minimax-h3-context-irCompare minimax-h3-context-ir API pricing, supported endpoints, capabilities and access options on Modelsell.
| Input/ 1M tokens | Output/ 1M tokens |
|---|---|
$0.9 | $3.6 |
ABAB tokenizerScores on standardized evaluations. Higher percentages are better — and rank percentile shows
Metrics sourced fromArtificial Analysis 2026-09-30·MiniMax H3 Context Ir
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Context-IR 读取与 H3 视频生成相同的多模态输入,将创作意图整理为结构化、增强后的提示词。成功结果位于 task.content.prompt,适合先检查镜头、动作与素材描述后再提交视频生成。此操作输出文字,不生成视频文件。
以下为 2026-10-28 供应商目录的美元标准价;组织采购折扣不用于此处的基准计费。实际账单还会应用账户所属分组的既有倍率。成功任务按最终用量结算,失败任务按网关任务流程退款,查询不重复收费。
输入 $0.90/百万 Token,输出 $3.60/百万 Token,分别读取最终 task.usage.prompt_tokens 与 task.usage.completion_tokens。
向网关 /v2/h3_context_ir 发送以下 JSON,并使用自己的网关令牌鉴权:
{
"model": "MiniMax-H3",
"content": [
{
"type": "text",
"text": "A red ceramic teapot rests on a wooden table in warm morning sunlight. No people, no text."
}
],
"duration": 4
}
任务为异步处理。创建响应中的 task_id 是网关公开任务 ID;使用 GET /v2/query/video_generation/{task_id} 查询,每 10–15 秒一次。成功视频见 task.content.url;文字结果见 task.content.prompt。创建、查询及源任务引用使用同一网关令牌和协议。
成功后读取 task.content.prompt。该操作的渠道权限和计费模型为 minimax-h3-context-ir,原生请求正文仍填写 MiniMax-H3。请调用专用 /v2/h3_context_ir 端点;统一视频生成接口不支持此操作。
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 |
|---|---|---|---|
| MiniMax | Unlimited | Unlimited | Unlimited |
| official | Unlimited | Unlimited | Unlimited |
No restriction
Compare minimax-h3-context-ir API pricing, supported endpoints, capabilities and access options on Modelsell.
Create an API key with access to minimax-h3-context-ir, 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.
Start with the use cases and prompting guidance on this page, then evaluate the model with representative inputs from your project.
