Enter opens the highlighted result. Esc closes.

Trinity Large Thinking vs Llama 3.3 70B Instruct

Updated October 21, 2026. 36 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 3.3 70B Instruct
Trinity Large ThinkingArcee AI
Coding
No data
Overall
10.8
Output $/M
$0.80
36
Llama 3.3 70B InstructMeta Llama
Coding
No data
Overall
7.7
Output $/M
$0.72
0
vs boards won of 36 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 131K tokens.

Model ATrinity Large ThinkingArcee AINot benchmarked1 independent benchmarkNo cost per solved taskModel BLlama 3.3 70B InstructMeta LlamaNot benchmarkedNo coding benchmarkNo cost per solved task
Shared results
36
Trinity Large Thinking only
16
Llama 3.3 70B Instruct only
15
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 3.3 70B Instruct not benchmarked.
Widest category
Agentic work, 63.5 points apart on average over 1 shared benchmark.
Widest single gap
τ²-Bench Telecom: Trinity Large Thinking 90.1% against Llama 3.3 70B Instruct 26.6%, 63.5 points apart on a 0 to 100 scale.
Output price
Trinity Large Thinking $0.80 against Llama 3.3 70B Instruct $0.72 per million output tokens, 1.1x apart.
Context window
Trinity Large Thinking takes 262K tokens, Llama 3.3 70B Instruct 131K.

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 3.3 70B InstructTies
Coding40
Intelligence10
Agentic work10
Reasoning50
Math20
Knowledge40
General190
All shared boards360
CodingLike-for-likeSix of these boards feed the Vibe Coding Index40
Coding benchmarks for Trinity Large Thinking and Llama 3.3 70B Instruct
BenchmarkTrinity Large ThinkingLlama 3.3 70B InstructLeader
LMArena WebDev1238Not measuredOnly Trinity Large Thinking measured
AA Coding Index25.811.9Trinity Large Thinking
LiveCodeBench (Artificial Analysis run)Not measured28.8%Only Llama 3.3 70B Instruct measured
SciCode40.6%Not measuredOnly Trinity Large Thinking measured
Terminal-Bench Hard (Artificial Analysis run)22.7%3.0%Trinity Large Thinking
WeirdMLNot measured14.4%Only Llama 3.3 70B Instruct measured
LMArena Text: coding13571268Trinity Large Thinking
LMArena Text: software and IT13621273Trinity 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 28 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Trinity Large Thinking and Llama 3.3 70B Instruct
BenchmarkTrinity Large ThinkingLlama 3.3 70B InstructLeader
AA Intelligence Index10.87.7Trinity Large Thinking
Epoch Capabilities IndexNot measured127.3Only Llama 3.3 70B Instruct measured
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for Trinity Large Thinking and Llama 3.3 70B Instruct
BenchmarkTrinity Large ThinkingLlama 3.3 70B InstructLeader
AA Agentic Index1.0Not measuredOnly Trinity Large Thinking measured
τ²-Bench Telecom90.1%26.6%Trinity Large Thinking
BALROGNot measured23.0%Only Llama 3.3 70B 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 3.3 70B Instruct
BenchmarkTrinity Large ThinkingLlama 3.3 70B InstructLeader
GPQA Diamond (Artificial Analysis run)75.2%49.8%Trinity Large Thinking
Humanity's Last Exam (Artificial Analysis run)15.8%3.6%Trinity Large Thinking
GPQA Diamond (Epoch AI run)Not measured47.4%Only Llama 3.3 70B Instruct measured
SimpleBenchNot measured19.9%Only Llama 3.3 70B Instruct measured
LMArena Text: hard prompts13421257Trinity Large Thinking
LMArena Text: expert13591225Trinity Large Thinking
LMArena Text: hard prompts in English13561277Trinity Large Thinking
Neither model has a result on the other 14 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for Trinity Large Thinking and Llama 3.3 70B Instruct
BenchmarkTrinity Large ThinkingLlama 3.3 70B InstructLeader
AA Math IndexNot measured7.7Only Llama 3.3 70B Instruct measured
AIME 2025 (Artificial Analysis run)Not measured7.7%Only Llama 3.3 70B Instruct measured
OTIS Mock AIMENot measured5.1%Only Llama 3.3 70B Instruct measured
MATH level 5Not measured41.6%Only Llama 3.3 70B Instruct measured
LMArena Text: math13651267Trinity Large Thinking
LMArena Text: mathematical work13501267Trinity Large Thinking
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for Trinity Large Thinking and Llama 3.3 70B Instruct
BenchmarkTrinity Large ThinkingLlama 3.3 70B 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 measured71.3%Only Llama 3.3 70B Instruct measured
MMLUNot measured86.3%Only Llama 3.3 70B Instruct measured
LMArena Text: science13551284Trinity Large Thinking
LMArena Text: medicine and healthcare13491275Trinity Large Thinking
LMArena Text: legal and government13451284Trinity Large Thinking
LMArena Text: business and finance13291243Trinity Large Thinking
Neither model has a result on the other 9 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 3.3 70B Instruct
BenchmarkTrinity Large ThinkingLlama 3.3 70B 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 index190
General benchmarks for Trinity Large Thinking and Llama 3.3 70B Instruct
BenchmarkTrinity Large ThinkingLlama 3.3 70B InstructLeader
IFBench56.3%47.1%Trinity Large Thinking
Long context reasoning (AA-LCR)38.0%15.7%Trinity Large Thinking
DTBenchNot measured59.5%Only Llama 3.3 70B Instruct measured
LMCANot measured17.5%Only Llama 3.3 70B Instruct measured
Fiction.LiveBenchNot measured33.3%Only Llama 3.3 70B Instruct measured
Surface Evolver Bench15.6%Not measuredOnly Trinity Large Thinking measured
LMArena Text13401274Trinity Large Thinking
LMArena Text: instruction following13261242Trinity Large Thinking
LMArena Text: creative writing13081250Trinity Large Thinking
LMArena Text: English13561303Trinity Large Thinking
LMArena Text: non-English13251236Trinity Large Thinking
LMArena Text: Chinese13711217Trinity Large Thinking
LMArena Text: German13561251Trinity Large Thinking
LMArena Text: Japanese13121150Trinity Large Thinking
LMArena Text: Korean13061142Trinity Large Thinking
LMArena Text: French13661282Trinity Large Thinking
LMArena Text: Spanish13271269Trinity Large Thinking
LMArena Text: Russian13381252Trinity Large Thinking
LMArena Text: Polish13121259Trinity Large Thinking
LMArena Text: multi-turn13201280Trinity Large Thinking
LMArena Text: longer queries13181255Trinity Large Thinking
LMArena Text: writing and language13171255Trinity Large Thinking
LMArena Text: entertainment and media12961241Trinity Large Thinking
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 Llama 3.3 70B Instruct
BenchmarkTrinity Large ThinkingLlama 3.3 70B 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 3.3 70B Instruct$0.0008Fits in one request

Trinity Large Thinking costs less

Repository review

50K input + 3K output tokens

Trinity Large Thinking$0.015Fits in one request
Llama 3.3 70B Instruct$0.025Fits in one request

Trinity Large Thinking costs less

Agent loop

200K input + 10K output tokens

Trinity Large Thinking$0.058Fits in one request
Llama 3.3 70B Instruct$0.097Exceeds 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 Llama 3.3 70B Instruct
SpecificationArcee AI Trinity Large ThinkingMeta Llama 3.3 70B Instruct
MakerArcee AIMeta Llama
WeightsOpen weightsOpen weights
ReleasedApril 1, 2026December 6, 2024
Context window262K131K
Input $/Mtok$0.25$0.45
Output $/Mtok$0.80$0.72
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 3.3 70B 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 131K tokens.

Which is cheaper, Trinity Large Thinking or Llama 3.3 70B Instruct?

Trinity Large Thinking costs $0.25 per million input tokens and $0.80 per million output tokens; Llama 3.3 70B Instruct costs $0.45 and $0.72. Cost per solved task is known for neither of them.

Which has the bigger context window, Trinity Large Thinking or Llama 3.3 70B Instruct?

Trinity Large Thinking, with 262K tokens against 131K.

How many benchmarks is the Trinity Large Thinking vs Llama 3.3 70B Instruct comparison based on?

36 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 3.3 70B Instruct's on 0. Where only one model has a result, the page says so instead of naming a winner.

Compare next