Type
Spec
Rate
Input
per 1M prompt tokens
$0.63
Output
per 1M generated tokens
$3.13
Seed 2.1 Turbo and Kimi K2.7 Code side by side: specs, capabilities, parameters, and live pricing from the EmpirioLabs catalog.
ByteDance 
Moonshot AI Text GenerationSeed 2.1 Turbo from ByteDance and Kimi K2.7 Code from Moonshot AI are both in the Text Generation category, available through the EmpirioLabs API.
| Spec | Seed 2.1 Turbo | Kimi K2.7 Code |
|---|---|---|
| Model ID | seed-2-1-turbo | kimi-k2-7-code |
| Author | ByteDance | Moonshot AI |
| Released | Jul 13, 2026 | Jun 16, 2026 |
| Context window | 229.1K tokens | 256K tokens |
| Max output | 65,536 tokens | 131,072 tokens |
| Input | Text Image Video | Text Image Video |
| Output | Text | Text |
| Structured output | JSON Schema | JSON Schema |
| Region | Malaysia | International |
| Endpoints | POST /v1/chat/completions POST /v1/responses POST /v1/messages POST /v1beta/models/seed-2-1-turbo:generateContent | POST /v1/chat/completions POST /v1/responses POST /v1/messages POST /v1beta/models/kimi-k2-7-code: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 | Seed 2.1 Turbo | Kimi K2.7 Code |
|---|---|---|
| max_tokens | 1 to 65536 | 1 to 262144 Default: 32768 |
| frequency_penalty | -2 to 2 Default: 0 | - |
| presence_penalty | -2 to 2 Default: 0 | - |
| stop | string | string |
| enable_thinking | boolean Default: true | - |
| reasoning_effort | low, medium, high Default: high | - |
| enable_web_search | boolean Default: false | - |
| max_tool_calls | 1 to 10 Default: 3 | 1 to 20 Default: 5 |
| image_detail | low, high, xhigh Default: high | - |
| video_fps | 0.2 to 5 | - |
| response_format | enum | enum |
| tool_web_search | - | boolean Default: false |
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.
Supports text, image, and video inputs with 256K context, function calling, JSON mode structured output, and built-in web search at $0.015 per invoked call. Thinking is always on and cannot be disabled; reasoning tokens are billed as output tokens. Temperature and other sampling overrides are ignored because the model service uses fixed sampling settings. Multi-step function calling through the API must replay the assistant message with its reasoning_content field intact.
Seed 2.1 Turbo 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 seed-2-1-turbo. Both models are called through the same endpoint. Set model to seed-2-1-turbo or kimi-k2-7-code. 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": "seed-2-1-turbo",
"messages": [
{"role": "user", "content": "Write a haiku about the ocean."}
]
}'Prompt tests and comparison runs that cover both models.
Seed 2.1 Turbo is the newer release (Jul 13, 2026); Kimi K2.7 Code was released on Jun 16, 2026. Kimi K2.7 Code has the larger context window: 256K tokens, against 229.1K for Seed 2.1 Turbo. Kimi K2.7 Code returns up to 131,072 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.
Seed 2.1 Turbo is the newer release (Jul 13, 2026); Kimi K2.7 Code was released on Jun 16, 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.
