Model comparison
Qwen3.5-Flash vs Trinity Large Thinking
Qwen3.5-Flash is the stronger model overall, scoring 42.5 to 38.6 on the Noometry Index.
Last verified . 19 shared benchmarks.
Alibaba (Qwen)
Arcee AISummary
- They share 19 benchmarks with published results for both. Qwen3.5-Flash scores higher in 7 categories and Trinity Large Thinking in 1 category; 6 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Qwen3.5-Flash leads 33.7 to 16.9.
- Qwen3.5-Flash is cheaper at $0.10 / $0.40 per million input/output tokens, against $0.25 / $0.80 for Trinity Large Thinking.
- Qwen3.5-Flash accepts more context: 1M tokens versus 262K.
- Trinity Large Thinking has downloadable open weights; the other is API-only.
Side by side
| Qwen3.5-Flash | Trinity Large Thinking | |
|---|---|---|
| Provider | Alibaba (Qwen) | Arcee AI |
| Noometry Index | 42.5 | 38.6 |
| Released | 2026-02-23 | 2026-04-01 |
| Weights | Proprietary | Open |
| Context window | 1M | 262K |
| Max output | 66K | 80K |
| Input $ / M tokens | $0.10 | $0.25 |
| Output $ / M tokens | $0.40 | $0.80 |
| Results tracked | 32 | 24 |
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Category by category
Coding Too close to call
Qwen3.5-Flash: 34.2 (#242), Trinity Large Thinking: 34.1 (#244)
| Benchmark | Qwen3.5-Flash | Trinity Large Thinking |
|---|---|---|
| LMArena WebDev | 1244 | 1238 |
| LMArena Coding | 1412 | 1381 |
| SciCode | — | 36.1% |
| ALE-Bench | 221.8 | — |
Agentic & Tool Use Not comparable
Qwen3.5-Flash: —, Trinity Large Thinking: —
| Benchmark | Qwen3.5-Flash | Trinity Large Thinking |
|---|---|---|
| Vending-Bench 2 | 462.69 | — |
Reasoning Qwen3.5-Flash leads
Qwen3.5-Flash: 33.7 (#72), Trinity Large Thinking: 16.9 (#298)
| Benchmark | Qwen3.5-Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Hard Prompts | 1403 | 1350 |
| NYT Connections (extended) | — | 16.5% |
| CritPt | — | 0.9% |
| Chess Puzzles | 21% | — |
| Thematic Generalization | — | 41.6% |
| Mystery Game Puzzles | 20% | — |
| DTBench | 82.9% | — |
| LMCA | 29.1% | — |
| Surface Evolver Bench | — | 15.6% |
| Epoch Capabilities Index | 143.98 | — |
Math Too close to call
Qwen3.5-Flash: 37.4 (#158), Trinity Large Thinking: 37.6 (#149)
| Benchmark | Qwen3.5-Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Math | 1407 | 1366 |
| FrontierMath (Tiers 1-3) | 18.2% | — |
| OTIS Mock AIME 2024-2025 | 84.4% | — |
| FrontierMath (Feb 2025 set) | 6.2% | — |
| FrontierMath Tier 4 (v1) | 0% | — |
Knowledge Qwen3.5-Flash leads
Qwen3.5-Flash: 43.2 (#93), Trinity Large Thinking: 40.9 (#113)
| Benchmark | Qwen3.5-Flash | Trinity Large Thinking |
|---|---|---|
| Vectara Hallucination Rate | 10.5% | 6.9% |
| LMArena Expert | 1407 | 1360 |
| GPQA Diamond | 82.3% | — |
| SimpleQA Verified | 20.3% | — |
Multilingual Qwen3.5-Flash leads
Qwen3.5-Flash: 50.5 (#121), Trinity Large Thinking: 46.2 (#160)
| Benchmark | Qwen3.5-Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | 1385 | 1325 |
| LMArena Chinese | 1446 | 1373 |
| LMArena French | 1412 | 1374 |
| LMArena German | 1390 | 1356 |
| LMArena Japanese | 1368 | 1311 |
| LMArena Korean | 1344 | 1306 |
| LMArena Russian | 1379 | 1337 |
| LMArena Spanish | 1400 | 1357 |
Instruction Following Qwen3.5-Flash leads
Qwen3.5-Flash: 72.6 (#139), Trinity Large Thinking: 70.5 (#162)
| Benchmark | Qwen3.5-Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | 1374 | 1334 |
Long Context Qwen3.5-Flash leads
Qwen3.5-Flash: 42.4 (#124), Trinity Large Thinking: 41.3 (#144)
| Benchmark | Qwen3.5-Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | 1392 | 1355 |
Writing & Preference Qwen3.5-Flash leads
Qwen3.5-Flash: 57.9 (#122), Trinity Large Thinking: 53.8 (#158)
| Benchmark | Qwen3.5-Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Text | 1397 | 1340 |
| LMArena Creative Writing | 1343 | 1320 |
| LMArena Multi-Turn | 1393 | 1342 |
Frequently asked questions
Is Qwen3.5-Flash better than Trinity Large Thinking?
Qwen3.5-Flash is the stronger model overall, scoring 42.5 to 38.6 on the Noometry Index.
Which is cheaper, Qwen3.5-Flash or Trinity Large Thinking?
Qwen3.5-Flash is cheaper. It lists at $0.10 per million input tokens and $0.40 per million output tokens; Trinity Large Thinking lists at $0.25 and $0.80.
Is Qwen3.5-Flash or Trinity Large Thinking better for coding?
They score almost the same on coding (34.2 vs 34.1); test both on your own repository before choosing.
Which has the bigger context window?
Qwen3.5-Flash does, with 1M tokens against 262K.
How many benchmarks do Qwen3.5-Flash and Trinity Large Thinking share?
19 benchmarks have published results for both models. Qwen3.5-Flash has 32 scored results on Noometry and Trinity Large Thinking has 24.