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Arcee AI: Virtuoso Large

arcee-ai/virtuoso-large

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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.

Modalities

Input Price

$0.75per 1M

Output Price

$1.20per 1M

Context

131K

Released

May 5, 2025

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API

Sample code and API for Virtuoso Large

OpenRouter normalizes requests and responses across providers for you.

1

Get your API key

Create an API key from your OpenRouter dashboard and set it as an environment variable:

2

Make your first request

Use arcee-ai/virtuoso-large with the OpenRouter API:

OpenRouter provides an OpenAI-compatible completion API to 400+ models & providers that you can call directly, or using the OpenAI SDK. Additionally, some third-party SDKs are available.

In the examples below, the OpenRouter-specific headers are optional. Setting them allows your app to appear on the OpenRouter leaderboards.

Using third-party SDKs

For information about using third-party SDKs and frameworks with OpenRouter, please see our frameworks documentation.

3

Enable streaming

Add "stream": true to your request body to receive responses as server-sent events:

Endpoint

POSThttps://openrouter.ai/api/v1/chat/completions
AuthorizationBearer $OPENROUTER_API_KEY
Content-Typeapplication/json
HTTP-Refereroptional — your site URL, for rankings
X-Titleoptional — your site name, for rankings
Modelarcee-ai/virtuoso-large

Parameters

NameTypeDefaultDescription
max_tokensinteger—This sets the upper limit for the number of tokens the model can generate in response.
temperaturefloat1This setting influences the variety in the model's responses.
top_pfloat1This setting limits the model's choices to a percentage of likely tokens: only the top tokens whose probabilities add up to P.
stoparray—Stop generation immediately if the model encounter any token specified in the stop array.
frequency_penaltyfloat0This setting aims to control the repetition of tokens based on how often they appear in the input.
presence_penaltyfloat0Adjusts how often the model repeats specific tokens already used in the input.
top_kinteger0This limits the model's choice of tokens at each step, making it choose from a smaller set.
repetition_penaltyfloat1Helps to reduce the repetition of tokens from the input.
logit_biasmap—Accepts a JSON object that maps tokens (specified by their token ID in the tokenizer) to an associated bias value from -100 to 100.
min_pfloat0Represents the minimum probability for a token to be considered, relative to the probability of the most likely token.
toolsarray—Tool calling parameter, following OpenAI's tool calling request shape.
tool_choicestring or object—Controls which (if any) tool is called by the model.