model release

Arcee AI releases Trinity Large Thinking, open-source reasoning model with 262K context window

TL;DR

Arcee AI has released Trinity Large Thinking, an open-source reasoning model featuring a 262,144 token context window. The model is priced at $0.25 per million input tokens and $0.90 per million output tokens, with free access available through OpenRouter for the first five days.

1 min read
0

Trinity Large Thinking — Quick Specs

Context window262K tokens
Input$0.25/1M tokens
Output$0.9/1M tokens

Arcee AI has released Trinity Large Thinking, an open-source reasoning model designed for complex problem-solving tasks. The model launched on April 1, 2026, and is available through OpenRouter with immediate access.

Specifications

Trinity Large Thinking offers a 262,144 token context window, enabling processing of substantial documents and extended conversations. The model supports OpenRouter's reasoning-enabled architecture, allowing users to access the model's step-by-step thinking process through the reasoning_details array in API responses.

Pricing

Input tokens cost $0.25 per million, while output tokens cost $0.90 per million. Arcee AI is offering free access through OpenRouter for the first five days following launch, allowing developers to evaluate the model at no cost.

Performance and Capabilities

According to Arcee AI, the model demonstrates strong performance on PinchBench, agentic workloads, and reasoning tasks. The reasoning capabilities enable transparent access to the model's internal decision-making process, allowing users to preserve and continue reasoning chains across multi-turn conversations.

Technical Details

Trinity Large Thinking is classified as a reasoning model and is available as open-source weights. OpenRouter routes requests across multiple providers with automatic fallback capability to maximize uptime. The platform normalizes requests and responses across different provider infrastructures.

Developers can integrate the model using standard OpenRouter API endpoints, with optional framework support through third-party SDKs. The reasoning parameter enables thinking mode in requests, while continuing conversations requires preservation of complete reasoning_details to maintain context continuity.

What this means

The release marks Arcee AI's entry into the reasoning model category with a competitive context window size. At $0.25/$0.90 pricing, Trinity Large Thinking positions itself in the mid-range of open-source reasoning models. The five-day free trial strategy reduces friction for adoption testing. The transparent reasoning process differentiates it from black-box alternatives, though real-world performance claims require independent verification against established benchmarks.

Related Articles

model release

Microsoft releases Harrier embedding models with 32K context window, achieving 74.3 on MTEB v2

Microsoft released the Harrier-OSS embedding model family, comprising three variants with 270M, 600M, and 27B parameters. The largest model achieves 74.3 on the Multilingual MTEB v2 benchmark. All models support 32,768 max tokens and multilingual inputs across 40+ languages.

model release

Microsoft releases Harrier embedding models with 32K token context, tops multilingual benchmark

Microsoft has released Harrier-OSS-v1, a family of multilingual text embedding models trained with contrastive learning and knowledge distillation. The 0.6B parameter variant achieves a 69.0 score on the Multilingual MTEB v2 benchmark with support for 32,768 token context windows and 45+ languages.

model release

Alibaba releases Qwen 3.6 Plus Preview with 1M token context, free via OpenRouter

Alibaba's Qwen division has released Qwen 3.6 Plus Preview, a free multimodal model available via OpenRouter with a 1,000,000 token context window. The model claims stronger reasoning and more reliable agentic behavior compared to the 3.5 series, with particular strength in coding and complex problem-solving tasks.

model release

Cohere releases 2B open-source speech model with 5.42% word error rate

Cohere has released Transcribe, a 2 billion parameter open-source automatic speech recognition model that the company claims tops the Hugging Face Open ASR Leaderboard with a 5.42% word error rate. The model supports 14 languages and is available under Apache 2.0 license, outperforming OpenAI's Whisper Large v3 and competing models on both accuracy and throughput metrics.

Comments

Loading...