Model comparison
Llama 3.1-70B vs Trinity Large Thinking
Trinity Large Thinking is the stronger model overall, scoring 38.6 to 29.6 on the Noometry Index.
Last verified . 17 shared benchmarks.
Meta
Arcee AISummary
- They share 17 benchmarks with published results for both. Llama 3.1-70B scores higher in 1 category and Trinity Large Thinking in 7 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Trinity Large Thinking leads 37.6 to 13.5.
- Both cost about the same: $0.40 input and $0.40 output per million tokens.
- Trinity Large Thinking accepts more context: 262K tokens versus 128K.
Side by side
| Llama 3.1-70B | Trinity Large Thinking | |
|---|---|---|
| Provider | Meta | Arcee AI |
| Noometry Index | 29.6 | 38.6 |
| Released | 2024-07-23 | 2026-04-01 |
| Weights | Open | Open |
| Context window | 128K | 262K |
| Max output | 4K | 80K |
| Input $ / M tokens | $0.40 | $0.25 |
| Output $ / M tokens | $0.40 | $0.80 |
| Results tracked | 35 | 24 |
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Category by category
Coding Trinity Large Thinking leads
Llama 3.1-70B: 30.3 (#296), Trinity Large Thinking: 34.1 (#244)
| Benchmark | Llama 3.1-70B | Trinity Large Thinking |
|---|---|---|
| LMArena Coding | 1260 | 1381 |
| LMArena WebDev | — | 1238 |
| SciCode | — | 36.1% |
| WeirdML | 9% | — |
| BigCodeBench Instruct | 46.1% | — |
| BigCodeBench Complete | 54.8% | — |
Agentic & Tool Use Not comparable
Llama 3.1-70B: 25.1 (#112), Trinity Large Thinking: —
| Benchmark | Llama 3.1-70B | Trinity Large Thinking |
|---|---|---|
| TheAgentCompany | 6.9% | — |
| BALROG | 27.9% | — |
Reasoning Llama 3.1-70B leads
Llama 3.1-70B: 21.6 (#220), Trinity Large Thinking: 16.9 (#298)
| Benchmark | Llama 3.1-70B | Trinity Large Thinking |
|---|---|---|
| LMArena Hard Prompts | 1241 | 1350 |
| NYT Connections (extended) | — | 16.5% |
| CritPt | — | 0.9% |
| Thematic Generalization | — | 41.6% |
| DTBench | 60% | — |
| LMCA | 14.8% | — |
| Surface Evolver Bench | — | 15.6% |
| Epoch Capabilities Index | 125.92 | — |
Math Trinity Large Thinking leads
Llama 3.1-70B: 13.5 (#304), Trinity Large Thinking: 37.6 (#149)
| Benchmark | Llama 3.1-70B | Trinity Large Thinking |
|---|---|---|
| LMArena Math | 1252 | 1366 |
| OTIS Mock AIME 2024-2025 | 3.6% | — |
| Omni-MATH | 21% | — |
| MATH Level 5 | 36.7% | — |
Knowledge Trinity Large Thinking leads
Llama 3.1-70B: 24.2 (#269), Trinity Large Thinking: 40.9 (#113)
| Benchmark | Llama 3.1-70B | Trinity Large Thinking |
|---|---|---|
| LMArena Expert | 1209 | 1360 |
| GPQA Diamond | 44.2% | — |
| MMLU-Pro | 65.3% | — |
| Vectara Hallucination Rate | — | 6.9% |
| GPQA (HELM) | 42.6% | — |
| MMLU | 80.1% | — |
Multilingual Trinity Large Thinking leads
Llama 3.1-70B: 38.8 (#225), Trinity Large Thinking: 46.2 (#160)
| Benchmark | Llama 3.1-70B | Trinity Large Thinking |
|---|---|---|
| LMArena Non-English | 1219 | 1325 |
| LMArena Chinese | 1215 | 1373 |
| LMArena French | 1261 | 1374 |
| LMArena German | 1222 | 1356 |
| LMArena Japanese | 1132 | 1311 |
| LMArena Korean | 1140 | 1306 |
| LMArena Russian | 1234 | 1337 |
| LMArena Spanish | 1253 | 1357 |
Instruction Following Trinity Large Thinking leads
Llama 3.1-70B: 65.3 (#223), Trinity Large Thinking: 70.5 (#162)
| Benchmark | Llama 3.1-70B | Trinity Large Thinking |
|---|---|---|
| LMArena Instruction Following | 1231 | 1334 |
| IFEval | 82.1% | — |
Long Context Trinity Large Thinking leads
Llama 3.1-70B: 37.6 (#214), Trinity Large Thinking: 41.3 (#144)
| Benchmark | Llama 3.1-70B | Trinity Large Thinking |
|---|---|---|
| LMArena Longer Query | 1241 | 1355 |
Writing & Preference Trinity Large Thinking leads
Llama 3.1-70B: 35.4 (#267), Trinity Large Thinking: 53.8 (#158)
| Benchmark | Llama 3.1-70B | Trinity Large Thinking |
|---|---|---|
| LMArena Text | 1261 | 1340 |
| LMArena Creative Writing | 1232 | 1320 |
| LMArena Multi-Turn | 1256 | 1342 |
| EQ-Bench Creative Writing | 784 | — |
| WildBench | 75.8% | — |
Frequently asked questions
Is Llama 3.1-70B better than Trinity Large Thinking?
Trinity Large Thinking is the stronger model overall, scoring 38.6 to 29.6 on the Noometry Index.
Which is cheaper, Llama 3.1-70B 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; Llama 3.1-70B lists at $0.40 and $0.40.
Is Llama 3.1-70B or Trinity Large Thinking better for coding?
Trinity Large Thinking scores higher on coding benchmarks: 34.1 versus 30.3 in the Noometry coding category.
Which has the bigger context window?
Trinity Large Thinking does, with 262K tokens against 128K.
How many benchmarks do Llama 3.1-70B and Trinity Large Thinking share?
17 benchmarks have published results for both models. Llama 3.1-70B has 35 scored results on Noometry and Trinity Large Thinking has 24.