Model comparison
Qwen3.5-122B-A10B vs Ternary Bonsai 4B
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: Qwen3.5-122B-A10B #47 (Supported); Ternary Bonsai 4B unranked (Not scored). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Qwen3.5-122B-A10B and Ternary Bonsai 4B share 0 comparable benchmark results. 0 of 8 categories are comparable. 31 results are unique to Qwen3.5-122B-A10B; 0 to Ternary Bonsai 4B.
Updated July 21, 2026- Shared results
- 0
- Qwen3.5-122B-A10B only
- 31
- Ternary Bonsai 4B only
- 0
- Comparable categories
- 0 / 8
Benchmark data for Qwen3.5-122B-A10B and Ternary Bonsai 4B 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 4B yet. This comparison is currently limited to metadata such as context window, reasoning mode, and pricing where available.
Qwen3.5-122B-A10B has the larger context window at 262K, compared with 32K for Ternary Bonsai 4B.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Qwen3.5-122B-A10B | Ternary Bonsai 4B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Qwen3.5-122B-A10B$0 input / $0 output | Ternary Bonsai 4B$0 input / $0 output | Listed prices are equal. |
| Generation speedtokens per second | Qwen3.5-122B-A10BNot available | Ternary Bonsai 4BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Qwen3.5-122B-A10BNot available | Ternary Bonsai 4BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Qwen3.5-122B-A10B262K | Ternary Bonsai 4B32K | Qwen3.5-122B-A10B lists the larger context window. |
Benchmark Deep Dive
Agentic7 benchmarks
| Benchmark | Qwen3.5-122B-A10B | Ternary Bonsai 4B | Result |
|---|---|---|---|
| Terminal-Bench 2.0Source | 49.4% | — | Not comparable |
| BrowseCompSource | 63.8% | — | Not comparable |
| OSWorld-VerifiedSource | 58% | — | Not comparable |
| τ²-bench resultsSource | 93.6% | — | Not comparable |
| AA Agentic IndexSource | 20.7% | — | Not comparable |
| GDPval-AASource | 23.9% | — | Not comparable |
| GDPval-AASource | 978 | — | Not comparable |
Coding3 benchmarks
Reasoning3 benchmarks
Knowledge9 benchmarks
| Benchmark | Qwen3.5-122B-A10B | Ternary Bonsai 4B | Result |
|---|---|---|---|
| MMLU-ProSource | 86.7% | — | Not comparable |
| SuperGPQASource | 67.1% | — | Not comparable |
| GPQASource | 86.6% | — | Not comparable |
| Artificial Analysis Intelligence IndexSource | 32.3% | — | Not comparable |
| AA-GPQA DiamondSource | 85.7% | — | Not comparable |
| AA-HLESource | 23.4% | — | Not comparable |
| AA-Omniscience IndexSource | -39.6% | — | Not comparable |
| AA-Omniscience AccuracySource | 24.7% | — | Not comparable |
| AA-Omniscience Hallucination RateSource | 85.5% | — | Not comparable |
Multilingual1 benchmarks
| Benchmark | Qwen3.5-122B-A10B | Ternary Bonsai 4B | Result |
|---|---|---|---|
| MMLU-ProXSource | 82.2% | — | Not comparable |
Multimodal6 benchmarks
Frequently Asked Questions (3)
Can I compare Qwen3.5-122B-A10B and Ternary Bonsai 4B 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 Qwen3.5-122B-A10B and Ternary Bonsai 4B today?
Qwen3.5-122B-A10B: $0.00 input / $0.00 output per 1M tokens Ternary 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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