Xiaomi: MiMo V2.5
mimo-v2.5
MiMo V2.5 costs $0.549 per million input tokens and $2.74 per million output tokens, supports 1.05M context, and is available through the OpenAI-compatible API.
MiMo V2.5 is Xiaomi's full-modal understanding model for agent workflows. It supports tool calling, structured outputs, and web search with up to 1M context.
Modalities
Text + Image + Video + Audio → Text
Input / output price
$0.549 / $2.74 per 1M
Context
1.05M · max output 131K
Capabilities
Pricing
Billed per token actually used and deducted from your credits.
| Item | USD per 1M tokens |
|---|---|
| Input | $0.549 |
| Output | $2.74 |
| Cached input | $0.110 |
Calculator
Drag the sliders to estimate what this model will cost.
- Per request
- $0.00384
- Per day
- $1.92
- Per month (30 days)
- $57.60
MiMo V2.5: input $0.5486/M · output $2.743/M · cached input $0.1097/M
curl https://api.geniusrelaygpt.com/v1/chat/completions \
-H "Authorization: Bearer $API_KEY" \
-H "Content-Type: application/json" \
-d '{"model": "mimo-v2.5", "max_tokens": 800,
"messages": [{"role": "user", "content": "…"}]}'Code samples
OpenAI-compatible. Set the base URL to https://api.geniusrelaygpt.com/v1 and the model to mimo-v2.5.
curl https://api.geniusrelaygpt.com/v1/chat/completions \
-H "Authorization: Bearer $API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "mimo-v2.5",
"stream": true,
"messages": [{"role": "user", "content": "Hello"}]
}'Use it in a client: Cursor · Cline · SillyTavern · Codex
Parameters
Common OpenAI parameters can be passed as-is.
temperaturetop_pmax_tokensstreamstoppresence_penaltyfrequency_penaltyseedFAQ
- How is MiMo V2.5 billed?
- Input is $0.549 and output is $2.74 per million tokens; cached input is $0.110. The charge for every request is listed in Usage Logs in the console.
- How long is the context window?
- 1.05M tokens. In a long conversation every turn is billed for the full input, so keep the history under control.
- Does it support streaming?
- Yes. Add "stream": true to the request to receive server-sent events in the OpenAI format.