Model comparison
Qwen3.5 35B-A3B vs Trinity Large Thinking
Qwen3.5 35B-A3B is the stronger model overall, scoring 42.0 to 38.6 on the Noometry Index. Trinity Large Thinking costs 1.8× less per token, which makes it the better buy when Qwen3.5 35B-A3B'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 35B-A3B scores higher in 7 categories and Trinity Large Thinking in 1 category; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3.5 35B-A3B leads 24.6 to 16.9.
- The biggest single-benchmark swing is SciCode: 29.3% for Qwen3.5 35B-A3B and 36.1% for Trinity Large Thinking.
- Trinity Large Thinking is cheaper at $0.25 / $0.80 per million input/output tokens, against $0.25 / $2 for Qwen3.5 35B-A3B.
Side by side
| Qwen3.5 35B-A3B | Trinity Large Thinking | |
|---|---|---|
| Provider | Alibaba (Qwen) | Arcee AI |
| Noometry Index | 42.0 | 38.6 |
| Released | 2026-02-01 | 2026-04-01 |
| Weights | Open | Open |
| Context window | 262K | 262K |
| Max output | 66K | 80K |
| Input $ / M tokens | $0.25 | $0.25 |
| Output $ / M tokens | $2 | $0.80 |
| Results tracked | 28 | 24 |
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Category by category
Coding Too close to call
Qwen3.5 35B-A3B: 33.8 (#251), Trinity Large Thinking: 34.1 (#244)
| Benchmark | Qwen3.5 35B-A3B | Trinity Large Thinking |
|---|---|---|
| LMArena WebDev | 1254 | 1238 |
| SciCode | 29.3% | 36.1% |
| LMArena Coding | 1410 | 1381 |
Reasoning Qwen3.5 35B-A3B leads
Qwen3.5 35B-A3B: 24.6 (#161), Trinity Large Thinking: 16.9 (#298)
| Benchmark | Qwen3.5 35B-A3B | Trinity Large Thinking |
|---|---|---|
| CritPt | 0.6% | 0.9% |
| LMArena Hard Prompts | 1400 | 1350 |
| NYT Connections (extended) | — | 16.5% |
| Chess Puzzles | 10% | — |
| Thematic Generalization | — | 41.6% |
| DTBench | 80% | — |
| LMCA | 29.5% | — |
| Surface Evolver Bench | — | 15.6% |
| Epoch Capabilities Index | 142.52 | — |
Math Qwen3.5 35B-A3B leads
Qwen3.5 35B-A3B: 39.9 (#97), Trinity Large Thinking: 37.6 (#149)
| Benchmark | Qwen3.5 35B-A3B | Trinity Large Thinking |
|---|---|---|
| LMArena Math | 1404 | 1366 |
| MathArena Final-Answer Competitions | 56% | — |
| OTIS Mock AIME 2024-2025 | 70% | — |
Knowledge Qwen3.5 35B-A3B leads
Qwen3.5 35B-A3B: 47.8 (#79), Trinity Large Thinking: 40.9 (#113)
| Benchmark | Qwen3.5 35B-A3B | Trinity Large Thinking |
|---|---|---|
| Vectara Hallucination Rate | 10.5% | 6.9% |
| LMArena Expert | 1408 | 1360 |
| GPQA Diamond | 83.5% | — |
Multilingual Qwen3.5 35B-A3B leads
Qwen3.5 35B-A3B: 50.0 (#127), Trinity Large Thinking: 46.2 (#160)
| Benchmark | Qwen3.5 35B-A3B | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | 1378 | 1325 |
| LMArena Chinese | 1457 | 1373 |
| LMArena French | 1412 | 1374 |
| LMArena German | 1367 | 1356 |
| LMArena Japanese | 1325 | 1311 |
| LMArena Korean | 1356 | 1306 |
| LMArena Russian | 1376 | 1337 |
| LMArena Spanish | 1392 | 1357 |
Instruction Following Qwen3.5 35B-A3B leads
Qwen3.5 35B-A3B: 72.8 (#128), Trinity Large Thinking: 70.5 (#162)
| Benchmark | Qwen3.5 35B-A3B | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | 1379 | 1334 |
Long Context Qwen3.5 35B-A3B leads
Qwen3.5 35B-A3B: 42.4 (#127), Trinity Large Thinking: 41.3 (#144)
| Benchmark | Qwen3.5 35B-A3B | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | 1389 | 1355 |
Writing & Preference Qwen3.5 35B-A3B leads
Qwen3.5 35B-A3B: 57.9 (#124), Trinity Large Thinking: 53.8 (#158)
| Benchmark | Qwen3.5 35B-A3B | Trinity Large Thinking |
|---|---|---|
| LMArena Text | 1395 | 1340 |
| LMArena Creative Writing | 1346 | 1320 |
| LMArena Multi-Turn | 1390 | 1342 |
Frequently asked questions
Is Qwen3.5 35B-A3B better than Trinity Large Thinking?
Qwen3.5 35B-A3B is the stronger model overall, scoring 42.0 to 38.6 on the Noometry Index. Trinity Large Thinking costs 1.8× less per token, which makes it the better buy when Qwen3.5 35B-A3B's lead doesn't matter for your workload.
Which is cheaper, Qwen3.5 35B-A3B 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 35B-A3B lists at $0.25 and $2.
Is Qwen3.5 35B-A3B or Trinity Large Thinking better for coding?
They score almost the same on coding (33.8 vs 34.1); test both on your own repository before choosing.
Which has the bigger context window?
Both accept 262K tokens.
How many benchmarks do Qwen3.5 35B-A3B and Trinity Large Thinking share?
21 benchmarks have published results for both models. Qwen3.5 35B-A3B has 28 scored results on Noometry and Trinity Large Thinking has 24.