AI 模型情报

Virtuoso Large

openrouter/virtuoso-large

出品方: openrouter · 发布 2025-05-05 · 知识截止: 2025-03-31

$0.750
输入 / 1M token
$1.20
输出 / 1M token
131K
上下文长度
64K
最大输出

Prices in USD per 1M tokens. Unknown means the provider does not publish per-token pricing.

能力清单

工具调用推理结构化输出附件开放权重温度可调
支持模态: 输入 text · 输出 text

Model fit scores

0–100 · higher is better

These scores reward declared capabilities, context size, price and provider availability — they are not benchmark results. Use them as a directional signal alongside your own evaluation.

Coding43
  • Tool calling40/40
  • Structured output0/20
  • Reasoning0/10
  • Context window (100K → 1M)2/20
  • Provider availability1/10
Agents51
  • Tool calling35/35
  • Structured output0/25
  • Reasoning0/15
  • Output token limit15/15
  • Provider availability1/10
JSON / structured output46
  • Structured output / JSON mode0/50
  • Tool calling20/20
  • Temperature control10/10
  • Price-friendly for high-volume16/20
Cost efficiency55
  • Headline price (log-scaled)55/95
  • Has prompt-cache pricing0/5
Long context46
  • Context window (100K → 2M)36/90
  • Has published price for full window10/10
Production-readiness65
  • Number of independent providers5/40
  • Has published per-token price20/20
  • Context window ≥ 8K15/15
  • No data inconsistencies across providers10/10
  • Official model (not derivative)15/15

Cost Efficiency Index

Open full calculator →

Estimated cost using the recommended provider's headline rate. Each scenario fixes average input/output tokens — the assumptions are shown in the third column.

ScenarioCostAssumption
RAG answer
per 1,000 RAG answers
$4.35
< $0.01 per request
5K input tokens (query + 4 retrieved chunks of ~1K each) and a 500-token answer. Typical SaaS knowledge-base bot.
Support ticket triage
per 10,000 tickets
$8.70
< $0.01 per request
1K input tokens (ticket body + system prompt) and a 100-token JSON classification reply. High-volume customer support.
Data extraction
per 1,000 documents
$2.10
< $0.01 per request
2K input tokens (a single document page) and a 500-token JSON extraction. ETL / invoice / form pipelines.
Code review
per 1,000 PRs
$7.20
< $0.01 per request
8K input tokens (diff + surrounding files) and a 1K-token review comment. PR-bot workloads.
Agent step
per 1,000 steps
$9.72
< $0.01 per request
12K input tokens (long-running tool history) and a 600-token tool-call decision. Cost per agent step.

定价详情

推荐定价来自 openrouter · arcee-ai/virtuoso-large

$0.750
输入
$1.20
输出

在 1 家渠道可用

服务商服务商模型 ID输入 / 1M输出 / 1M上下文发布日期
OpenRouter
openrouter
arcee-ai/virtuoso-large$0.750$1.20131K2025-05-05

Frequently asked questions

How much does Virtuoso Large cost?

Virtuoso Large costs $0.750 per 1M input tokens and $1.20 per 1M output tokens, sourced from openrouter. Cache reads, audio tokens and >200K-context tiers (where applicable) are listed in the Pricing detail block above.

What is the context window of Virtuoso Large?

Virtuoso Large has a context window of 131K tokens, with a max output of 64K tokens per reply. This is the total combined size of prompt + completion.

Does Virtuoso Large support tool calling?

Yes. Virtuoso Large supports tool calling (function calling). This makes it suitable for production agent and automation workloads where the model has to invoke external functions reliably.

Does Virtuoso Large support structured output / JSON mode?

No. Virtuoso Large does not support structured output / JSON-schema-constrained decoding. If your workflow requires it, look at the /capabilities/structured-output list for alternatives.

Can Virtuoso Large accept image input?

No. Virtuoso Large only accepts text as input. If you need image input, see our /capabilities/vision list for current vision-capable models.

Is Virtuoso Large open-weight?

No. Virtuoso Large is a proprietary model — only openrouter (and any approved hosting partners) can serve it. The pricing above reflects the cheapest API access.

What are the best alternatives to Virtuoso Large?

If Virtuoso Large doesn't fit, consider INTELLECT-3, LFM2-24B-A2B, LFM2.5-1.2B-Thinking (free). Each one targets the same use case — see the Related links below for direct head-to-head pages.

Where does this data come from?

All numbers are normalised into a single canonical model record and reconciled with each provider's official documentation. We re-pull daily and write any changes (price, context, capability) to the /changelog page.

More openrouter models

Capability lists this model is in

最近更新:

Pricing and capabilities are refreshed daily and reconciled against each provider's official documentation. Always verify critical production decisions with the provider directly.