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Phi-42.02 s | Ternary Bonsai 1.7BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Phi-416K | Ternary Bonsai 1.7B32K | Ternary Bonsai 1.7B lists the larger context window. |
Benchmark Deep Dive
Agentic1 benchmarks
| Benchmark | Phi-4 | Ternary Bonsai 1.7B | Result |
|---|---|---|---|
| τ²-bench resultsSource | 0% | — | Not comparable |
Coding1 benchmarks
| Benchmark | Phi-4 | Ternary Bonsai 1.7B | Result |
|---|---|---|---|
| AA-SciCodeSource | 26.0% | — | Not comparable |
Reasoning2 benchmarks
Knowledge6 benchmarks
| Benchmark | Phi-4 | Ternary Bonsai 1.7B | Result |
|---|---|---|---|
| Artificial Analysis Intelligence IndexSource | 4.9% | — | Not comparable |
| AA-GPQA DiamondSource | 57.5% | — | Not comparable |
| AA-HLESource | 4.1% | — | Not comparable |
| AA-Omniscience IndexSource | -56.7% | — | Not comparable |
| AA-Omniscience AccuracySource | 13.2% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 80.5% | — | Not comparable |
Inst. Following1 benchmarks
| Benchmark | Phi-4 | Ternary Bonsai 1.7B | Result |
|---|---|---|---|
| AA-IFBenchSource | 23.5% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare Phi-4 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 Phi-4 and Ternary Bonsai 1.7B today?
Phi-4: $0.00 input / $0.00 output per 1M tokens 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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