Type
Spec
Rate
Input
per 1M prompt tokens
$1.32
Output
per 1M generated tokens
$3.96
Web Search (Linkup)
per call when invoked
$0.013
DeepSeek V4 Pro 0813 and Seed 2.1 Turbo side by side: specs, capabilities, parameters, and live pricing from the EmpirioLabs catalog.
DeepSeek 
ByteDance Text GenerationDeepSeek V4 Pro 0813 from DeepSeek and Seed 2.1 Turbo from ByteDance are both in the Text Generation category, available through the EmpirioLabs API.
| Spec | DeepSeek V4 Pro 0813 | Seed 2.1 Turbo |
|---|---|---|
| Model ID | deepseek-v4-pro-0813 | seed-2-1-turbo |
| Author | DeepSeek | ByteDance |
| Released | Aug 13, 2026 | Jul 13, 2026 |
| Context window | 1M tokens | 229.1K tokens |
| Max output | 393,216 tokens | 65,536 tokens |
| Input | Text | Text Image Video |
| Output | Text | Text |
| Structured output | JSON Schema | JSON Schema |
| Region | Singapore | Malaysia |
| Endpoints | POST /v1/chat/completions POST /v1/responses POST /v1/messages POST /v1beta/models/deepseek-v4-pro-0813:generateContent | POST /v1/chat/completions POST /v1/responses POST /v1/messages POST /v1beta/models/seed-2-1-turbo: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 | DeepSeek V4 Pro 0813 | Seed 2.1 Turbo |
|---|---|---|
| temperature | 0 to 2 Default: 0.7 | - |
| top_p | 0 to 1 Default: 0.9 | - |
| max_tokens | 1 to 393216 | 1 to 65536 |
| stop | string | string |
| enable_thinking | boolean Default: true | boolean Default: true |
| reasoning_effort | none, low, medium, high, max Default: medium | low, medium, high Default: high |
| thinking_budget | 1 to 393216 Default: 32768 | - |
| response_format | enum | enum |
| web_search_linkup | boolean Default: false | - |
| disable_formatting | boolean Default: false | - |
| frequency_penalty | - | -2 to 2 Default: 0 |
| presence_penalty | - | -2 to 2 Default: 0 |
| enable_web_search | - | boolean Default: false |
| max_tool_calls | - | 1 to 10 Default: 3 |
| image_detail | - | low, high, xhigh Default: high |
| video_fps | - | 0.2 to 5 |
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.
Per-token pricing is flat across the full context window, with no higher rate above 128K. Reasoning is on by default; set enable_thinking to false to answer directly without it.
DeepSeek V4 Pro 0813 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 deepseek-v4-pro-0813. Both models are called through the same endpoint. Set model to deepseek-v4-pro-0813 or seed-2-1-turbo. 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": "deepseek-v4-pro-0813",
"messages": [
{"role": "user", "content": "Write a haiku about the ocean."}
]
}'Prompt tests and comparison runs that cover both models.
DeepSeek V4 Pro 0813 is the newer release (Aug 13, 2026); Seed 2.1 Turbo was released on Jul 13, 2026. DeepSeek V4 Pro 0813 has the larger context window: 1M tokens, against 229.1K for Seed 2.1 Turbo. DeepSeek V4 Pro 0813 returns up to 393,216 output tokens per response, Seed 2.1 Turbo up to 65,536. The specs, rate cards, and parameters on this page come from the live EmpirioLabs catalog.
DeepSeek V4 Pro 0813 is the newer release (Aug 13, 2026); Seed 2.1 Turbo was released on Jul 13, 2026.
Seed 2.1 Turbo 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.
