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Trinity Large Thinking vs GLM 5.2

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 GLM 5.2
Trinity Large ThinkingArcee AI
Coding
5.4
Overall
10.8
Output $/M
$0.80
0
GLM 5.2Z.ai
Coding
57.7
Overall
33.7
Output $/M
$7.00
51
vs boards won of 51 shared

Decision reading

Pick GLM 5.2 for coding: it scores 57.7 on the Vibe Coding Index against 5.4 for Trinity Large Thinking.

Pick Trinity Large Thinking when output tokens cost 8.8x less.

Model ATrinity Large ThinkingArcee AI5.4/1001 independent benchmarkNo cost per solved taskModel BGLM 5.2Z.ai57.7/1001 independent benchmark$0.86 per solved task
Shared results
51
Trinity Large Thinking only
1
GLM 5.2 only
46
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, GLM 5.2 57.7 from 1 benchmark.
Widest category
Coding, 36.5 points apart on average over 8 shared benchmarks.
Widest single gap
LMArena WebDev: React: Trinity Large Thinking 1231 against GLM 5.2 1617, 61.6 points apart on a 0 to 100 scale.
Output price
Trinity Large Thinking $0.80 against GLM 5.2 $7.00 per million output tokens, 8.8x apart.
Context window
Trinity Large Thinking takes 262K tokens, GLM 5.2 1.05M.

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 ThinkingBarsGLM 5.2Ties
Coding08
Intelligence01
Agentic work02
Reasoning05
Math02
Knowledge05
Web design08
General020
All shared boards051
CodingLike-for-likeFour of these boards feed the Vibe Coding Index08
Coding benchmarks for Trinity Large Thinking and GLM 5.2
BenchmarkTrinity Large ThinkingGLM 5.2Leader
LMArena WebDev12381604GLM 5.2
AA Coding Index25.868.8GLM 5.2
LiveCodeBench (Vals AI)Not measured69.5%Only GLM 5.2 measured
SWE-bench Verified (Vals AI)Not measured82.8%Only GLM 5.2 measured
Vibe Code Bench (Vals AI)Not measured64.0%Only GLM 5.2 measured
Code migration (Vals AI)Not measured37.9%Only GLM 5.2 measured
ProgramBench (Vals AI)Not measured0.5%Only GLM 5.2 measured
Terminal-Bench 2.1 (Vals AI)Not measured67.8%Only GLM 5.2 measured
SkillsBench (Vals AI)Not measured45.1%Only GLM 5.2 measured
SciCode40.6%51.2%GLM 5.2
Terminal-Bench Hard (Artificial Analysis run)22.7%50.8%GLM 5.2
FrontierCodeNot measured24.5%Only GLM 5.2 measured
WeirdMLNot measured70.1%Only GLM 5.2 measured
ALE-BenchNot measured1047.0Only GLM 5.2 measured
LMArena Text: coding13571487GLM 5.2
LMArena Text: software and IT13621486GLM 5.2
LMArena WebDev: React12311617GLM 5.2
LMArena WebDev: HTML12401565GLM 5.2
Neither model has a result on the other 20 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Trinity Large Thinking and GLM 5.2
BenchmarkTrinity Large ThinkingGLM 5.2Leader
AA Intelligence Index10.833.7GLM 5.2
Epoch Capabilities IndexNot measured151.9Only GLM 5.2 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index02
Agentic work benchmarks for Trinity Large Thinking and GLM 5.2
BenchmarkTrinity Large ThinkingGLM 5.2Leader
AA Agentic Index1.038.4GLM 5.2
Design Arena: agents building web appsNot measured1222Only GLM 5.2 measured
Design Arena: agents building full-stack appsNot measured1241Only GLM 5.2 measured
Design Arena: agents building mobile appsNot measured1160Only GLM 5.2 measured
Design Arena: agents building Android appsNot measured1184Only GLM 5.2 measured
Design Arena: agents building Godot gamesNot measured1142Only GLM 5.2 measured
Design Arena: agents building gamesNot measured1206Only GLM 5.2 measured
Design Arena: HTML slidesNot measured1175Only GLM 5.2 measured
Design Arena: PowerPoint slidesNot measured1195Only GLM 5.2 measured
SREBench (Vals AI)Not measured0.0%Only GLM 5.2 measured
Finance Agent (Vals AI)Not measured49.7%Only GLM 5.2 measured
Legal Research Bench (Vals AI)Not measured31.3%Only GLM 5.2 measured
Excel Modeling Benchmark (Vals AI)Not measured61.5%Only GLM 5.2 measured
τ²-Bench Telecom90.1%99.1%GLM 5.2
APEX-AgentsNot measured45.2%Only GLM 5.2 measured
PostTrainBenchNot measured31.7%Only GLM 5.2 measured
Vending-Bench 2Not measured$8,314Only GLM 5.2 measured
Neither model has a result on the other 22 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for Trinity Large Thinking and GLM 5.2
BenchmarkTrinity Large ThinkingGLM 5.2Leader
GPQA DiamondNot measured85.6%Only GLM 5.2 measured
GPQA Diamond (Artificial Analysis run)75.2%89.5%GLM 5.2
Humanity's Last Exam (Artificial Analysis run)15.8%41.1%GLM 5.2
GPQA Diamond (Epoch AI run)Not measured91.9%Only GLM 5.2 measured
ARC-AGINot measured77.0%Only GLM 5.2 measured
ARC-AGI-2Not measured22.8%Only GLM 5.2 measured
SimpleBenchNot measured58.8%Only GLM 5.2 measured
Chess puzzlesNot measured22.0%Only GLM 5.2 measured
Mystery game puzzlesNot measured19.0%Only GLM 5.2 measured
EBR-benchNot measured9.5%Only GLM 5.2 measured
LMArena Text: hard prompts13421481GLM 5.2
LMArena Text: expert13591487GLM 5.2
LMArena Text: hard prompts in English13561481GLM 5.2
Neither model has a result on the other 8 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Trinity Large Thinking and GLM 5.2
BenchmarkTrinity Large ThinkingGLM 5.2Leader
OTIS Mock AIMENot measured86.4%Only GLM 5.2 measured
FrontierMath, tiers 1 to 3Not measured59.2%Only GLM 5.2 measured
FrontierMath, tier 4Not measured29.3%Only GLM 5.2 measured
ProofBenchNot measured35.0%Only GLM 5.2 measured
LMArena Text: math13651483GLM 5.2
LMArena Text: mathematical work13501489GLM 5.2
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05
Knowledge benchmarks for Trinity Large Thinking and GLM 5.2
BenchmarkTrinity Large ThinkingGLM 5.2Leader
MMLU ProNot measured86.7%Only GLM 5.2 measured
LegalBench (Vals AI)Not measured84.1%Only GLM 5.2 measured
CaseLaw (Vals AI)57.9%Not measuredOnly Trinity Large Thinking measured
CorpFin (Vals AI)54.7%66.1%GLM 5.2
TaxEval (Vals AI)Not measured73.3%Only GLM 5.2 measured
MedCode (Vals AI)Not measured40.8%Only GLM 5.2 measured
SimpleQA VerifiedNot measured34.2%Only GLM 5.2 measured
LMArena Text: science13551489GLM 5.2
LMArena Text: medicine and healthcare13491475GLM 5.2
LMArena Text: legal and government13451486GLM 5.2
LMArena Text: business and finance13291451GLM 5.2
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index08
Web design benchmarks for Trinity Large Thinking and GLM 5.2
BenchmarkTrinity Large ThinkingGLM 5.2Leader
Design Arena: websites11371285GLM 5.2
Design Arena: UI components10451296GLM 5.2
Design Arena: game dev10791268GLM 5.2
Design Arena: data viz10981285GLM 5.2
Design Arena: 3D10821288GLM 5.2
Design Arena: all code categories11171288GLM 5.2
Design Arena: SVG10161214GLM 5.2
Design Arena: ASCII art10411190GLM 5.2
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index020
General benchmarks for Trinity Large Thinking and GLM 5.2
BenchmarkTrinity Large ThinkingGLM 5.2Leader
MedScribe (Vals AI)Not measured83.5%Only GLM 5.2 measured
IFBench56.3%73.3%GLM 5.2
Long context reasoning (AA-LCR)38.0%78.3%GLM 5.2
DTBenchNot measured93.6%Only GLM 5.2 measured
LMCANot measured45.8%Only GLM 5.2 measured
Surface Evolver Bench15.6%55.6%GLM 5.2
LMArena Text13401470GLM 5.2
LMArena Text: instruction following13261466GLM 5.2
LMArena Text: creative writing13081463GLM 5.2
LMArena Text: English13561475GLM 5.2
LMArena Text: non-English13251459GLM 5.2
LMArena Text: Chinese13711522GLM 5.2
LMArena Text: German13561470GLM 5.2
LMArena Text: Japanese13121450GLM 5.2
LMArena Text: Korean13061440GLM 5.2
LMArena Text: French13661479GLM 5.2
LMArena Text: Spanish13271478GLM 5.2
LMArena Text: Russian13381468GLM 5.2
LMArena Text: Polish13121456GLM 5.2
LMArena Text: multi-turn13201469GLM 5.2
LMArena Text: longer queries13181480GLM 5.2
LMArena Text: writing and language13171463GLM 5.2
LMArena Text: entertainment and media12961450GLM 5.2
Neither model has a result on the other 23 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 GLM 5.2
BenchmarkTrinity Large ThinkingGLM 5.2Leader
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
GLM 5.2$0.0035Fits in one request

Trinity Large Thinking costs less

Repository review

50K input + 3K output tokens

Trinity Large Thinking$0.015Fits in one request
GLM 5.2$0.023Fits in one request

Trinity Large Thinking costs less

Agent loop

200K input + 10K output tokens

Trinity Large Thinking$0.058Fits in one request
GLM 5.2$0.077Fits 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 GLM 5.2
SpecificationArcee AI Trinity Large ThinkingZ.ai GLM 5.2
MakerArcee AIZ.ai
WeightsOpen weightsOpen weights
ReleasedApril 1, 2026June 16, 2026
Context window262K1.05M
Input $/Mtok$0.25$0.0341
Output $/Mtok$0.80$7.00
Coding index5.457.7
Independent measurements behind it11
Cost per solved taskNot computable$0.86
SourceOpenRouter listingOpenRouter listing

Questions

Is Trinity Large Thinking better than GLM 5.2 for coding?

Pick GLM 5.2 for coding: it scores 57.7 on the Vibe Coding Index against 5.4 for Trinity Large Thinking. Pick Trinity Large Thinking when output tokens cost 8.8x less.

Which is cheaper, Trinity Large Thinking or GLM 5.2?

Trinity Large Thinking costs $0.25 per million input tokens and $0.80 per million output tokens; GLM 5.2 costs $0.0341 and $7.00. Cost per solved task is known for GLM 5.2 only.

Which has the bigger context window, Trinity Large Thinking or GLM 5.2?

GLM 5.2, with 1.05M tokens against 262K.

How many benchmarks is the Trinity Large Thinking vs GLM 5.2 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 GLM 5.2's on 1. Where only one model has a result, the page says so instead of naming a winner.

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