跳转到内容
Alpha
  • 模型
  • 排行榜
  • Ori
联系销售

页脚

OpenRouterOpenRouter
© 2026 OpenRouter, Inc

产品

  • 聊天
  • 排行榜
  • 基准测试
  • 应用
  • 发现
  • 模型
  • Ori
  • 合集
  • 提供商
  • 工具
  • 定价
  • Business
  • Enterprise
  • 实验室

公司

  • 关于
  • 博客
  • 客户
  • 招聘
    招聘
  • 隐私
  • 服务条款
  • 信任中心
  • 支持
  • 兼容 OR
  • 数据
  • 品牌

开发者

  • 文档
  • API 参考
  • 开发者平台
  • 状态
  • AI 站点地图

连接

  • Discord
  • GitHub
  • LinkedIn
  • X
  • YouTube
venice 的网站图标

Venice: Uncensored

cognitivecomputations/dolphin-mistral-24b-venice-edition

模型权重
比较

Venice Uncensored Dolphin Mistral 24B Venice Edition is a fine-tuned variant of Mistral-Small-24B-Instruct-2501, developed by dphn.ai in collaboration with Venice.ai. This model is designed as an “uncensored” instruct-tuned LLM, preserving user control over alignment, system prompts, and behavior. Intended for advanced and unrestricted use cases, Venice Uncensored emphasizes steerability and transparent behavior, removing default safety and alignment layers typically found in mainstream assistant models.

模态
输入 / 输出价格
US$0.20 / US$0.90每 1M
上下文
128K
发布时间
2025年7月9日
知识截止日期
2024年4月
比较
提供商定价性能正常运行时间应用活动常见问题探索

提供商

此模型由一家提供商托管。OpenRouter 将每个请求直接转发给该提供商,无需做出路由决策。

定价

客户为此模型实际支付的平均价格,与提供商公布的价格并列展示。由于缓存和折扣,实际支付的价格往往远低于标价。

性能

吞吐量是模型生成内容的速度(每秒 token 数,越高越好)。延迟是完整的往返时间(越低越好)。TTFT 是首个 token 的响应时间,即您看到内容出现前需要等待的时间(越低越好)。

正常运行时间

正常运行时间是指过去 3 天中至少有一家提供商响应请求的时间百分比。可用性是指成功提供推理服务的时间百分比。OpenRouter 会持续监控,并在某家提供商返回错误时使用次优提供商。

应用

向此模型发送最多流量的公开应用。这能很好地反映实际生产工作负载的情况,也能提示此模型最适合哪些用例。

活动

此模型的 token 用量和请求流量随时间的变化。

API

可直接用于调用此模型的代码。OpenRouter 的 API 与 OpenAI 兼容——大多数 SDK 只需替换基础 URL 即可使用。切换模型时,唯一需要更改的是下方的模型标识符。

目前无法通过 EU 区域内路由使用。 区域内路由文档

探索更多模型

AI 模型排行榜排名
延迟 / 吞吐量
US$0.20US$0.900.76s69 tps
100.00%
吞吐量
69token/秒

P50,所有提供商中最佳

延迟
0.76秒

P50,最佳提供商

正常运行时间(3 天)模型可访问。请求已路由至提供商。
100.00%
可用性(3 天)模型通过任意提供商返回了推理结果。错误和空响应均计为失败。
99.90%

过去 3 天的可用性

最近 72 小时
可用性 99.90%
3 天前2 天前昨天现在

过去 24 小时的可用性

OpenRouter Availability
99.89%

当上游提供商发生错误时,如果您的请求筛选条件允许,我们可以通过路由到另一家健康的提供商来恢复服务。您可以通过以下接口以编程方式访问各提供商的正常运行时间数据: 端点 API。了解更多有关我们的 负载均衡和提供商路由选项。

1.
https://chamadavip-orcin.vercel.app/ 的网站图标
ChamadaVIP
新增
855Mtoken
2.
https://hotlive-backend-production.up.railway.app/ 的网站图标
HotLive
新增
492Mtoken
3.
https://sillytavern.app/ 的网站图标
SillyTavern
SillyTavern is the LLM frontend for power users, a chat interface that connects to any model and gives deep control through character creation, roleplay, and prompt customization.
335Mtoken
4.
https://janitorai.com/ 的网站图标
Janitor AI
Janitor AI is a chatbot platform where users create and chat with custom AI characters for interactive roleplay, storytelling, and immersive fiction.
163Mtoken
5.
https://chub.ai/ 的网站图标
Chub AI
GenAI for everyone
122Mtoken

常见问题

Venice Uncensored Dolphin Mistral 24B Venice Edition is a fine-tuned variant of Mistral-Small-24B-Instruct-2501, developed by dphn.ai in collaboration with Venice.ai. This model is designed as an “uncensored” instruct-tuned LLM, preserving user control over alignment, system prompts, and behavior.

Uncensored 的费用为 US$0.20/百万输入 token 和 US$0.90/百万输出 token。

Uncensored 的上下文窗口为 128,000 个 token。它最多支持 8,192 个补全 token。

不支持。Uncensored 不接受 tools,因此无法使用函数调用。 它支持使用 response_format 输出 JSON,但不强制执行 JSON Schema。

Uncensored 于 2025年7月9日 发布。其知识截止日期为 2024年4月30日。

更多模型,来自 Cognitive Computations

Dolphin3.0 R1 Mistral 24B

Dolphin 3.0 R1 is the next generation of the Dolphin series of instruct-tuned models. Designed to be the ultimate general purpose local model, enabling coding, math, agentic, function calling, and general use cases.

The R1 version has been trained for 3 epochs to reason using 800k reasoning traces from the Dolphin-R1 dataset.

Dolphin aims to be a general purpose reasoning instruct model, similar to the models behind ChatGPT, Claude, Gemini.

Part of the Dolphin 3.0 Collection Curated and trained by Eric Hartford, Ben Gitter, BlouseJury and DphnAI

文本33K 上下文
Dolphin3.0 Mistral 24B

Dolphin 3.0 is the next generation of the Dolphin series of instruct-tuned models. Designed to be the ultimate general purpose local model, enabling coding, math, agentic, function calling, and general use cases.

Dolphin aims to be a general purpose instruct model, similar to the models behind ChatGPT, Claude, Gemini.

Part of the Dolphin 3.0 Collection Curated and trained by Eric Hartford, Ben Gitter, BlouseJury and DphnAI

文本33K 上下文
Dolphin Llama 3 70B 🐬

Dolphin 2.9 is designed for instruction following, conversational, and coding. This model is a fine-tune of Llama 3 70B. It demonstrates improvements in instruction, conversation, coding, and function calling abilities, when compared to the original.

Uncensored and is stripped of alignment and bias, it requires an external alignment layer for ethical use. Users are cautioned to use this highly compliant model responsibly, as detailed in a blog post about uncensored models at erichartford.com/uncensored-models.

Usage of this model is subject to Meta's Acceptable Use Policy.

文本8K 上下文
Dolphin 2.9.2 Mixtral 8x22B 🐬

Dolphin 2.9 is designed for instruction following, conversational, and coding. This model is a finetune of Mixtral 8x22B Instruct. It features a 64k context length and was fine-tuned with a 16k sequence length using ChatML templates.

This model is a successor to Dolphin Mixtral 8x7B.

The model is uncensored and is stripped of alignment and bias. It requires an external alignment layer for ethical use. Users are cautioned to use this highly compliant model responsibly, as detailed in a blog post about uncensored models at erichartford.com/uncensored-models.

#moe #uncensored

文本66K 上下文
Dolphin 2.6 Mixtral 8x7B 🐬

This is a 16k context fine-tune of Mixtral-8x7b. It excels in coding tasks due to extensive training with coding data and is known for its obedience, although it lacks DPO tuning.

The model is uncensored and is stripped of alignment and bias. It requires an external alignment layer for ethical use. Users are cautioned to use this highly compliant model responsibly, as detailed in a blog post about uncensored models at erichartford.com/uncensored-models.

#moe #uncensored

文本33K 上下文