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Trinity Large Thinking vs GLM 4.7

Updated October 21, 2026. 49 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 4.7
Trinity Large ThinkingArcee AI
Coding
5.4
Overall
10.8
Output $/M
$0.80
2
GLM 4.7Z.ai
Coding
33.6
Overall
22.2
Output $/M
$1.98
47
vs boards won of 49 shared

Decision reading

Pick GLM 4.7 for coding: it scores 33.6 on the Vibe Coding Index against 5.4 for Trinity Large Thinking.

Pick Trinity Large Thinking when output tokens cost 2.5x 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 BGLM 4.7Z.ai33.6/1001 independent benchmark$0.29 per solved task
Shared results
49
Trinity Large Thinking only
3
GLM 4.7 only
31
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 4.7 33.6 from 1 benchmark.
Widest category
Coding, 22.0 points apart on average over 7 shared benchmarks.
Widest single gap
LMArena WebDev: HTML: Trinity Large Thinking 1240 against GLM 4.7 1447, 34.4 points apart on a 0 to 100 scale.
Output price
Trinity Large Thinking $0.80 against GLM 4.7 $1.98 per million output tokens, 2.5x apart.
Context window
Trinity Large Thinking takes 262K tokens, GLM 4.7 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 ThinkingBarsGLM 4.7Ties
Coding07
Intelligence01
Agentic work01
Reasoning05
Math02
Knowledge24
Web design08
General019
All shared boards247
CodingLike-for-likeFour of these boards feed the Vibe Coding Index07
Coding benchmarks for Trinity Large Thinking and GLM 4.7
BenchmarkTrinity Large ThinkingGLM 4.7Leader
LMArena WebDev12381435GLM 4.7
AA Coding Index25.845.3GLM 4.7
LiveCodeBench (Vals AI)Not measured82.2%Only GLM 4.7 measured
SWE-bench Verified (Vals AI)Not measured69.4%Only GLM 4.7 measured
LiveCodeBench (Artificial Analysis run)Not measured89.4%Only GLM 4.7 measured
SciCode40.6%Not measuredOnly Trinity Large Thinking measured
Terminal-Bench Hard (Artificial Analysis run)22.7%31.8%GLM 4.7
Terminal-BenchNot measured33.4%Only GLM 4.7 measured
ALE-BenchNot measured399.5Only GLM 4.7 measured
LMArena Text: coding13571454GLM 4.7
LMArena Text: software and IT13621453GLM 4.7
LMArena WebDev: React12311420GLM 4.7
LMArena WebDev: HTML12401447GLM 4.7
Neither model has a result on the other 25 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Trinity Large Thinking and GLM 4.7
BenchmarkTrinity Large ThinkingGLM 4.7Leader
AA Intelligence Index10.822.2GLM 4.7
Epoch Capabilities IndexNot measured143.6Only GLM 4.7 measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Trinity Large Thinking and GLM 4.7
BenchmarkTrinity Large ThinkingGLM 4.7Leader
AA Agentic Index1.0Not measuredOnly Trinity Large Thinking measured
Design Arena: agents building full-stack appsNot measured1050Only GLM 4.7 measured
Design Arena: agents building mobile appsNot measured1105Only GLM 4.7 measured
Design Arena: agents building Android appsNot measured1118Only GLM 4.7 measured
Design Arena: agents building Godot gamesNot measured1058Only GLM 4.7 measured
τ²-Bench Telecom90.1%95.9%GLM 4.7
Vending-Bench 2Not measured$2,377Only GLM 4.7 measured
Neither model has a result on the other 32 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index05
Reasoning benchmarks for Trinity Large Thinking and GLM 4.7
BenchmarkTrinity Large ThinkingGLM 4.7Leader
GPQA DiamondNot measured80.0%Only GLM 4.7 measured
GPQA Diamond (Artificial Analysis run)75.2%85.9%GLM 4.7
Humanity's Last Exam (Artificial Analysis run)15.8%27.4%GLM 4.7
GPQA Diamond (Epoch AI run)Not measured83.3%Only GLM 4.7 measured
SimpleBenchNot measured47.7%Only GLM 4.7 measured
Chess puzzlesNot measured21.0%Only GLM 4.7 measured
LMArena Text: hard prompts13421443GLM 4.7
LMArena Text: expert13591424GLM 4.7
LMArena Text: hard prompts in English13561452GLM 4.7
Neither model has a result on the other 12 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for Trinity Large Thinking and GLM 4.7
BenchmarkTrinity Large ThinkingGLM 4.7Leader
AIMENot measured93.3%Only GLM 4.7 measured
MGSM (Vals AI)Not measured88.2%Only GLM 4.7 measured
AA Math IndexNot measured95.0Only GLM 4.7 measured
AIME 2025 (Artificial Analysis run)Not measured95.0%Only GLM 4.7 measured
OTIS Mock AIMENot measured83.3%Only GLM 4.7 measured
ProofBenchNot measured6.0%Only GLM 4.7 measured
LMArena Text: math13651424GLM 4.7
LMArena Text: mathematical work13501411GLM 4.7
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index24
Knowledge benchmarks for Trinity Large Thinking and GLM 4.7
BenchmarkTrinity Large ThinkingGLM 4.7Leader
MMLU ProNot measured82.7%Only GLM 4.7 measured
LegalBench (Vals AI)Not measured83.4%Only GLM 4.7 measured
CaseLaw (Vals AI)57.9%54.9%Trinity Large Thinking
CorpFin (Vals AI)54.7%46.4%Trinity Large Thinking
TaxEval (Vals AI)Not measured68.8%Only GLM 4.7 measured
MedQA (Vals AI)Not measured93.7%Only GLM 4.7 measured
MedCode (Vals AI)Not measured32.8%Only GLM 4.7 measured
MMLU Pro (Artificial Analysis run)Not measured85.6%Only GLM 4.7 measured
SimpleQA VerifiedNot measured32.2%Only GLM 4.7 measured
LMArena Text: science13551457GLM 4.7
LMArena Text: medicine and healthcare13491469GLM 4.7
LMArena Text: legal and government13451444GLM 4.7
LMArena Text: business and finance13291429GLM 4.7
Neither model has a result on the other 4 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index08
Web design benchmarks for Trinity Large Thinking and GLM 4.7
BenchmarkTrinity Large ThinkingGLM 4.7Leader
Design Arena: websites11371226GLM 4.7
Design Arena: UI components10451199GLM 4.7
Design Arena: game dev10791189GLM 4.7
Design Arena: data viz10981195GLM 4.7
Design Arena: 3D10821191GLM 4.7
Design Arena: all code categories11171217GLM 4.7
Design Arena: SVG10161142GLM 4.7
Design Arena: ASCII art10411165GLM 4.7
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 GLM 4.7
BenchmarkTrinity Large ThinkingGLM 4.7Leader
MedScribe (Vals AI)Not measured68.6%Only GLM 4.7 measured
IFBench56.3%67.9%GLM 4.7
Long context reasoning (AA-LCR)38.0%71.0%GLM 4.7
CL-benchNot measured15.9%Only GLM 4.7 measured
Surface Evolver Bench15.6%Not measuredOnly Trinity Large Thinking measured
CL-bench LifeNot measured10.9%Only GLM 4.7 measured
LMArena Text13401435GLM 4.7
LMArena Text: instruction following13261412GLM 4.7
LMArena Text: creative writing13081401GLM 4.7
LMArena Text: English13561453GLM 4.7
LMArena Text: non-English13251417GLM 4.7
LMArena Text: Chinese13711495GLM 4.7
LMArena Text: German13561426GLM 4.7
LMArena Text: Japanese13121439GLM 4.7
LMArena Text: Korean13061399GLM 4.7
LMArena Text: French13661432GLM 4.7
LMArena Text: Spanish13271434GLM 4.7
LMArena Text: Russian13381423GLM 4.7
LMArena Text: Polish13121435GLM 4.7
LMArena Text: multi-turn13201446GLM 4.7
LMArena Text: longer queries13181432GLM 4.7
LMArena Text: writing and language13171411GLM 4.7
LMArena Text: entertainment and media12961400GLM 4.7
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 4.7
BenchmarkTrinity Large ThinkingGLM 4.7Leader
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
GLM 4.7$0.0015Fits in one request

Trinity Large Thinking costs less

Repository review

50K input + 3K output tokens

Trinity Large Thinking$0.015Fits in one request
GLM 4.7$0.033Fits in one request

Trinity Large Thinking costs less

Agent loop

200K input + 10K output tokens

Trinity Large Thinking$0.058Fits in one request
GLM 4.7$0.128Exceeds 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 GLM 4.7
SpecificationArcee AI Trinity Large ThinkingZ.ai GLM 4.7
MakerArcee AIZ.ai
WeightsOpen weightsOpen weights
ReleasedApril 1, 2026December 22, 2025
Context window262K205K
Input $/Mtok$0.25$0.54
Output $/Mtok$0.80$1.98
Coding index5.433.6
Independent measurements behind it11
Cost per solved taskNot computable$0.29
SourceOpenRouter listingOpenRouter listing

Questions

Is Trinity Large Thinking better than GLM 4.7 for coding?

Pick GLM 4.7 for coding: it scores 33.6 on the Vibe Coding Index against 5.4 for Trinity Large Thinking. Pick Trinity Large Thinking when output tokens cost 2.5x less, or when the context window is larger, 262K against 205K tokens.

Which is cheaper, Trinity Large Thinking or GLM 4.7?

Trinity Large Thinking costs $0.25 per million input tokens and $0.80 per million output tokens; GLM 4.7 costs $0.54 and $1.98. Cost per solved task is known for GLM 4.7 only.

Which has the bigger context window, Trinity Large Thinking or GLM 4.7?

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

How many benchmarks is the Trinity Large Thinking vs GLM 4.7 comparison based on?

49 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 4.7's on 1. Where only one model has a result, the page says so instead of naming a winner.

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