Model comparison
Agents-A1 vs Qwen3.5-27B
Head-to-head evidence from 3 shared benchmark results across 3 categories. Overall scores shown here use the public BenchAlign v5 ranking lane.
Public leaderboard positions: Agents-A1 unranked (Not scored); Qwen3.5-27B #45 (Supported). Intervals and evidence labels describe ranking uncertainty, not a guarantee for a specific workload.
Evidence parity. Agents-A1 and Qwen3.5-27B share 3 comparable benchmark results. 4 of 8 categories are comparable. 3 results are unique to Agents-A1; 25 to Qwen3.5-27B.
Updated July 23, 2026- Shared results
- 3
- Agents-A1 only
- 3
- Qwen3.5-27B only
- 25
- Comparable categories
- 4 / 8
Treat this as a split decision. Agents-A1 makes more sense if agentic is the priority; Qwen3.5-27B is the better fit if knowledge is the priority.
Confidence note. This is a partial-evidence comparison with 3 shared benchmark results across 3 evidence categories; 4 of 8 categories currently have scoreable aggregates for both models. Treat the verdict as directional until coverage is more balanced.
Why this result
Agents-A1 and Qwen3.5-27B finish on the same BenchAlign overall score, so this is less about a single winner and more about where the edge shows up. The BenchAlign headline says tie; the benchmark table is where the real choice happens.
Category breakdown
Exact category averages are shown below. Not measured means BenchLM does not have enough sourced public coverage for that model and category.
| Category | Agents-A1 | Δ | Qwen3.5-27B |
|---|---|---|---|
| Knowledge | Agents-A147.6 | Margin→ 35.1 | Qwen3.5-27B82.7 |
| Agentic | Agents-A175.5 | Margin← 23.5 | Qwen3.5-27B52.0 |
| Reasoning | Agents-A160.2 | Margin→ 0.4 | Qwen3.5-27B60.6 |
| Inst. Following | Agents-A194.8 | Margin→ 0.2 | Qwen3.5-27B95.0 |
| Coding | Agents-A1Not measured | MarginNo overlap | Qwen3.5-27B64.9 |
| Multilingual | Agents-A1Not measured | MarginNo overlap | Qwen3.5-27B82.2 |
Decisive benchmark drivers
The largest measured benchmark gaps in this matchup, with exact reported values.
More
- Source ↗
BrowseComp
AgenticA 75.5%B 61%Winner: Agents-A1Δ 14.5BrowseComp: Agents-A1 scored 75.5%; Qwen3.5-27B scored 61%. Agents-A1 wins this benchmark. - Source ↗
LongBench v2
ReasoningA 60.2%B 60.6%Winner: Qwen3.5-27BΔ 0.4LongBench v2: Agents-A1 scored 60.2%; Qwen3.5-27B scored 60.6%. Qwen3.5-27B wins this benchmark. - Source ↗
IFEval
Inst. FollowingA 94.8%B 95%Winner: Qwen3.5-27BΔ 0.2IFEval: Agents-A1 scored 94.8%; Qwen3.5-27B scored 95%. Qwen3.5-27B wins this benchmark.
Operational comparison
Runtime and commercial metrics are compared only when both models have a complete sourced value.
| Metric | Agents-A1 | Qwen3.5-27B | Comparison |
|---|---|---|---|
| Input / output priceUSD per 1M tokens | Agents-A1Not available | Qwen3.5-27B$0 input / $0 output | A complete price comparison is not available. |
| Generation speedtokens per second | Agents-A1Not available | Qwen3.5-27BNot available | A complete speed comparison is not available. |
| First-answer latencyseconds to first token | Agents-A1Not available | Qwen3.5-27BNot available | A complete latency comparison is not available. |
| Context windowmaximum listed tokens | Agents-A1262K | Qwen3.5-27B262K | Listed context windows are equal. |
Benchmark Deep Dive
AgenticAgents-A1 wins7 benchmarks
| Benchmark | Agents-A1 | Qwen3.5-27B | Result |
|---|---|---|---|
| BrowseCompSource | 75.5% | 61% | Agents-A1 leads |
| HLE w/ toolsSource | 47.6% | — | Not comparable |
| VITA-BenchSource | 38.8% | — | Not comparable |
| Terminal-Bench 2.0Source | — | 41.6% | Not comparable |
| OSWorld-VerifiedSource | — | 56.2% | Not comparable |
| τ²-bench resultsSource | — | 93.9% | Not comparable |
| Gert LabsSource | — | 39.41% | Not comparable |
Coding3 benchmarks
ReasoningQwen3.5-27B wins3 benchmarks
KnowledgeQwen3.5-27B wins10 benchmarks
| Benchmark | Agents-A1 | Qwen3.5-27B | Result |
|---|---|---|---|
| HLESource | 47.6% | — | Not comparable |
| MMLU-ProSource | — | 86.1% | Not comparable |
| SuperGPQASource | — | 65.6% | Not comparable |
| GPQASource | — | 85.5% | Not comparable |
| Artificial Analysis Intelligence IndexSource | — | 33.8% | Not comparable |
| AA-GPQA DiamondSource | — | 85.8% | Not comparable |
| AA-HLESource | — | 22.2% | Not comparable |
| AA-Omniscience IndexSource | — | -42.0% | Not comparable |
| AA-Omniscience AccuracySource | — | 21.0% | Not comparable |
| AA-Omniscience Hallucination RateSource | — | 79.7% | Not comparable |
Multilingual1 benchmarks
| Benchmark | Agents-A1 | Qwen3.5-27B | Result |
|---|---|---|---|
| MMLU-ProXSource | — | 82.2% | Not comparable |
Multimodal5 benchmarks
Frequently Asked Questions (5)
Which is better, Agents-A1 or Qwen3.5-27B?
Agents-A1 and Qwen3.5-27B are tied on the BenchAlign overall score, so the right pick depends on which category matters most for your use case.
Which is better for knowledge tasks, Agents-A1 or Qwen3.5-27B?
Qwen3.5-27B has the edge for knowledge tasks in this comparison, averaging 82.7 versus 47.6. Agents-A1 stays close enough that the answer can still flip depending on your workload.
Which is better for reasoning, Agents-A1 or Qwen3.5-27B?
Qwen3.5-27B has the edge for reasoning in this comparison, averaging 60.6 versus 60.2. Inside this category, LongBench v2 is the benchmark that creates the most daylight between them.
Which is better for agentic tasks, Agents-A1 or Qwen3.5-27B?
Agents-A1 has the edge for agentic tasks in this comparison, averaging 75.5 versus 52. Inside this category, BrowseComp is the benchmark that creates the most daylight between them.
Which is better for instruction following, Agents-A1 or Qwen3.5-27B?
Qwen3.5-27B has the edge for instruction following in this comparison, averaging 95 versus 94.8. Inside this category, IFEval is the benchmark that creates the most daylight between them.
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