Model comparison
GLM-4.7-Flash vs Trinity Large Thinking
GLM-4.7-Flash and Trinity Large Thinking score almost the same on the Noometry Index (38.8 vs 38.6), so choose on price, context window or the category you care about most.
Last verified . 17 shared benchmarks.
Arcee AISummary
- They share 17 benchmarks with published results for both. GLM-4.7-Flash scores higher in 3 categories and Trinity Large Thinking in 5 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in coding, where GLM-4.7-Flash leads 40.6 to 34.1.
- GLM-4.7-Flash is cheaper at $0.06 / $0.40 per million input/output tokens, against $0.25 / $0.80 for Trinity Large Thinking.
- Trinity Large Thinking accepts more context: 262K tokens versus 200K.
Side by side
| GLM-4.7-Flash | Trinity Large Thinking | |
|---|---|---|
| Provider | Z.ai (Zhipu) | Arcee AI |
| Noometry Index | 38.8 | 38.6 |
| Released | 2026-01-19 | 2026-04-01 |
| Weights | Open | Open |
| Context window | 200K | 262K |
| Max output | 131K | 80K |
| Input $ / M tokens | $0.06 | $0.25 |
| Output $ / M tokens | $0.40 | $0.80 |
| Results tracked | 21 | 24 |
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Category by category
Coding GLM-4.7-Flash leads
GLM-4.7-Flash: 40.6 (#135), Trinity Large Thinking: 34.1 (#244)
| Benchmark | GLM-4.7-Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Coding | 1383 | 1381 |
| LMArena WebDev | — | 1238 |
| SciCode | — | 36.1% |
Reasoning GLM-4.7-Flash leads
GLM-4.7-Flash: 20.9 (#229), Trinity Large Thinking: 16.9 (#298)
| Benchmark | GLM-4.7-Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Hard Prompts | 1356 | 1350 |
| NYT Connections (extended) | — | 16.5% |
| CritPt | — | 0.9% |
| Chess Puzzles | 0% | — |
| Thematic Generalization | — | 41.6% |
| Surface Evolver Bench | — | 15.6% |
Math Trinity Large Thinking leads
GLM-4.7-Flash: 36.1 (#173), Trinity Large Thinking: 37.6 (#149)
| Benchmark | GLM-4.7-Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Math | 1355 | 1366 |
| OTIS Mock AIME 2024-2025 | 58.3% | — |
Knowledge Trinity Large Thinking leads
GLM-4.7-Flash: 35.5 (#184), Trinity Large Thinking: 40.9 (#113)
| Benchmark | GLM-4.7-Flash | Trinity Large Thinking |
|---|---|---|
| Vectara Hallucination Rate | 9.3% | 6.9% |
| LMArena Expert | 1357 | 1360 |
| GPQA Diamond | 60.5% | — |
Multilingual Too close to call
GLM-4.7-Flash: 46.5 (#158), Trinity Large Thinking: 46.2 (#160)
| Benchmark | GLM-4.7-Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | 1330 | 1325 |
| LMArena Chinese | 1403 | 1373 |
| LMArena French | 1332 | 1374 |
| LMArena German | 1337 | 1356 |
| LMArena Korean | 1283 | 1306 |
| LMArena Russian | 1332 | 1337 |
| LMArena Spanish | 1350 | 1357 |
| LMArena Japanese | — | 1311 |
Instruction Following Too close to call
GLM-4.7-Flash: 70.1 (#167), Trinity Large Thinking: 70.5 (#162)
| Benchmark | GLM-4.7-Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | 1327 | 1334 |
Long Context Too close to call
GLM-4.7-Flash: 40.9 (#148), Trinity Large Thinking: 41.3 (#144)
| Benchmark | GLM-4.7-Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | 1345 | 1355 |
Writing & Preference Trinity Large Thinking leads
GLM-4.7-Flash: 47.4 (#210), Trinity Large Thinking: 53.8 (#158)
| Benchmark | GLM-4.7-Flash | Trinity Large Thinking |
|---|---|---|
| LMArena Text | 1351 | 1340 |
| LMArena Creative Writing | 1297 | 1320 |
| LMArena Multi-Turn | 1342 | 1342 |
| EQ-Bench Creative Writing | 1125 | — |
Frequently asked questions
Is GLM-4.7-Flash better than Trinity Large Thinking?
GLM-4.7-Flash and Trinity Large Thinking score almost the same on the Noometry Index (38.8 vs 38.6), so choose on price, context window or the category you care about most.
Which is cheaper, GLM-4.7-Flash or Trinity Large Thinking?
GLM-4.7-Flash is cheaper. It lists at $0.06 per million input tokens and $0.40 per million output tokens; Trinity Large Thinking lists at $0.25 and $0.80.
Is GLM-4.7-Flash or Trinity Large Thinking better for coding?
GLM-4.7-Flash scores higher on coding benchmarks: 40.6 versus 34.1 in the Noometry coding category.
Which has the bigger context window?
Trinity Large Thinking does, with 262K tokens against 200K.
How many benchmarks do GLM-4.7-Flash and Trinity Large Thinking share?
17 benchmarks have published results for both models. GLM-4.7-Flash has 21 scored results on Noometry and Trinity Large Thinking has 24.