Model comparison
Grok 4.20 Multi-Agent vs Trinity Large Thinking
Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 38.6 on the Noometry Index. Trinity Large Thinking costs 4.0× less per token, which makes it the better buy when Grok 4.20 Multi-Agent's lead doesn't matter for your workload.
Last verified . 18 shared benchmarks.
Arcee AISummary
- They share 18 benchmarks with published results for both. Grok 4.20 Multi-Agent 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 Grok 4.20 Multi-Agent leads 43.9 to 16.9.
- The biggest single-benchmark swing is NYT Connections (extended): 89.6% for Grok 4.20 Multi-Agent and 16.5% for Trinity Large Thinking.
- Trinity Large Thinking is cheaper at $0.25 / $0.80 per million input/output tokens, against $1.25 / $2.50 for Grok 4.20 Multi-Agent.
- Grok 4.20 Multi-Agent accepts more context: 1M tokens versus 262K.
- Trinity Large Thinking has downloadable open weights; the other is API-only.
Side by side
| Grok 4.20 Multi-Agent | Trinity Large Thinking | |
|---|---|---|
| Provider | xAI | Arcee AI |
| Noometry Index | 46.2 | 38.6 |
| Released | 2026-03-09 | 2026-04-01 |
| Weights | Proprietary | Open |
| Context window | 1M | 262K |
| Max output | 30K | 80K |
| Input $ / M tokens | $1.25 | $0.25 |
| Output $ / M tokens | $2.50 | $0.80 |
| Results tracked | 20 | 24 |
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Category by category
Coding Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 43.0 (#92), Trinity Large Thinking: 34.1 (#244)
| Benchmark | Grok 4.20 Multi-Agent | Trinity Large Thinking |
|---|---|---|
| LMArena Coding | 1457 | 1381 |
| LMArena WebDev | — | 1238 |
| SciCode | — | 36.1% |
Agentic & Tool Use Not comparable
Grok 4.20 Multi-Agent: —, Trinity Large Thinking: —
| Benchmark | Grok 4.20 Multi-Agent | Trinity Large Thinking |
|---|---|---|
| LMArena Search | 1204 | — |
Reasoning Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 43.9 (#48), Trinity Large Thinking: 16.9 (#298)
| Benchmark | Grok 4.20 Multi-Agent | Trinity Large Thinking |
|---|---|---|
| NYT Connections (extended) | 89.6% | 16.5% |
| LMArena Hard Prompts | 1448 | 1350 |
| CritPt | — | 0.9% |
| Thematic Generalization | — | 41.6% |
| Surface Evolver Bench | — | 15.6% |
Math Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 39.4 (#104), Trinity Large Thinking: 37.6 (#149)
| Benchmark | Grok 4.20 Multi-Agent | Trinity Large Thinking |
|---|---|---|
| LMArena Math | 1442 | 1366 |
Knowledge Too close to call
Grok 4.20 Multi-Agent: 40.4 (#119), Trinity Large Thinking: 40.9 (#113)
| Benchmark | Grok 4.20 Multi-Agent | Trinity Large Thinking |
|---|---|---|
| LMArena Expert | 1445 | 1360 |
| Vectara Hallucination Rate | — | 6.9% |
Multimodal Not comparable
Grok 4.20 Multi-Agent: 40.5 (#48), Trinity Large Thinking: —
| Benchmark | Grok 4.20 Multi-Agent | Trinity Large Thinking |
|---|---|---|
| LMArena Vision | 1259 | — |
Multilingual Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 54.4 (#43), Trinity Large Thinking: 46.2 (#160)
| Benchmark | Grok 4.20 Multi-Agent | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | 1440 | 1325 |
| LMArena Chinese | 1475 | 1373 |
| LMArena French | 1466 | 1374 |
| LMArena German | 1456 | 1356 |
| LMArena Japanese | 1405 | 1311 |
| LMArena Korean | 1416 | 1306 |
| LMArena Russian | 1457 | 1337 |
| LMArena Spanish | 1447 | 1357 |
Instruction Following Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 74.8 (#84), Trinity Large Thinking: 70.5 (#162)
| Benchmark | Grok 4.20 Multi-Agent | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | 1420 | 1334 |
Long Context Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 43.7 (#88), Trinity Large Thinking: 41.3 (#144)
| Benchmark | Grok 4.20 Multi-Agent | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | 1431 | 1355 |
Writing & Preference Grok 4.20 Multi-Agent leads
Grok 4.20 Multi-Agent: 64.0 (#59), Trinity Large Thinking: 53.8 (#158)
| Benchmark | Grok 4.20 Multi-Agent | Trinity Large Thinking |
|---|---|---|
| LMArena Text | 1450 | 1340 |
| LMArena Creative Writing | 1436 | 1320 |
| LMArena Multi-Turn | 1452 | 1342 |
Frequently asked questions
Is Grok 4.20 Multi-Agent better than Trinity Large Thinking?
Grok 4.20 Multi-Agent is the stronger model overall, scoring 46.2 to 38.6 on the Noometry Index. Trinity Large Thinking costs 4.0× less per token, which makes it the better buy when Grok 4.20 Multi-Agent's lead doesn't matter for your workload.
Which is cheaper, Grok 4.20 Multi-Agent 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; Grok 4.20 Multi-Agent lists at $1.25 and $2.50.
Is Grok 4.20 Multi-Agent or Trinity Large Thinking better for coding?
Grok 4.20 Multi-Agent scores higher on coding benchmarks: 43.0 versus 34.1 in the Noometry coding category.
Which has the bigger context window?
Grok 4.20 Multi-Agent does, with 1M tokens against 262K.
How many benchmarks do Grok 4.20 Multi-Agent and Trinity Large Thinking share?
18 benchmarks have published results for both models. Grok 4.20 Multi-Agent has 20 scored results on Noometry and Trinity Large Thinking has 24.