Model comparison
Qwen3.5 27B vs Trinity Large Thinking
Qwen3.5 27B is the stronger model overall, scoring 41.9 to 38.6 on the Noometry Index. Trinity Large Thinking costs 2.1× less per token, which makes it the better buy when Qwen3.5 27B's lead doesn't matter for your workload.
Last verified . 21 shared benchmarks.
Alibaba (Qwen)
Arcee AISummary
- They share 21 benchmarks with published results for both. Qwen3.5 27B scores higher in 7 categories and Trinity Large Thinking in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3.5 27B leads 27.5 to 16.9.
- The biggest single-benchmark swing is NYT Connections (extended): 47.9% for Qwen3.5 27B and 16.5% for Trinity Large Thinking.
- Trinity Large Thinking is cheaper at $0.25 / $0.80 per million input/output tokens, against $0.30 / $2.40 for Qwen3.5 27B.
Side by side
| Qwen3.5 27B | Trinity Large Thinking | |
|---|---|---|
| Provider | Alibaba (Qwen) | Arcee AI |
| Noometry Index | 41.9 | 38.6 |
| Released | 2026-02-23 | 2026-04-01 |
| Weights | Open | Open |
| Context window | 262K | 262K |
| Max output | 66K | 80K |
| Input $ / M tokens | $0.30 | $0.25 |
| Output $ / M tokens | $2.40 | $0.80 |
| Results tracked | 28 | 24 |
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Category by category
Coding Qwen3.5 27B leads
Qwen3.5 27B: 38.9 (#168), Trinity Large Thinking: 34.1 (#244)
| Benchmark | Qwen3.5 27B | Trinity Large Thinking |
|---|---|---|
| LMArena WebDev | 1358 | 1238 |
| LMArena Coding | 1427 | 1381 |
| SciCode | — | 36.1% |
| WeirdML | 39.5% | — |
| ALE-Bench | 349.45 | — |
Agentic & Tool Use Not comparable
Qwen3.5 27B: —, Trinity Large Thinking: —
| Benchmark | Qwen3.5 27B | Trinity Large Thinking |
|---|---|---|
| Vending-Bench 2 | 201.98 | — |
Reasoning Qwen3.5 27B leads
Qwen3.5 27B: 27.5 (#117), Trinity Large Thinking: 16.9 (#298)
| Benchmark | Qwen3.5 27B | Trinity Large Thinking |
|---|---|---|
| NYT Connections (extended) | 47.9% | 16.5% |
| Thematic Generalization | 45.5% | 41.6% |
| LMArena Hard Prompts | 1414 | 1350 |
| CritPt | — | 0.9% |
| DTBench | 82.4% | — |
| LMCA | 34% | — |
| Surface Evolver Bench | — | 15.6% |
Math Qwen3.5 27B leads
Qwen3.5 27B: 38.8 (#127), Trinity Large Thinking: 37.6 (#149)
| Benchmark | Qwen3.5 27B | Trinity Large Thinking |
|---|---|---|
| LMArena Math | 1429 | 1366 |
| MathArena Final-Answer Competitions | 56.7% | — |
Knowledge Trinity Large Thinking leads
Qwen3.5 27B: 38.0 (#150), Trinity Large Thinking: 40.9 (#113)
| Benchmark | Qwen3.5 27B | Trinity Large Thinking |
|---|---|---|
| Vectara Hallucination Rate | 12.1% | 6.9% |
| LMArena Expert | 1428 | 1360 |
Multimodal Not comparable
Qwen3.5 27B: 39.4 (#59), Trinity Large Thinking: —
| Benchmark | Qwen3.5 27B | Trinity Large Thinking |
|---|---|---|
| LMArena Vision | 1241 | — |
Multilingual Qwen3.5 27B leads
Qwen3.5 27B: 50.8 (#115), Trinity Large Thinking: 46.2 (#160)
| Benchmark | Qwen3.5 27B | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | 1390 | 1325 |
| LMArena Chinese | 1478 | 1373 |
| LMArena French | 1410 | 1374 |
| LMArena German | 1393 | 1356 |
| LMArena Japanese | 1345 | 1311 |
| LMArena Korean | 1358 | 1306 |
| LMArena Russian | 1390 | 1337 |
| LMArena Spanish | 1407 | 1357 |
Instruction Following Qwen3.5 27B leads
Qwen3.5 27B: 73.5 (#119), Trinity Large Thinking: 70.5 (#162)
| Benchmark | Qwen3.5 27B | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | 1393 | 1334 |
Long Context Qwen3.5 27B leads
Qwen3.5 27B: 43.1 (#106), Trinity Large Thinking: 41.3 (#144)
| Benchmark | Qwen3.5 27B | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | 1413 | 1355 |
Writing & Preference Qwen3.5 27B leads
Qwen3.5 27B: 59.3 (#111), Trinity Large Thinking: 53.8 (#158)
| Benchmark | Qwen3.5 27B | Trinity Large Thinking |
|---|---|---|
| LMArena Text | 1409 | 1340 |
| LMArena Creative Writing | 1362 | 1320 |
| LMArena Multi-Turn | 1410 | 1342 |
Frequently asked questions
Is Qwen3.5 27B better than Trinity Large Thinking?
Qwen3.5 27B is the stronger model overall, scoring 41.9 to 38.6 on the Noometry Index. Trinity Large Thinking costs 2.1× less per token, which makes it the better buy when Qwen3.5 27B's lead doesn't matter for your workload.
Which is cheaper, Qwen3.5 27B or Trinity Large Thinking?
Trinity Large Thinking is cheaper. It lists at $0.25 per million input tokens and $0.80 per million output tokens; Qwen3.5 27B lists at $0.30 and $2.40.
Is Qwen3.5 27B or Trinity Large Thinking better for coding?
Qwen3.5 27B scores higher on coding benchmarks: 38.9 versus 34.1 in the Noometry coding category.
Which has the bigger context window?
Both accept 262K tokens.
How many benchmarks do Qwen3.5 27B and Trinity Large Thinking share?
21 benchmarks have published results for both models. Qwen3.5 27B has 28 scored results on Noometry and Trinity Large Thinking has 24.