Virtuoso Large

Arcee Ai chattool_use

API ID: arcee-ai/virtuoso-large

Input Price
$0.75
/1M tokens
Output Price
$1.20
/1M tokens

About Virtuoso Large

Virtuoso‑Large is Arcee's top‑tier general‑purpose LLM at 72 B parameters, tuned to tackle cross‑domain reasoning, creative writing and enterprise QA. Unlike many 70 B peers, it retains the 128 k context inherited from Qwen 2.5, letting it ingest books, codebases or financial filings wholesale. Training blended DeepSeek R1 distillation, multi‑epoch supervised fine‑tuning and a final DPO/RLHF alignment stage, yielding strong performance on BIG‑Bench‑Hard, GSM‑8K and long‑context Needle‑In‑Haystack tests. Enterprises use Virtuoso‑Large as the "fallback" brain in Conductor pipelines when other SLMs flag low confidence. Despite its size, aggressive KV‑cache optimizations keep first‑token latency in the low‑second range on 8× H100 nodes, making it a practical production‑grade powerhouse.

💰
Price Ranking
#923 lowest price among 1240 Chat models

Model Specifications

Context Length
131k
Max Output
64k
Release Date
2025-05-05
Capabilities
chat tool_use
Input Modalities
text
Output Modalities
text

Best For

  • Conversations, content writing, general assistance

Consider Alternatives For

  • Image understanding (needs vision capability)

💰 Real-World Cost Examples

Estimated monthly costs for common use cases

Personal AI Assistant
$0.70
/month
50 conversations/day, ~500 tokens each
Customer Service Bot
$22.05
/month
1000 tickets/day, ~800 tokens each

Arcee Ai Model Lineup

Compare all models from Arcee Ai to find the best fit

Model Input Output Context Capabilities
Virtuoso Large Current $0.75 $1.20 131k chat tool_use
Trinity Large Thinking $0.25 $0.80 262k chat reasoning tool_use

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🚀 Quick Start

Get started with Virtuoso Large API

OpenAI-compatible SDK
from openai import OpenAI

client = OpenAI(
    base_url="https://api.provider.com/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="arcee-ai/virtuoso-large",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)
print(response.choices[0].message.content)