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Trinity Large Thinking vs Llama 3.2 1B Instruct

Updated October 21, 2026. 30 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 Llama 3.2 1B Instruct
Trinity Large ThinkingArcee AI
Coding
No data
Overall
10.8
Output $/M
$0.80
30
Llama 3.2 1B InstructMeta Llama
Coding
No data
Overall
4.8
Output $/M
$0.201
0
vs boards won of 30 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 60K tokens.

Model ATrinity Large ThinkingArcee AINot benchmarked1 independent benchmarkNo cost per solved taskModel BLlama 3.2 1B InstructMeta LlamaNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
30
Trinity Large Thinking only
22
Llama 3.2 1B Instruct only
7
Like-for-like categories
7 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, Llama 3.2 1B Instruct not benchmarked.
Widest category
Agentic work, 90.1 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Trinity Large Thinking 90.1% against Llama 3.2 1B Instruct 0.0%, 90.1 points apart on a 0 to 100 scale.
Output price
Trinity Large Thinking $0.80 against Llama 3.2 1B Instruct $0.201 per million output tokens, 4.0x apart.
Context window
Trinity Large Thinking takes 262K tokens, Llama 3.2 1B Instruct 60K.

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 ThinkingBarsLlama 3.2 1B InstructTies
Coding30
Intelligence10
Agentic work10
Reasoning50
Math20
Knowledge40
General140
All shared boards300
CodingLike-for-likeSix of these boards feed the Vibe Coding Index30
Coding benchmarks for Trinity Large Thinking and Llama 3.2 1B Instruct
BenchmarkTrinity Large ThinkingLlama 3.2 1B InstructLeader
LMArena WebDev1238Not measuredOnly Trinity Large Thinking measured
AA Coding Index25.8Not measuredOnly Trinity Large Thinking measured
LiveCodeBench (Artificial Analysis run)Not measured1.9%Only Llama 3.2 1B Instruct measured
SciCode40.6%Not measuredOnly Trinity Large Thinking measured
Terminal-Bench Hard (Artificial Analysis run)22.7%0.0%Trinity Large Thinking
LMArena Text: coding13571070Trinity Large Thinking
LMArena Text: software and IT13621056Trinity Large Thinking
LMArena WebDev: React1231Not measuredOnly Trinity Large Thinking measured
LMArena WebDev: HTML1240Not measuredOnly Trinity Large Thinking measured
Neither model has a result on the other 29 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Trinity Large Thinking and Llama 3.2 1B Instruct
BenchmarkTrinity Large ThinkingLlama 3.2 1B InstructLeader
AA Intelligence Index10.84.8Trinity Large Thinking
Neither model has a result on the other 1 board here
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for Trinity Large Thinking and Llama 3.2 1B Instruct
BenchmarkTrinity Large ThinkingLlama 3.2 1B InstructLeader
AA Agentic Index1.0Not measuredOnly Trinity Large Thinking measured
τ²-Bench Telecom90.1%0.0%Trinity Large Thinking
BALROGNot measured6.6%Only Llama 3.2 1B Instruct measured
Neither model has a result on the other 36 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for Trinity Large Thinking and Llama 3.2 1B Instruct
BenchmarkTrinity Large ThinkingLlama 3.2 1B InstructLeader
GPQA Diamond (Artificial Analysis run)75.2%19.6%Trinity Large Thinking
Humanity's Last Exam (Artificial Analysis run)15.8%5.5%Trinity Large Thinking
GPQA Diamond (Epoch AI run)Not measured23.9%Only Llama 3.2 1B Instruct measured
LMArena Text: hard prompts13421044Trinity Large Thinking
LMArena Text: expert13591007Trinity Large Thinking
LMArena Text: hard prompts in English13561087Trinity Large Thinking
Neither model has a result on the other 15 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for Trinity Large Thinking and Llama 3.2 1B Instruct
BenchmarkTrinity Large ThinkingLlama 3.2 1B InstructLeader
AA Math IndexNot measured0.0Only Llama 3.2 1B Instruct measured
AIME 2025 (Artificial Analysis run)Not measured0.0%Only Llama 3.2 1B Instruct measured
OTIS Mock AIMENot measured0.6%Only Llama 3.2 1B Instruct measured
LMArena Text: math13651086Trinity Large Thinking
LMArena Text: mathematical work13501098Trinity Large Thinking
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for Trinity Large Thinking and Llama 3.2 1B Instruct
BenchmarkTrinity Large ThinkingLlama 3.2 1B InstructLeader
CaseLaw (Vals AI)57.9%Not measuredOnly Trinity Large Thinking measured
CorpFin (Vals AI)54.7%Not measuredOnly Trinity Large Thinking measured
MMLU Pro (Artificial Analysis run)Not measured20.0%Only Llama 3.2 1B Instruct measured
LMArena Text: science13551055Trinity Large Thinking
LMArena Text: medicine and healthcare13491009Trinity Large Thinking
LMArena Text: legal and government13451071Trinity Large Thinking
LMArena Text: business and finance13291000Trinity Large Thinking
Neither model has a result on the other 10 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 Llama 3.2 1B Instruct
BenchmarkTrinity Large ThinkingLlama 3.2 1B InstructLeader
Design Arena: websites1137Not measuredOnly Trinity Large Thinking measured
Design Arena: UI components1045Not measuredOnly Trinity Large Thinking measured
Design Arena: game dev1079Not measuredOnly Trinity Large Thinking measured
Design Arena: data viz1098Not measuredOnly Trinity Large Thinking measured
Design Arena: 3D1082Not measuredOnly Trinity Large Thinking measured
Design Arena: all code categories1117Not measuredOnly Trinity Large Thinking measured
Design Arena: SVG1017Not 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 index140
General benchmarks for Trinity Large Thinking and Llama 3.2 1B Instruct
BenchmarkTrinity Large ThinkingLlama 3.2 1B InstructLeader
IFBench56.3%22.8%Trinity Large Thinking
Long context reasoning (AA-LCR)38.0%6.7%Trinity Large Thinking
Surface Evolver Bench15.6%Not measuredOnly Trinity Large Thinking measured
LMArena Text13401055Trinity Large Thinking
LMArena Text: instruction following13261031Trinity Large Thinking
LMArena Text: creative writing13081033Trinity Large Thinking
LMArena Text: English13561117Trinity Large Thinking
LMArena Text: non-English1325973Trinity Large Thinking
LMArena Text: Chinese1371959Trinity Large Thinking
LMArena Text: German13561014Trinity Large Thinking
LMArena Text: Japanese1312Not measuredOnly Trinity Large Thinking measured
LMArena Text: Korean1306Not measuredOnly Trinity Large Thinking measured
LMArena Text: French1366Not measuredOnly Trinity Large Thinking measured
LMArena Text: Spanish1327Not measuredOnly Trinity Large Thinking measured
LMArena Text: Russian1338941Trinity Large Thinking
LMArena Text: Polish1312Not measuredOnly Trinity Large Thinking measured
LMArena Text: multi-turn13201030Trinity Large Thinking
LMArena Text: longer queries13181050Trinity Large Thinking
LMArena Text: writing and language13171030Trinity Large Thinking
LMArena Text: entertainment and media12961025Trinity Large Thinking
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 Llama 3.2 1B Instruct
BenchmarkTrinity Large ThinkingLlama 3.2 1B InstructLeader
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
Llama 3.2 1B Instruct$0.0001Fits in one request

Llama 3.2 1B Instruct costs less

Repository review

50K input + 3K output tokens

Trinity Large Thinking$0.015Fits in one request
Llama 3.2 1B Instruct$0.0020Fits in one request

Llama 3.2 1B Instruct costs less

Agent loop

200K input + 10K output tokens

Trinity Large Thinking$0.058Fits in one request
Llama 3.2 1B Instruct$0.0074Exceeds the context window

Llama 3.2 1B Instruct 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 Llama 3.2 1B Instruct
SpecificationArcee AI Trinity Large ThinkingMeta Llama 3.2 1B Instruct
MakerArcee AIMeta Llama
WeightsOpen weightsOpen weights
ReleasedApril 1, 2026September 25, 2024
Context window262K60K
Input $/Mtok$0.25$0.027
Output $/Mtok$0.80$0.201
Coding indexNot benchmarkedNot benchmarked
Independent measurements behind it10
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Trinity Large Thinking better than Llama 3.2 1B Instruct 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 60K tokens.

Which is cheaper, Trinity Large Thinking or Llama 3.2 1B Instruct?

Trinity Large Thinking costs $0.25 per million input tokens and $0.80 per million output tokens; Llama 3.2 1B Instruct costs $0.027 and $0.201. Cost per solved task is known for neither of them.

Which has the bigger context window, Trinity Large Thinking or Llama 3.2 1B Instruct?

Trinity Large Thinking, with 262K tokens against 60K.

How many benchmarks is the Trinity Large Thinking vs Llama 3.2 1B Instruct comparison based on?

30 benchmarks have a result for both models as of October 21, 2026. Trinity Large Thinking's coding index rests on 1 independent benchmark and Llama 3.2 1B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.

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