Model comparison
Claude Opus 4.7 (Adaptive) 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: Claude Opus 4.7 (Adaptive) #27 (Estimated); Ternary Bonsai 1.7B unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Claude Opus 4.7 (Adaptive) and Ternary Bonsai 1.7B share 0 comparable benchmark results. 0 of 8 categories are comparable. 38 results are unique to Claude Opus 4.7 (Adaptive); 0 to Ternary Bonsai 1.7B.
Updated July 23, 2026- Shared results
- 0
- Claude Opus 4.7 (Adaptive) only
- 38
- Ternary Bonsai 1.7B only
- 0
- Comparable categories
- 0 / 8
Benchmark data for Claude Opus 4.7 (Adaptive) 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.
Claude Opus 4.7 (Adaptive) is priced at $5.00 input / $25.00 output per 1M tokens, versus $0.00 input / $0.00 output per 1M tokens for Ternary Bonsai 1.7B. Claude Opus 4.7 (Adaptive) has the larger context window at 1M, 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 | Claude Opus 4.7 (Adaptive) | Ternary Bonsai 1.7B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Claude Opus 4.7 (Adaptive)$5 input / $25 output | Ternary Bonsai 1.7B$0 input / $0 output | Ternary Bonsai 1.7B has the lower combined listed price. |
| Generation speedtokens per second | Claude Opus 4.7 (Adaptive)Not available | Ternary Bonsai 1.7BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Claude Opus 4.7 (Adaptive)Not available | Ternary Bonsai 1.7BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Claude Opus 4.7 (Adaptive)1M | Ternary Bonsai 1.7B32K | Claude Opus 4.7 (Adaptive) lists the larger context window. |
Benchmark Deep Dive
Agentic12 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | Ternary Bonsai 1.7B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 69.4% | — | Not comparable |
| BrowseCompSource | 79.3% | — | Not comparable |
| MCP AtlasSource | 77.3% | — | Not comparable |
| OSWorld-VerifiedSource | 78% | — | Not comparable |
| CyberGymSource | 73.1% | — | Not comparable |
| AA Agentic IndexSource | 44.4% | — | Not comparable |
| τ²-bench resultsSource | 88.6% | — | Not comparable |
| GDPval-AASource | 49.8% | — | Not comparable |
| GDPval-AASource | 1495 | — | Not comparable |
| OSWorld 2.0Source | 18.2% | — | Not comparable |
| JobBenchSource | 45.9% | — | Not comparable |
| AA ITBenchSource | 46.7% | — | Not comparable |
Coding5 benchmarks
Reasoning4 benchmarks
Knowledge10 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | Ternary Bonsai 1.7B | Result |
|---|---|---|---|
| GPQASource | 94.2% | — | Not comparable |
| GPQA-DSource | 94.2% | — | Not comparable |
| HLESource | 54.7% | — | Not comparable |
| HLE w/o toolsSource | 46.9% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 53.5% | — | Not comparable |
| AA-GPQA DiamondSource | 91.4% | — | Not comparable |
| AA-HLESource | 39.6% | — | Not comparable |
| AA-Omniscience IndexSource | 26.2% | — | Not comparable |
| AA-Omniscience AccuracySource | 45.8% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 36.2% | — | Not comparable |
Math1 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | Ternary Bonsai 1.7B | Result |
|---|---|---|---|
| FrontierMath (legacy)Source | 43.8% | — | Not comparable |
Multimodal5 benchmarks
Inst. Following1 benchmarks
| Benchmark | Claude Opus 4.7 (Adaptive) | Ternary Bonsai 1.7B | Result |
|---|---|---|---|
| AA-IFBenchSource | 58.6% | — | Not comparable |
Frequently Asked Questions (3)
Can I compare Claude Opus 4.7 (Adaptive) 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 Claude Opus 4.7 (Adaptive) and Ternary Bonsai 1.7B today?
Claude Opus 4.7 (Adaptive): $5.00 input / $25.00 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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