mimo-v2.5-ttsCompare mimo-v2.5-tts API pricing, supported endpoints, capabilities and access options on voguesly.
cl100k_baseOlder GPT-3.5 familyScores on standardized evaluations. Higher percentages are better — and rank percentile shows
Metrics sourced fromArtificial Analysis 2026-09-30·MiMo V2.5 Tts
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MiMo-V2.5-TTS 适合通知播报、课程朗读、角色旁白和有情绪变化的配音。选择内置音色后,可以用自然语言描述语速、情感、角色状态与停顿,让同一段正文呈现不同表达方式。它也提供唱歌模式,适合尝试把给定歌词合成为演唱片段。
输入消息的角色分工很重要:assistant 内容是待合成的正文,user 内容用于声音风格或场景指令,不会作为正文读出。比如,把课程内容放在 assistant,再用 user 说明“讲给初学者听,语气耐心,关键术语前稍停顿”。不要把这两部分混在同一段口播内容里。
风格控制可以从整段语气细化到句子节奏、词语重音和呼吸停顿。需要更明确表演方向时,可以说明角色、正在发生的场景和朗读指导。正文中的风格标签也能用于控制,唱歌模式应在正文开头添加“(唱歌)”等支持的标签。先用短片段试听,再逐步加细节,比一次叠加很多指令更容易调整。
它支持低延迟流式输出,流式音频应选择 pcm16,便于逐段拼接与播放。完整节目仍需要检查音量、段落衔接和专有名词读法。这个型号使用内置音色,声音设计与参考音频复刻应分别使用对应的专用型号。
默认音色会固定吗? mimo_default 会随部署集群使用不同默认声音;需要明确声音时,指定具体支持的 voice。
能让语音顺便回答问题吗? 应先生成和确认正文,再进行合成,避免把内容创作与声音制作混为一步。
user:你是一位耐心的科学老师。语速稍慢,在问题后自然停顿,最后一句带一点鼓励。
assistant:为什么冰会浮在水面上?答案藏在水结冰时的结构里。接下来,我们用一个小实验看看。
选择具体内置音色并用短句试听;流式输出设置音频格式为 pcm16,按顺序拼接。唱歌时把“(唱歌)”放在正文开头,并提交希望唱出的歌词。长内容按段落处理,统一音色与风格,检查数字、术语和首尾衔接。
Use the linked documentation for model-specific request parameters and examples.
All requests must include Authorization: Bearer <TOKEN> header. Anthropic-formatted endpoints accept the x-api-key header instead.
Generate tokens from the Tokens page; you can scope them to specific models, groups, IPs, and rate-limits.
| Supplier | RPM | TPM | RPD |
|---|---|---|---|
| XiaomiMIMO | Unlimited | Unlimited | Unlimited |
No restriction
Compare mimo-v2.5-tts API pricing, supported endpoints, capabilities and access options on voguesly.
Create an API key with access to mimo-v2.5-tts, then use the exact model ID and a supported endpoint from the API access section. Request fields depend on the selected endpoint.
Pricing depends on the selected provider group and the model billing unit. The current input, output, request, or media prices are shown on this page before sign-up.
The model catalog lists a context window of 8192 tokens. Check the selected endpoint for request limits.
The model catalog lists a maximum output of 8192 tokens. Your request settings may set a lower limit.
Start with the use cases and prompting guidance on this page, then evaluate the model with representative inputs from your project.
