Compare Models

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Trinity Large ThinkingMiniMax-M3.1-Flash


Vals IndexGDP-weighted benchmark	N/A	53.78%±1.07
Legal Research BenchAgentic US legal research	N/A	34.13%±3.30
Finance Agent v2.1Core financial analyst tasks	N/A	58.83%±2.07
Tax Agent BenchAgentic US corporate tax research	N/A	32.14%±3.34
Terminal-Bench 4.0Frontier-difficulty terminal tasks	N/A	25.25%±1.01
Vibe Code Bench v1.1Building web apps from scratch	N/A	73.94%±4.25

Benchmarks

Vals Index *

Trinity Large Thinking

N/A

MiniMax-M3.1-Flash

0.00%± 1.07

(26/26)

Legal Research Bench *

Trinity Large Thinking

N/A

MiniMax-M3.1-Flash

0.00%± 3.30

(84/84)

Finance Agent v2.1 *

Trinity Large Thinking

N/A

MiniMax-M3.1-Flash

0.00%± 2.07

(30/30)

Tax Agent Bench *

Trinity Large Thinking

N/A

MiniMax-M3.1-Flash

0.00%± 3.34

(75/75)

Terminal-Bench 4.0

Trinity Large Thinking

N/A

MiniMax-M3.1-Flash

0.00%± 1.01

(54/54)

Vibe Code Bench v1.1 *

Trinity Large Thinking

N/A

MiniMax-M3.1-Flash

0.00%± 4.25

(118/118)

Overall performance

Performance on the Vals Index, a GDP-weighted aggregation of tasks across finance, coding, and law

•2026-10-22

Trinity Large Thinking MiniMax-M3.1-Flash

Comparison by Industry

Model performance on different sections of the economy.

Legal

N/A

vs.

20.82%

Finance

N/A

vs.

52.94%

Coding

N/A

vs.

49.60%

Cost Analysis

Per task and per token model pricing.

Vals Index · USD

N/A

$0.66

Cost / TestVals Index

N/A

vs.

$0.66

Input Cost/ 1M Tokens

$0.25

vs.

$0.15

Input Cache Read/ 1M Tokens

$0.06

vs.

$0.015

Output Cost/ 1M Tokens

$0.90

vs.

$0.60

Model Metadata

Basic information about each model.


Model provider	Arcee AI	MiniMax
Latency	N/A	2597.84s
Cost (In/Out)	$0.25 / $0.9	$0.15 / $0.6
Context Window	262k	1M
Max Output Token	80k	524k
Input Modality