DeepSeek 67B Chat on Together AI

DeepSeek · DeepSeek

ServerlessOpen Weights

Last refreshed 2026-06-15. Next refresh: weekly.

Why use DeepSeek 67B Chat on Together AI?

Together AI offers DeepSeek 67B Chat with pay-as-you-go pricing at $0.90/1M input tokens. Together AI is a platform for running open-source and proprietary LLMs with fast serverless and dedicated endpoints at competitive inference pricing.

Input / 1M
$0.90
Output / 1M
$0.90
Cache
Not sourced
Batch
Not sourced

Setup recipe

Python + curl
Install
pip install together
Auth
export TOGETHER_API_KEY=...
Call
from together import Together
client = Together()  # reads TOGETHER_API_KEY from env
response = client.chat.completions.create(
    model="deepseek-67b-chat",
Model ID
deepseek-67b-chat

Request example

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)

Gotchas

  • Together 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.
  • The examples expect TOGETHER_API_KEY; rename it only if your application config maps the new variable.

Pricing

TypePrice (per 1M)
Input tokens$0.90
Output tokens$0.90

Capabilities

Structured Outputs

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.

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Model Specs

Released2023-11-29
Parameters67B
Context4k
ArchitectureDecoder Only
Knowledge cutoff2023-05

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