Using DeepSeek 67B Chat on Together AI
Implementation guide · DeepSeek · DeepSeek
Together AI exposes DeepSeek 67B Chat through model ID deepseek-67b-chat. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-06-15. Next refresh: weekly.
Quick Start
- 1
- 2Use the Together AI SDK or REST API to call
deepseek-67b-chat— see the documentation for request format. - 3
Code Examples
pip install togetherTOGETHER_API_KEYdeepseek-67b-chatTogether uses "organization/model-name" format, e.g. "meta-llama/Llama-4-Scout-17B-16E-Instruct" or "Qwen/QwQ-32B". See the Together model catalog for the exact ID.
from together import Together
client = Together() # reads TOGETHER_API_KEY from env
response = client.chat.completions.create(
model="deepseek-67b-chat",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Pricing on Together AI
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.90 |
| Output tokens | $0.90 |
Capabilities
About DeepSeek 67B Chat
DeepSeek LLM 67B Chat is a sophisticated language model with 67 billion parameters, leveraging the LLaMA architecture with enhancements such as Grouped-Query Attention across 95 layers. Trained on a vast corpus of 2 trillion tokens in English and Chinese, it excels in tasks like text generation, question answering, and fluent conversation, demonstrating superior performance in reasoning, coding, and mathematics compared to some larger models. Despite its advanced capabilities, the model can exhibit biases from its training data, experience hallucinations, and produce repetitive outputs.