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Trinity Large Thinking vs MiniMax M2.7

Updated October 21, 2026. 51 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace Trinity Large Thinking Replace MiniMax M2.7
Trinity Large ThinkingArcee AI
Coding
5.4
Overall
10.8
Output $/M
$0.80
2
MiniMax M2.7MiniMax
Coding
28.4
Overall
22.8
Output $/M
$1.20
49
vs boards won of 51 shared

Decision reading

Pick MiniMax M2.7 for coding: it scores 28.4 on the Vibe Coding Index against 5.4 for Trinity Large Thinking.

Pick Trinity Large Thinking when output tokens cost 1.5x less, or when the context window is larger, 262K against 205K tokens.

Model ATrinity Large ThinkingArcee AI5.4/1001 independent benchmarkNo cost per solved taskModel BMiniMax M2.7MiniMax28.4/1001 independent benchmark$0.64 per solved task
Shared results
51
Trinity Large Thinking only
1
MiniMax M2.7 only
23
Like-for-like categories
8 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
Trinity Large Thinking 5.4 from 1 benchmark, MiniMax M2.7 28.4 from 1 benchmark.
Widest category
Coding, 19.9 points apart on average over 8 shared benchmarks.
Widest single gap
Long context reasoning (AA-LCR): Trinity Large Thinking 38.0% against MiniMax M2.7 78.3%, 40.3 points apart on a 0 to 100 scale.
Output price
Trinity Large Thinking $0.80 against MiniMax M2.7 $1.20 per million output tokens, 1.5x apart.
Context window
Trinity Large Thinking takes 262K tokens, MiniMax M2.7 205K.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryTrinity Large ThinkingBarsMiniMax M2.7Ties
Coding08
Intelligence01
Agentic work11
Reasoning05
Math02
Knowledge06
Web design08
General118
All shared boards249
CodingLike-for-likeFour of these boards feed the Vibe Coding Index08
Coding benchmarks for Trinity Large Thinking and MiniMax M2.7
BenchmarkTrinity Large ThinkingMiniMax M2.7Leader
LMArena WebDev12381399MiniMax M2.7
AA Coding Index25.852.6MiniMax M2.7
LiveCodeBench (Vals AI)Not measured79.9%Only MiniMax M2.7 measured
SWE-bench Verified (Vals AI)Not measured73.8%Only MiniMax M2.7 measured
Vibe Code Bench (Vals AI)Not measured11.9%Only MiniMax M2.7 measured
Code migration (Vals AI)Not measured8.7%Only MiniMax M2.7 measured
ProgramBench (Vals AI)Not measured0.0%Only MiniMax M2.7 measured
Terminal-Bench 2.1 (Vals AI)Not measured48.7%Only MiniMax M2.7 measured
SciCode40.6%50.1%MiniMax M2.7
Terminal-Bench Hard (Artificial Analysis run)22.7%39.4%MiniMax M2.7
Terminal-BenchNot measured45.1%Only MiniMax M2.7 measured
WeirdMLNot measured37.0%Only MiniMax M2.7 measured
ALE-BenchNot measured599.3Only MiniMax M2.7 measured
LMArena Text: coding13571454MiniMax M2.7
LMArena Text: software and IT13621446MiniMax M2.7
LMArena WebDev: React12311388MiniMax M2.7
LMArena WebDev: HTML12401401MiniMax M2.7
Neither model has a result on the other 21 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Trinity Large Thinking and MiniMax M2.7
BenchmarkTrinity Large ThinkingMiniMax M2.7Leader
AA Intelligence Index10.822.8MiniMax M2.7
Epoch Capabilities IndexNot measured145.8Only MiniMax M2.7 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index11
Agentic work benchmarks for Trinity Large Thinking and MiniMax M2.7
BenchmarkTrinity Large ThinkingMiniMax M2.7Leader
AA Agentic Index1.015.3MiniMax M2.7
Finance Agent (Vals AI)Not measured27.9%Only MiniMax M2.7 measured
Tax Agent Bench (Vals AI)Not measured6.9%Only MiniMax M2.7 measured
Legal Research Bench (Vals AI)Not measured10.6%Only MiniMax M2.7 measured
Excel Modeling Benchmark (Vals AI)Not measured28.4%Only MiniMax M2.7 measured
τ²-Bench Telecom90.1%84.8%Trinity Large Thinking
Neither model has a result on the other 33 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for Trinity Large Thinking and MiniMax M2.7
BenchmarkTrinity Large ThinkingMiniMax M2.7Leader
GPQA DiamondNot measured86.6%Only MiniMax M2.7 measured
GPQA Diamond (Artificial Analysis run)75.2%87.4%MiniMax M2.7
Humanity's Last Exam (Artificial Analysis run)15.8%29.6%MiniMax M2.7
LMArena Text: hard prompts13421422MiniMax M2.7
LMArena Text: expert13591443MiniMax M2.7
LMArena Text: hard prompts in English13561441MiniMax M2.7
Neither model has a result on the other 15 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Trinity Large Thinking and MiniMax M2.7
BenchmarkTrinity Large ThinkingMiniMax M2.7Leader
AIMENot measured91.0%Only MiniMax M2.7 measured
ProofBenchNot measured3.0%Only MiniMax M2.7 measured
LMArena Text: math13651421MiniMax M2.7
LMArena Text: mathematical work13501437MiniMax M2.7
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index06
Knowledge benchmarks for Trinity Large Thinking and MiniMax M2.7
BenchmarkTrinity Large ThinkingMiniMax M2.7Leader
MMLU ProNot measured80.4%Only MiniMax M2.7 measured
LegalBench (Vals AI)Not measured84.0%Only MiniMax M2.7 measured
CaseLaw (Vals AI)57.9%60.9%MiniMax M2.7
CorpFin (Vals AI)54.7%61.2%MiniMax M2.7
TaxEval (Vals AI)Not measured66.6%Only MiniMax M2.7 measured
MedCode (Vals AI)Not measured34.4%Only MiniMax M2.7 measured
LMArena Text: science13551416MiniMax M2.7
LMArena Text: medicine and healthcare13491409MiniMax M2.7
LMArena Text: legal and government13451403MiniMax M2.7
LMArena Text: business and finance13291407MiniMax M2.7
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index08
Web design benchmarks for Trinity Large Thinking and MiniMax M2.7
BenchmarkTrinity Large ThinkingMiniMax M2.7Leader
Design Arena: websites11371243MiniMax M2.7
Design Arena: UI components10451210MiniMax M2.7
Design Arena: game dev10791210MiniMax M2.7
Design Arena: data viz10981233MiniMax M2.7
Design Arena: 3D10821195MiniMax M2.7
Design Arena: all code categories11171233MiniMax M2.7
Design Arena: SVG10161136MiniMax M2.7
Design Arena: ASCII art10411136MiniMax M2.7
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index118
General benchmarks for Trinity Large Thinking and MiniMax M2.7
BenchmarkTrinity Large ThinkingMiniMax M2.7Leader
MedScribe (Vals AI)Not measured79.9%Only MiniMax M2.7 measured
IFBench56.3%75.7%MiniMax M2.7
Long context reasoning (AA-LCR)38.0%78.3%MiniMax M2.7
Surface Evolver Bench15.6%Not measuredOnly Trinity Large Thinking measured
ExploitBenchNot measured13.3%Only MiniMax M2.7 measured
LMArena Text13401405MiniMax M2.7
LMArena Text: instruction following13261405MiniMax M2.7
LMArena Text: creative writing13081354MiniMax M2.7
LMArena Text: English13561426MiniMax M2.7
LMArena Text: non-English13251382MiniMax M2.7
LMArena Text: Chinese13711442MiniMax M2.7
LMArena Text: German13561398MiniMax M2.7
LMArena Text: Japanese13121260Trinity Large Thinking
LMArena Text: Korean13061314MiniMax M2.7
LMArena Text: French13661424MiniMax M2.7
LMArena Text: Spanish13271402MiniMax M2.7
LMArena Text: Russian13381383MiniMax M2.7
LMArena Text: Polish13121387MiniMax M2.7
LMArena Text: multi-turn13201412MiniMax M2.7
LMArena Text: longer queries13181418MiniMax M2.7
LMArena Text: writing and language13171376MiniMax M2.7
LMArena Text: entertainment and media12961360MiniMax M2.7
Neither model has a result on the other 24 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Trinity Large Thinking and MiniMax M2.7
BenchmarkTrinity Large ThinkingMiniMax M2.7Leader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

Trinity Large Thinking$0.0006Fits in one request
MiniMax M2.7$0.0009Fits in one request

Trinity Large Thinking costs less

Repository review

50K input + 3K output tokens

Trinity Large Thinking$0.015Fits in one request
MiniMax M2.7$0.019Fits in one request

Trinity Large Thinking costs less

Agent loop

200K input + 10K output tokens

Trinity Large Thinking$0.058Fits in one request
MiniMax M2.7$0.072Exceeds the context window

Trinity Large Thinking costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of Trinity Large Thinking and MiniMax M2.7
SpecificationArcee AI Trinity Large ThinkingMiniMax M2.7
MakerArcee AIMiniMax
WeightsOpen weightsOpen weights
ReleasedApril 1, 2026March 18, 2026
Context window262K205K
Input $/Mtok$0.25$0.30
Output $/Mtok$0.80$1.20
Coding index5.428.4
Independent measurements behind it11
Cost per solved taskNot computable$0.64
SourceOpenRouter listingOpenRouter listing

Questions

Is Trinity Large Thinking better than MiniMax M2.7 for coding?

Pick MiniMax M2.7 for coding: it scores 28.4 on the Vibe Coding Index against 5.4 for Trinity Large Thinking. Pick Trinity Large Thinking when output tokens cost 1.5x less, or when the context window is larger, 262K against 205K tokens.

Which is cheaper, Trinity Large Thinking or MiniMax M2.7?

Trinity Large Thinking costs $0.25 per million input tokens and $0.80 per million output tokens; MiniMax M2.7 costs $0.30 and $1.20. Cost per solved task is known for MiniMax M2.7 only.

Which has the bigger context window, Trinity Large Thinking or MiniMax M2.7?

Trinity Large Thinking, with 262K tokens against 205K.

How many benchmarks is the Trinity Large Thinking vs MiniMax M2.7 comparison based on?

51 benchmarks have a result for both models as of October 21, 2026. Trinity Large Thinking's coding index rests on 1 independent benchmark and MiniMax M2.7's on 1. Where only one model has a result, the page says so instead of naming a winner.

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