Type
Spec
Rate
Input
per 1M prompt tokens
$0.435
Output
per 1M generated tokens
$0.87
Web search
per call when invoked
$0.015
MiMo V2.6 Pro and DeepSeek V4 Pro 0813 side by side: specs, capabilities, parameters, and live pricing from the EmpirioLabs catalog.
Xiaomi 
DeepSeek Text GenerationMiMo V2.6 Pro from Xiaomi and DeepSeek V4 Pro 0813 from DeepSeek are both in the Text Generation category, available through the EmpirioLabs API.
| Spec | MiMo V2.6 Pro | DeepSeek V4 Pro 0813 |
|---|---|---|
| Model ID | mimo-v2-6-pro | deepseek-v4-pro-0813 |
| Author | Xiaomi | DeepSeek |
| Released | Sep 22, 2026 | Aug 13, 2026 |
| Context window | 1M tokens | 1M tokens |
| Max output | 131,072 tokens | 393,216 tokens |
| Input | Text Image Video Audio | Text |
| Output | Text | Text |
| Structured output | JSON Schema | JSON Schema |
| Region | Singapore | Singapore |
| Endpoints | POST /v1/chat/completions POST /v1/responses POST /v1/messages POST /v1beta/models/mimo-v2-6-pro:generateContent | POST /v1/chat/completions POST /v1/responses POST /v1/messages POST /v1beta/models/deepseek-v4-pro-0813:generateContent |
| Capabilities |
Live rates from the EmpirioLabs catalog for both models. Each rate card always matches what the API charges.
Request parameters each model lists on EmpirioLabs, with the allowed values or range where one applies. A dash marks a parameter the model does not list.
| Parameter | MiMo V2.6 Pro | DeepSeek V4 Pro 0813 |
|---|---|---|
| enable_thinking | boolean Default: true | boolean Default: true |
| video_fps | 0.1 to 10 | - |
| media_resolution | default, max Default: default | - |
| tool_web_search | boolean Default: false | - |
| web_search_force | boolean Default: false | - |
| web_search_max_keyword | 1 to 5 Default: 3 | - |
| web_search_limit | 1 to 10 Default: 5 | - |
| temperature | 0 to 1.5 Default: 1 | 0 to 2 Default: 0.7 |
| top_p | 0.01 to 1 Default: 0.95 | 0 to 1 Default: 0.9 |
| max_tokens | 1 to 131072 Default: 8192 | 1 to 393216 |
| stop | string | string |
| response_format | enum | enum |
| disable_formatting | boolean Default: false | boolean Default: false |
| reasoning_effort | - | none, low, medium, high, max Default: medium |
| thinking_budget | - | 1 to 393216 Default: 32768 |
| web_search_linkup | - | boolean Default: false |
Web search ($0.015/call) is charged only when invoked. Accepts text, image, video, and audio input and returns text. Thinking is on by default and can be turned off. Sustains complex autonomous workflows with 1000+ tool calls on a 1M context.
Thinking is enabled by default and can be disabled. Reasoning tokens are billed as output tokens. Optional Linkup web search is billed only when invoked.
MiMo V2.6 Pro serves the OpenAI-compatible Chat Completions API. Point any OpenAI SDK at https://api.empiriolabs.ai/v1 with your EmpirioLabs API key and use the model id mimo-v2-6-pro. Both models are called through the same endpoint. Set model to mimo-v2-6-pro or deepseek-v4-pro-0813. Get an API key from the EmpirioLabs dashboard.
curl https://api.empiriolabs.ai/v1/chat/completions \
-H "Authorization: Bearer $EMPIRIOLABS_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "mimo-v2-6-pro",
"messages": [
{"role": "user", "content": "Write a haiku about the ocean."}
]
}'Prompt tests and comparison runs that cover both models.
MiMo V2.6 Pro is the newer release (Sep 22, 2026); DeepSeek V4 Pro 0813 was released on Aug 13, 2026. Both models have a context window of 1M tokens. DeepSeek V4 Pro 0813 returns up to 393,216 output tokens per response, MiMo V2.6 Pro up to 131,072. The specs, rate cards, and parameters on this page come from the live EmpirioLabs catalog.
MiMo V2.6 Pro is the newer release (Sep 22, 2026); DeepSeek V4 Pro 0813 was released on Aug 13, 2026.
MiMo V2.6 Pro lists the lower rate for Input (per 1M prompt tokens) and Output (per 1M generated tokens). Both live rate cards are on this page and always match what the API charges.
Yes. Both models use POST /v1/chat/completions with the same EmpirioLabs API key, so most integrations switch by changing the model value. Check the parameters table on this page first if you rely on a model-specific parameter.
Yes. Open each model in the EmpirioLabs playground and run the same prompt on both, with the parameters the API exposes.
Check out our pricing or reach out if you want your own model deployed on our stack.
