Model comparison

Gemini 3.1 Pro Preview vs Trinity Large Thinking

Gemini 3.1 Pro Preview is the stronger model overall, scoring 56.7 to 38.6 on the Noometry Index. Trinity Large Thinking costs 12× less per token, which makes it the better buy when Gemini 3.1 Pro Preview's lead doesn't matter for your workload.

Last verified . 23 shared benchmarks.

Gemini 3.1 Pro Preview Google

56.7

Rank #23 Confirmed

Trinity Large Thinking Arcee AI

38.6

Rank #185 Confirmed

Summary

  • They share 23 benchmarks with published results for both. Gemini 3.1 Pro Preview scores higher in 8 categories and Trinity Large Thinking in 0 categories; 8 gaps are clear of the uncertainty.
  • The widest gap is in reasoning, where Gemini 3.1 Pro Preview leads 71.7 to 16.9.
  • The biggest single-benchmark swing is NYT Connections (extended): 97.4% for Gemini 3.1 Pro Preview and 16.5% for Trinity Large Thinking.
  • Trinity Large Thinking is cheaper at $0.25 / $0.80 per million input/output tokens, against $2 / $12 for Gemini 3.1 Pro Preview.
  • Gemini 3.1 Pro Preview accepts more context: 1.05M tokens versus 262K.
  • Trinity Large Thinking has downloadable open weights; the other is API-only.

Side by side

Gemini 3.1 Pro Preview and Trinity Large Thinking specifications
Gemini 3.1 Pro PreviewTrinity Large Thinking
ProviderGoogleArcee AI
Noometry Index56.738.6
Released2026-02-192026-04-01
WeightsProprietaryOpen
Context window1.05M262K
Max output66K80K
Input $ / M tokens$2$0.25
Output $ / M tokens$12$0.80
Results tracked7124

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Category by category

Coding Gemini 3.1 Pro Preview leads

Gemini 3.1 Pro Preview: 42.5 (#99), Trinity Large Thinking: 34.1 (#244)

Coding benchmarks
BenchmarkGemini 3.1 Pro PreviewTrinity Large Thinking
LMArena WebDev14471238
SciCode58.9%36.1%
LMArena Coding14841381
SWE-bench Verified75.6%—
DeepSWE11.7%—
GSO22.6%—
WeirdML72.1%—
MirrorCode8.9%—
ALE-Bench1,161—
AlgoTune2.02—

Agentic & Tool Use Not comparable

Gemini 3.1 Pro Preview: 37.7 (#34), Trinity Large Thinking: —

Agentic & Tool Use benchmarks
BenchmarkGemini 3.1 Pro PreviewTrinity Large Thinking
Terminal-Bench80.2%—
APEX-Agents35.3%—
τ²-bench Banking26%—
DeepResearch Bench47.8%—
PostTrainBench22%—
BALROG57%—
ExploitBench26.1%—
GBAEval0.8%—
GDP.pdf17%—
LMArena Search1211—
METR Time Horizons77%—
Vending-Bench 23,774—

Reasoning Gemini 3.1 Pro Preview leads

Gemini 3.1 Pro Preview: 71.7 (#12), Trinity Large Thinking: 16.9 (#298)

Reasoning benchmarks
BenchmarkGemini 3.1 Pro PreviewTrinity Large Thinking
NYT Connections (extended)97.4%16.5%
CritPt17.7%0.9%
Thematic Generalization79.4%41.6%
LMArena Hard Prompts14851350
ARC-AGI-277.1%—
SimpleBench79.6%—
ARC-AGI-198%—
Chess Puzzles55%—
EnigmaEval36.8%—
EBR-Bench14.3%—
Mystery Game Puzzles34%—
DTBench97.1%—
LMCA53.8%—
Surface Evolver Bench—15.6%
Epoch Capabilities Index154.77—
ForecastBench59—

Math Gemini 3.1 Pro Preview leads

Gemini 3.1 Pro Preview: 62.1 (#34), Trinity Large Thinking: 37.6 (#149)

Math benchmarks
BenchmarkGemini 3.1 Pro PreviewTrinity Large Thinking
LMArena Math14851366
FrontierMath (Tiers 1-3)59.6%—
FrontierMath Tier 426.8%—
MathArena Final-Answer Competitions86.5%—
OTIS Mock AIME 2024-202595.6%—
ProofBench26%—
FrontierMath (Feb 2025 set)36.9%—
FrontierMath Tier 4 (v1)16.7%—

Knowledge Gemini 3.1 Pro Preview leads

Gemini 3.1 Pro Preview: 71.8 (#3), Trinity Large Thinking: 40.9 (#113)

Knowledge benchmarks
BenchmarkGemini 3.1 Pro PreviewTrinity Large Thinking
Vectara Hallucination Rate10.4%6.9%
LMArena Expert14851360
GPQA Diamond94.4%—
Humanity's Last Exam46.4%—
SimpleQA Verified73.5%—

Multimodal Not comparable

Gemini 3.1 Pro Preview: 37.9 (#69), Trinity Large Thinking: —

Multimodal benchmarks
BenchmarkGemini 3.1 Pro PreviewTrinity Large Thinking
LMArena Vision1296—
Blueprint-Bench 226.5%—
Furniture Assembly26.7%—
LMArena Document1444—

Multilingual Gemini 3.1 Pro Preview leads

Gemini 3.1 Pro Preview: 57.0 (#12), Trinity Large Thinking: 46.2 (#160)

Multilingual benchmarks
BenchmarkGemini 3.1 Pro PreviewTrinity Large Thinking
LMArena Non-English14771325
LMArena Chinese15291373
LMArena French14871374
LMArena German14911356
LMArena Japanese14931311
LMArena Korean14551306
LMArena Russian14981337
LMArena Spanish14791357

Instruction Following Gemini 3.1 Pro Preview leads

Gemini 3.1 Pro Preview: 77.0 (#32), Trinity Large Thinking: 70.5 (#162)

Instruction Following benchmarks
BenchmarkGemini 3.1 Pro PreviewTrinity Large Thinking
LMArena Instruction Following14661334

Long Context Gemini 3.1 Pro Preview leads

Gemini 3.1 Pro Preview: 47.4 (#18), Trinity Large Thinking: 41.3 (#144)

Long Context benchmarks
BenchmarkGemini 3.1 Pro PreviewTrinity Large Thinking
LMArena Longer Query14831355
CL-bench20.8%—
CL-bench Life16.9%—

Writing & Preference Gemini 3.1 Pro Preview leads

Gemini 3.1 Pro Preview: 66.1 (#37), Trinity Large Thinking: 53.8 (#158)

Writing & Preference benchmarks
BenchmarkGemini 3.1 Pro PreviewTrinity Large Thinking
LMArena Text14811340
LMArena Creative Writing14821320
LMArena Multi-Turn14881342
EQ-Bench Creative Writing1491—
EQ-Bench 41142—

Frequently asked questions

Is Gemini 3.1 Pro Preview better than Trinity Large Thinking?

Gemini 3.1 Pro Preview is the stronger model overall, scoring 56.7 to 38.6 on the Noometry Index. Trinity Large Thinking costs 12× less per token, which makes it the better buy when Gemini 3.1 Pro Preview's lead doesn't matter for your workload.

Which is cheaper, Gemini 3.1 Pro Preview 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; Gemini 3.1 Pro Preview lists at $2 and $12.

Is Gemini 3.1 Pro Preview or Trinity Large Thinking better for coding?

Gemini 3.1 Pro Preview scores higher on coding benchmarks: 42.5 versus 34.1 in the Noometry coding category.

Which has the bigger context window?

Gemini 3.1 Pro Preview does, with 1.05M tokens against 262K.

How many benchmarks do Gemini 3.1 Pro Preview and Trinity Large Thinking share?

23 benchmarks have published results for both models. Gemini 3.1 Pro Preview has 71 scored results on Noometry and Trinity Large Thinking has 24.

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