Seed 2.1 Turbo, Kimi K2.7 Code, and DeepSeek V4 Pro are three of the strongest coding and agent models on EmpirioLabs. All three reason before answering, call tools with function calling, and return strict JSON, and all three run on the same OpenAI-compatible API, so you can switch between them by changing one field. This post compares them on the facts that matter for real coding and agent work: context window, price, modalities, and capabilities.
At a glance
| Model | Context | Eingabe | Ausgabe | Image + video | Structured output |
|---|---|---|---|---|---|
| Seed 2.1 Turbo | 256K | $0.63 | $3.13 | Yes | JSON schema |
| Kimi K2.7 Code | 256K | $0.95 | $4.00 | Yes | JSON schema |
| DeepSeek V4 Pro | 1M | $1.65 | $3.30 | Text only | JSON schema |
Input and output prices are current pay-as-you-go rates in USD per 1M tokens and can change. The live figures are always on each model page and the pricing page. All three also support reasoning, function calling with parallel tool calls, and web search. Seed 2.1 Turbo includes web search at no separate charge, while Kimi and DeepSeek bill a small per-search fee.
Seed 2.1 Turbo
ByteDance's newest coding and agent model. It is the most affordable of the three and the only one with flat per-token pricing across its full 256K context, so long-context requests never jump to a higher rate. It reasons by default, calls tools, returns strict JSON, and reads images and video, which makes it a strong fit for cost-sensitive coding agents and multimodal work like reading screenshots, diagrams, and UI. See the Seed 2.1 Turbo model page.
Kimi K2.7 Code
Moonshot's agentic coding model, also 256K context with image and video input. Its reasoning is always on and it has built-in web search, so it is a good pick when your agent needs live information as part of the coding loop. See the Kimi K2.7 Code model page.
DeepSeek V4 Pro
The context-window leader here at 1M tokens, which suits very large codebases and long documents in a single request. It is text only, with no image or video input, and priced above Seed 2.1 Turbo, so choose it when raw context length matters more than multimodal input or the lowest price. See the DeepSeek V4 Pro model page.
Which one to pick
- Lowest cost and multimodal: Seed 2.1 Turbo. The cheapest input and output of the three, flat pricing across the full context, and it reads images and video.
- Live information in the loop: Kimi K2.7 Code, for its always-on reasoning and native web search.
- Largest context: DeepSeek V4 Pro, for 1M-token codebases and documents when text only is fine.
How to call them
All three use the same endpoint. Swap the model field to switch:
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": "Explain and fix the bug in this function."}]
}'Use kimi-k2-7-code or deepseek-v4-pro as the model id for the other two. Each also works on /v1/responses, /v1/messages, and the Gemini-compatible route.
Frequently asked questions
Which is the cheapest?
Seed 2.1 Turbo has the lowest input and output token prices of the three, and its rate stays flat across the full 256K context.
Which has the largest context window?
DeepSeek V4 Pro, at 1M tokens. Seed 2.1 Turbo and Kimi K2.7 Code both offer 256K.
Which support image and video input?
Seed 2.1 Turbo and Kimi K2.7 Code accept text, image, and video. DeepSeek V4 Pro is text only.
Do they all support tools and JSON output?
Yes. All three do function calling with parallel tool calls and can return strict JSON that matches a schema you provide.
Try any of them in the playground, or read the API docs.
