AI Models · Open-Source vs Paid

ARTrinity Large Thinking Open vs GPT-3.5 Turbo (batch) Paid

Trinity Large Thinking vs GPT-3.5 Turbo (batch) compared — price per token, context window, multimodality, openness and which to choose. Can the open-source model replace the paid one? Full 2026 breakdown.

Prices & specs refreshed from live data · olud.ai

Open-model prices = cheapest provider via OpenRouter; official maker rates may be higher.

ARTrinity Large ThinkingOpenArcee ai
$0.25 /M input
$0.8 /M outputNo per-token fees if you self-host
TypeOpen-weight
Context window262K tokens
MultimodalNo
Self-hostYes
GPT-3.5 Turbo (batch)PaidOpenAI
$0.25 /M input
$0.75 /M outputManaged API (no infra to run)
TypeProprietary
Context window16K tokens
MultimodalNo
Self-hostNo
Choose Trinity Large Thinking if you want to self-host, keep your data private and skip per-token fees — it's open-weight and runs on your own hardware. Choose GPT-3.5 Turbo (batch) if you want frontier capability through a managed API with zero infrastructure to run.

Trinity Large Thinking vs GPT-3.5 Turbo (batch) specs

SpecTrinity Large ThinkingGPT-3.5 Turbo (batch)Winner
MakerArcee aiOpenAI
TypeOpen-weightProprietaryARTrinity Large Thinking
Context window262K tokens16K tokensARTrinity Large Thinking
Input price$0.25/M · free self-host$0.25/M= Tie
Output price$0.8/M · free self-host$0.75/MGPT-3.5 Turbo (batch)
Vision / multimodalNoNo
Tool / function callingYesYes= Tie
Self-hostableYesNo (API only)ARTrinity Large Thinking
LicenseOpen weightsProprietaryARTrinity Large Thinking

Price gap & when to choose each

ARChoose Trinity Large Thinking if…
  • You want to self-host or run on your cloud
  • You need the longer 262K context window
  • You prioritize data privacy & control
  • You are building open or reproducible AI
Choose GPT-3.5 Turbo (batch) if…
  • You want frontier performance through a managed API
  • You want the lower output price
  • You value reliability & ecosystem
  • You don't want to manage infrastructure

Feature comparison

CapabilityTrinity Large ThinkingGPT-3.5 Turbo (batch)
Open weights (downloadable)
Self-hostable
Runs fully offline
Vision / multimodal
Tool / function calling
1M+ context window

Benchmarks: Trinity Large Thinking vs GPT-3.5 Turbo (batch)

Independent benchmark scores measured by Artificial Analysis. Higher is better (except latency).

Trinity Large Thinking delivers 3.6× more intelligence per dollar.
Trinity Large Thinking
GPT-3.5 Turbo (batch)
Intelligence index
10.9
5.5
Coding index
25.8
10.7
GPQA
75.2%
29.7%
Humanity's Last Exam
15.8%
Long Context Reasoning
38%
SciCode
40.6%
IFBench
56.3%
τ²-Bench
90.1%
τ-Bench Banking
5.8%
Terminal-Bench
20.6%
Terminal-Bench Hard
22.7%
MMLU-Pro
46.2%
MATH-500
44.1%
Speed
365.5 tok/s
0 tok/s
Latency
1.05s
0s
Intelligence per $
26.5
7.3

Benchmark data by Artificial Analysis.

How Trinity Large Thinking and GPT-3.5 Turbo (batch) score

🏆 Best value & openness: Trinity Large Thinking (4.5 vs 2.6 / 5)
CriterionTrinity Large ThinkingGPT-3.5 Turbo (batch)
Cost-efficiency5.05.0
Context window4.02.0
Openness5.01.5
Self-hosting5.01.0
Multimodality3.53.5

Scores come from live data — output price (cost), context length, open vs closed weights (openness & self-hosting) and vision/tool support (multimodality). Raw task quality isn't scored here; it depends on your benchmark — see the verdict.

What each model is

Trinity Large Thinking Open

Arcee ai · Open-weight

Trinity Large Thinking is a powerful open source reasoning model from the team at Arcee AI. It shows strong performance in PinchBench, agentic workloads, and reasoning tasks. Launch video: https://youtu.be/Gc82AXLa0Rg?si=4RLn6WBz33qT--B7...

GPT-3.5 Turbo (batch) Paid

OpenAI · Proprietary

GPT-3.5 Turbo is OpenAI's fastest model. It can understand and generate natural language or code, and is optimized for chat and traditional completion tasks. Training data up to Sep 2021.

Frequently asked questions

Is Trinity Large Thinking as good as GPT-3.5 Turbo (batch)?

Trinity Large Thinking is open-weight and competitive on many tasks, but GPT-3.5 Turbo (batch) may still lead on the hardest reasoning and agentic work. The gap keeps narrowing — benchmark both on your actual use case before deciding.

Can I run Trinity Large Thinking locally?

Yes. Trinity Large Thinking has open weights, so you can self-host it on your own GPUs or run it via a low-cost API. GPT-3.5 Turbo (batch) is API-only and cannot be self-hosted.

Trinity Large Thinking vs GPT-3.5 Turbo (batch) — which should I pick in 2026?

Choose Trinity Large Thinking if you want to self-host, keep your data private and skip per-token fees — it's open-weight and runs on your own hardware. Choose GPT-3.5 Turbo (batch) if you want frontier capability through a managed API with zero infrastructure to run.

People also compare

Explore more open-source AI

Browse the full open-source model leaderboard, thousands of tools and live benchmarks — all in one place.

Open the leaderboard →