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Trinity Large Thinking vs GLM 4.7 Flash

Updated October 21, 2026. 41 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 Flash
Trinity Large ThinkingArcee AI
Coding
No data
Overall
10.8
Output $/M
$0.80
12
GLM 4.7 FlashZ.ai
Coding
No data
Overall
14.9
Output $/M
$0.40
29
vs boards won of 41 shared

Decision reading

Neither model has a coding score yet, so the two cannot be ranked on coding.

Trinity Large Thinking has the edge where the context window is larger, 262K against 200K tokens, and where what matters is LMArena Text: coding or LMArena Text: software and IT, where it leads.

Model ATrinity Large ThinkingArcee AINot benchmarked1 independent benchmarkNo cost per solved taskModel BGLM 4.7 FlashZ.aiNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
41
Trinity Large Thinking only
11
GLM 4.7 Flash only
2
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 not benchmarked, GLM 4.7 Flash not benchmarked.
Widest category
Agentic work, 8.8 points apart on average over 1 shared benchmark.
Widest single gap
Design Arena: UI components: Trinity Large Thinking 1045 against GLM 4.7 Flash 1208, 20.4 points apart on a 0 to 100 scale.
Output price
Trinity Large Thinking $0.80 against GLM 4.7 Flash $0.40 per million output tokens, 2.0x apart.
Context window
Trinity Large Thinking takes 262K tokens, GLM 4.7 Flash 200K.

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 4.7 FlashTies
Coding12
Intelligence01
Agentic work01
Reasoning32
Math11
Knowledge13
Web design07
General612
All shared boards1229
CodingLike-for-likeSix of these boards feed the Vibe Coding Index12
Coding benchmarks for Trinity Large Thinking and GLM 4.7 Flash
BenchmarkTrinity Large ThinkingGLM 4.7 FlashLeader
LMArena WebDev1238Not measuredOnly Trinity Large Thinking measured
AA Coding Index25.8Not measuredOnly Trinity Large Thinking measured
SciCode40.6%Not measuredOnly Trinity Large Thinking measured
Terminal-Bench Hard (Artificial Analysis run)22.7%22.0%Trinity Large Thinking
LMArena Text: coding13571382GLM 4.7 Flash
LMArena Text: software and IT13621389GLM 4.7 Flash
LMArena WebDev: React1231Not measuredOnly Trinity Large Thinking measured
LMArena WebDev: HTML1240Not measuredOnly Trinity Large Thinking measured
Neither model has a result on the other 30 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for Trinity Large Thinking and GLM 4.7 Flash
BenchmarkTrinity Large ThinkingGLM 4.7 FlashLeader
AA Intelligence Index10.814.9GLM 4.7 Flash
Neither model has a result on the other 1 board here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index01
Agentic work benchmarks for Trinity Large Thinking and GLM 4.7 Flash
BenchmarkTrinity Large ThinkingGLM 4.7 FlashLeader
AA Agentic Index1.0Not measuredOnly Trinity Large Thinking measured
τ²-Bench Telecom90.1%98.8%GLM 4.7 Flash
Neither model has a result on the other 37 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index32
Reasoning benchmarks for Trinity Large Thinking and GLM 4.7 Flash
BenchmarkTrinity Large ThinkingGLM 4.7 FlashLeader
GPQA Diamond (Artificial Analysis run)75.2%58.1%Trinity Large Thinking
Humanity's Last Exam (Artificial Analysis run)15.8%7.6%Trinity Large Thinking
GPQA Diamond (Epoch AI run)Not measured60.5%Only GLM 4.7 Flash measured
LMArena Text: hard prompts13421356GLM 4.7 Flash
LMArena Text: expert13591357Trinity Large Thinking
LMArena Text: hard prompts in English13561369GLM 4.7 Flash
Neither model has a result on the other 15 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index11
Math benchmarks for Trinity Large Thinking and GLM 4.7 Flash
BenchmarkTrinity Large ThinkingGLM 4.7 FlashLeader
OTIS Mock AIMENot measured58.3%Only GLM 4.7 Flash measured
LMArena Text: math13651355Trinity Large Thinking
LMArena Text: mathematical work13501369GLM 4.7 Flash
Neither model has a result on the other 10 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index13
Knowledge benchmarks for Trinity Large Thinking and GLM 4.7 Flash
BenchmarkTrinity Large ThinkingGLM 4.7 FlashLeader
CaseLaw (Vals AI)57.9%Not measuredOnly Trinity Large Thinking measured
CorpFin (Vals AI)54.7%Not measuredOnly Trinity Large Thinking measured
LMArena Text: science13551358GLM 4.7 Flash
LMArena Text: medicine and healthcare13491343Trinity Large Thinking
LMArena Text: legal and government13451357GLM 4.7 Flash
LMArena Text: business and finance13291343GLM 4.7 Flash
Neither model has a result on the other 11 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index07
Web design benchmarks for Trinity Large Thinking and GLM 4.7 Flash
BenchmarkTrinity Large ThinkingGLM 4.7 FlashLeader
Design Arena: websites11371194GLM 4.7 Flash
Design Arena: UI components10451208GLM 4.7 Flash
Design Arena: game dev10791135GLM 4.7 Flash
Design Arena: data viz10981123GLM 4.7 Flash
Design Arena: 3D10821121GLM 4.7 Flash
Design Arena: all code categories11171178GLM 4.7 Flash
Design Arena: SVG10171038GLM 4.7 Flash
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 index612
General benchmarks for Trinity Large Thinking and GLM 4.7 Flash
BenchmarkTrinity Large ThinkingGLM 4.7 FlashLeader
IFBench56.3%60.8%GLM 4.7 Flash
Long context reasoning (AA-LCR)38.0%41.7%GLM 4.7 Flash
Surface Evolver Bench15.6%Not measuredOnly Trinity Large Thinking measured
LMArena Text13401351GLM 4.7 Flash
LMArena Text: instruction following13261327GLM 4.7 Flash
LMArena Text: creative writing13081296Trinity Large Thinking
LMArena Text: English13561373GLM 4.7 Flash
LMArena Text: non-English13251330GLM 4.7 Flash
LMArena Text: Chinese13711403GLM 4.7 Flash
LMArena Text: German13561336Trinity Large Thinking
LMArena Text: Japanese1312Not measuredOnly Trinity Large Thinking measured
LMArena Text: Korean13061283Trinity Large Thinking
LMArena Text: French13661332Trinity Large Thinking
LMArena Text: Spanish13271350GLM 4.7 Flash
LMArena Text: Russian13381333Trinity Large Thinking
LMArena Text: Polish13121291Trinity Large Thinking
LMArena Text: multi-turn13201342GLM 4.7 Flash
LMArena Text: longer queries13181345GLM 4.7 Flash
LMArena Text: writing and language13171320GLM 4.7 Flash
LMArena Text: entertainment and media12961304GLM 4.7 Flash
Neither model has a result on the other 26 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 Flash
BenchmarkTrinity Large ThinkingGLM 4.7 FlashLeader
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 Flash$0.0003Fits in one request

GLM 4.7 Flash costs less

Repository review

50K input + 3K output tokens

Trinity Large Thinking$0.015Fits in one request
GLM 4.7 Flash$0.0045Fits in one request

GLM 4.7 Flash costs less

Agent loop

200K input + 10K output tokens

Trinity Large Thinking$0.058Fits in one request
GLM 4.7 Flash$0.017Exceeds the context window

GLM 4.7 Flash 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 Flash
SpecificationArcee AI Trinity Large ThinkingZ.ai GLM 4.7 Flash
MakerArcee AIZ.ai
WeightsOpen weightsOpen weights
ReleasedApril 1, 2026January 19, 2026
Context window262K200K
Input $/Mtok$0.25$0.0653
Output $/Mtok$0.80$0.40
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Trinity Large Thinking better than GLM 4.7 Flash for coding?

Neither model has a coding score yet, so the two cannot be ranked on coding. Trinity Large Thinking has the edge where the context window is larger, 262K against 200K tokens, and where what matters is LMArena Text: coding or LMArena Text: software and IT, where it leads.

Which is cheaper, Trinity Large Thinking or GLM 4.7 Flash?

Trinity Large Thinking costs $0.25 per million input tokens and $0.80 per million output tokens; GLM 4.7 Flash costs $0.0653 and $0.40. Cost per solved task is known for neither of them.

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

Trinity Large Thinking, with 262K tokens against 200K.

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

41 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 Flash's on 0. Where only one model has a result, the page says so instead of naming a winner.

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