Capabilities & Performance
- SOTA multi-turn agent coding performance
- Wholesale tier discount down to $0.429/M input, $0.857/M output
DeepSeek next-gen MoE reasoning flagship for complex architectural design, autonomous coding loops, and math proofs.
Params
MoE 256K
Context
256K
Max Output
64K
| Lane | Public Rate | Cached |
|---|---|---|
| Realtime API | $0.56 / $1.11 | $0.111 |
| Batch Queue | Batch rates available on rollout | $0.111 |
Prices per 1M tokens. Cached prompt rate applies on prefix hits.
from openai import OpenAI
client = OpenAI(
base_url="https://api.batchin.tech/v1",
api_key="BATCHIN_API_KEY"
)
resp = client.chat.completions.create(
model="deepseek-v4-pro",
messages=[{"role": "user", "content": "Benchmark system architecture performance and cost profile."}]
)
print(resp.choices[0].message.content)import OpenAI from "openai";
const client = new OpenAI({
baseURL: "https://api.batchin.tech/v1",
apiKey: process.env.BATCHIN_API_KEY,
});
const resp = await client.chat.completions.create({
model: "deepseek-v4-pro",
messages: [{ role: "user", content: "Benchmark system architecture performance and cost profile." }],
});
console.log(resp.choices[0]?.message?.content);curl https://api.batchin.tech/v1/chat/completions \
-H "Authorization: Bearer $BATCHIN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "deepseek-v4-pro",
"messages": [{"role":"user","content":"Benchmark system architecture performance and cost profile."}]
}'High-throughput, ultra-low latency DeepSeek model optimized for rapid tool calls and high-frequency agent loops.
Alibaba flagship reasoning model with native 1M context window and state-of-the-art benchmark capabilities.
Zhipu AI flagship model with upgraded reasoning, deep tool invocation capabilities, and Chinese enterprise alignment.