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Trinity Large Thinking vs GPT-5.4 Mini

GPT-5.4 Mini leads Trinity Large Thinking on the Artificial Analysis Intelligence Index, 24.1 to 10.8, and Trinity Large Thinking costs 5.6x less per output token ($0.80 vs $4.50 per million). Updated October 22, 2026; 43 benchmarks have a result for both.

Trinity Large ThinkingArcee AI
Coding
No data
Overall
No data
Output $/M
$0.80
2
GPT-5.4 MiniOpenAI
Coding
35.8
Overall
44.0
Output $/M
$4.50
41
vs boards won of 43 shared

Trinity Large Thinking or GPT-5.4 Mini: which to pick

Only GPT-5.4 Mini has a coding score, 35.8 on the Vibe Coding Index; Trinity Large Thinking has none, so the two cannot be ranked on coding.

Pick Trinity Large Thinking for output tokens 5.6x cheaper ($0.80 vs $4.50 per million) and work measured by τ²-Bench Telecom or CaseLaw (Vals AI), where it leads.

Shared results
43
Trinity Large Thinking only
9
GPT-5.4 Mini only
46
Like-for-like categories
7 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

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 not benchmarked, GPT-5.4 Mini 35.8 from 5 benchmarks.
Widest category
Coding, 22.0 points apart on average over 8 shared benchmarks.
Widest single gap
Long context reasoning (AA-LCR): Trinity Large Thinking 38.0% against GPT-5.4 Mini 77.0%, 39.0 points apart on a 0 to 100 scale.
Output price
Trinity Large Thinking $0.80 against GPT-5.4 Mini $4.50 per million output tokens, 5.6x apart.
Context window
Trinity Large Thinking takes 262K tokens, GPT-5.4 Mini 400K.

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 ThinkingBarsGPT-5.4 MiniTies
Coding08
Intelligence01
Agentic work11
Reasoning05
Math02
Knowledge15
General019
All shared boards241
CodingLike-for-likeSix of these boards feed the Vibe Coding Index08
Coding benchmarks for Trinity Large Thinking and GPT-5.4 Mini
BenchmarkTrinity Large ThinkingGPT-5.4 MiniLeader
LMArena WebDev12381397GPT-5.4 Mini
AA Coding Index25.856.1GPT-5.4 Mini
LiveCodeBench (Vals AI)Not measured81.5%Only GPT-5.4 Mini measured
SWE-bench Verified (Vals AI)Not measured73.0%Only GPT-5.4 Mini measured
Terminal-Bench 4 (Vals AI)Not measured2.5%Only GPT-5.4 Mini measured
Vibe Code Bench (Vals AI)Not measured48.0%Only GPT-5.4 Mini measured
Code migration (Vals AI)Not measured12.9%Only GPT-5.4 Mini measured
ProgramBench (Vals AI)Not measured0.0%Only GPT-5.4 Mini measured
Terminal-Bench 2.1 (Vals AI)Not measured54.7%Only GPT-5.4 Mini measured
SciCode40.6%52.1%GPT-5.4 Mini
Terminal-Bench Hard (Artificial Analysis run)22.7%52.3%GPT-5.4 Mini
FrontierCodeNot measured27.0%Only GPT-5.4 Mini measured
WeirdMLNot measured60.3%Only GPT-5.4 Mini measured
ALE-BenchNot measured1188.6Only GPT-5.4 Mini measured
LMArena Text: coding13571438GPT-5.4 Mini
LMArena Text: software and IT13621436GPT-5.4 Mini
LMArena WebDev: React12311386GPT-5.4 Mini
LMArena WebDev: HTML12401419GPT-5.4 Mini
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 GPT-5.4 Mini
BenchmarkTrinity Large ThinkingGPT-5.4 MiniLeader
AA Intelligence Index10.824.1GPT-5.4 Mini
Epoch Capabilities IndexNot measured148.7Only GPT-5.4 Mini measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index11
Agentic work benchmarks for Trinity Large Thinking and GPT-5.4 Mini
BenchmarkTrinity Large ThinkingGPT-5.4 MiniLeader
AA Agentic Index1.017.9GPT-5.4 Mini
Finance Agent (Vals AI)Not measured45.4%Only GPT-5.4 Mini measured
Tax Agent Bench (Vals AI)Not measured8.8%Only GPT-5.4 Mini measured
Legal Research Bench (Vals AI)Not measured12.5%Only GPT-5.4 Mini measured
Excel Modeling Benchmark (Vals AI)Not measured45.4%Only GPT-5.4 Mini measured
τ²-Bench Telecom90.1%83.3%Trinity Large Thinking
DeepResearch BenchNot measured36.3%Only GPT-5.4 Mini measured
Neither model has a result on the other 34 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for Trinity Large Thinking and GPT-5.4 Mini
BenchmarkTrinity Large ThinkingGPT-5.4 MiniLeader
GPQA DiamondNot measured83.1%Only GPT-5.4 Mini measured
MMMU Pro (Vals AI)Not measured79.3%Only GPT-5.4 Mini measured
GPQA Diamond (Artificial Analysis run)75.2%87.5%GPT-5.4 Mini
Humanity's Last Exam (Artificial Analysis run)15.8%28.1%GPT-5.4 Mini
GPQA Diamond (Epoch AI run)Not measured86.9%Only GPT-5.4 Mini measured
ARC-AGINot measured63.7%Only GPT-5.4 Mini measured
ARC-AGI-2Not measured18.9%Only GPT-5.4 Mini measured
Chess puzzlesNot measured23.0%Only GPT-5.4 Mini measured
Mystery game puzzlesNot measured11.0%Only GPT-5.4 Mini measured
LMArena Text: hard prompts13421424GPT-5.4 Mini
LMArena Text: expert13591435GPT-5.4 Mini
LMArena Text: hard prompts in English13561420GPT-5.4 Mini
LMArena Vision: diagramsNot measured1266Only GPT-5.4 Mini measured
LMArena Vision: homeworkNot measured1285Only GPT-5.4 Mini measured
Kagi LLM BenchmarkNot measured37.9%Only GPT-5.4 Mini measured
Neither model has a result on the other 7 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Trinity Large Thinking and GPT-5.4 Mini
BenchmarkTrinity Large ThinkingGPT-5.4 MiniLeader
AIMENot measured95.6%Only GPT-5.4 Mini measured
OTIS Mock AIMENot measured88.9%Only GPT-5.4 Mini measured
FrontierMath, tiers 1 to 3Not measured51.2%Only GPT-5.4 Mini measured
FrontierMath, tier 4Not measured9.8%Only GPT-5.4 Mini measured
ProofBenchNot measured21.0%Only GPT-5.4 Mini measured
LMArena Text: math13651418GPT-5.4 Mini
LMArena Text: mathematical work13501429GPT-5.4 Mini
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index15
Knowledge benchmarks for Trinity Large Thinking and GPT-5.4 Mini
BenchmarkTrinity Large ThinkingGPT-5.4 MiniLeader
MMLU ProNot measured84.5%Only GPT-5.4 Mini measured
CaseLaw (Vals AI)57.9%51.7%Trinity Large Thinking
CorpFin (Vals AI)54.7%60.9%GPT-5.4 Mini
TaxEval (Vals AI)Not measured71.2%Only GPT-5.4 Mini measured
MortgageTax (Vals AI)Not measured63.5%Only GPT-5.4 Mini measured
SimpleQA VerifiedNot measured29.4%Only GPT-5.4 Mini measured
LMArena Text: science13551417GPT-5.4 Mini
LMArena Text: medicine and healthcare13491395GPT-5.4 Mini
LMArena Text: legal and government13451414GPT-5.4 Mini
LMArena Text: business and finance13291418GPT-5.4 Mini
Neither model has a result on the other 8 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Trinity Large Thinking and GPT-5.4 Mini
BenchmarkTrinity Large ThinkingGPT-5.4 MiniLeader
Design Arena: websites1137Not measuredOnly Trinity Large Thinking measured
Design Arena: UI components1042Not measuredOnly Trinity Large Thinking measured
Design Arena: game dev1078Not measuredOnly Trinity Large Thinking measured
Design Arena: data viz1098Not measuredOnly Trinity Large Thinking measured
Design Arena: 3D1081Not measuredOnly Trinity Large Thinking measured
Design Arena: all code categories1116Not measuredOnly Trinity Large Thinking measured
Design Arena: SVG1016Not measuredOnly Trinity Large Thinking measured
Design Arena: ASCII art1041Not measuredOnly Trinity Large Thinking measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index019
General benchmarks for Trinity Large Thinking and GPT-5.4 Mini
BenchmarkTrinity Large ThinkingGPT-5.4 MiniLeader
SAGE (Vals AI)Not measured50.8%Only GPT-5.4 Mini measured
Vals Multimodal IndexNot measured54.2%Only GPT-5.4 Mini measured
IFBench56.3%73.3%GPT-5.4 Mini
Long context reasoning (AA-LCR)38.0%77.0%GPT-5.4 Mini
DTBenchNot measured80.0%Only GPT-5.4 Mini measured
LMCANot measured40.8%Only GPT-5.4 Mini measured
Surface Evolver Bench15.6%Not measuredOnly Trinity Large Thinking measured
LMArena Text13401412GPT-5.4 Mini
LMArena Text: instruction following13261405GPT-5.4 Mini
LMArena Text: creative writing13081370GPT-5.4 Mini
LMArena VisionNot measured1245Only GPT-5.4 Mini measured
LMArena Text: English13561412GPT-5.4 Mini
LMArena Text: non-English13251405GPT-5.4 Mini
LMArena Text: Chinese13711446GPT-5.4 Mini
LMArena Text: German13561408GPT-5.4 Mini
LMArena Text: Japanese13121375GPT-5.4 Mini
LMArena Text: Korean13061370GPT-5.4 Mini
LMArena Text: French13661441GPT-5.4 Mini
LMArena Text: Spanish13271405GPT-5.4 Mini
LMArena Text: Russian13381417GPT-5.4 Mini
LMArena Text: Polish13121415GPT-5.4 Mini
LMArena Text: multi-turn13201429GPT-5.4 Mini
LMArena Text: longer queries13181408GPT-5.4 Mini
LMArena Text: writing and language13171393GPT-5.4 Mini
LMArena Text: entertainment and media12961373GPT-5.4 Mini
LMArena Vision: EnglishNot measured1244Only GPT-5.4 Mini measured
LMArena Vision: ChineseNot measured1286Only GPT-5.4 Mini measured
LMArena Vision: reading textNot measured1253Only GPT-5.4 Mini measured
LMArena Vision: humorNot measured1235Only GPT-5.4 Mini measured
LMArena Vision: recognizing thingsNot measured1218Only GPT-5.4 Mini measured
LMArena Vision: creative writingNot measured1222Only GPT-5.4 Mini measured
Neither model has a result on the other 15 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 GPT-5.4 Mini
BenchmarkTrinity Large ThinkingGPT-5.4 MiniLeader
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
GPT-5.4 Mini$0.0030Fits in one request

Trinity Large Thinking costs less

Repository review

50K input + 3K output tokens

Trinity Large Thinking$0.015Fits in one request
GPT-5.4 Mini$0.051Fits in one request

Trinity Large Thinking costs less

Agent loop

200K input + 10K output tokens

Trinity Large Thinking$0.058Fits in one request
GPT-5.4 Mini$0.195Fits in one request

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 GPT-5.4 Mini
SpecificationArcee AI Trinity Large ThinkingOpenAI GPT-5.4 Mini
MakerArcee AIOpenAI
WeightsOpen weightsNo public weights listed
ReleasedApril 1, 2026March 17, 2026
Context window262K400K
Input $/Mtok$0.25$0.75
Output $/Mtok$0.80$4.50
Coding indexNot benchmarked35.8
Independent measurements behind it15
Cost per solved taskNot computable$0.70
SourceOpenRouter listingOpenRouter listing

Questions

Is Trinity Large Thinking better than GPT-5.4 Mini for coding?

Only GPT-5.4 Mini has a coding score, 35.8 on the Vibe Coding Index; Trinity Large Thinking has none, so the two cannot be ranked on coding. Pick Trinity Large Thinking for output tokens 5.6x cheaper ($0.80 vs $4.50 per million) and work measured by τ²-Bench Telecom or CaseLaw (Vals AI), where it leads.

Which is cheaper, Trinity Large Thinking or GPT-5.4 Mini?

Trinity Large Thinking costs $0.25 per million input tokens and $0.80 per million output tokens; GPT-5.4 Mini costs $0.75 and $4.50. Cost per solved task is known for GPT-5.4 Mini only.

Which has the bigger context window, Trinity Large Thinking or GPT-5.4 Mini?

GPT-5.4 Mini, with 400K tokens against 262K.

How many benchmarks is the Trinity Large Thinking vs GPT-5.4 Mini comparison based on?

43 benchmarks have a result for both models as of October 22, 2026. Trinity Large Thinking's coding index rests on 1 independent benchmark and GPT-5.4 Mini's on 5. Where only one model has a result, the page says so instead of naming a winner.

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