DeepSeek develops advanced foundation models optimized for computational efficiency and strong generalization across diverse tasks. The architecture incorporates recent advances in transformer-based systems, delivering robust performance in both zero-shot and fine-tuned scenarios. Models are pretrained on rigorously filtered multilingual corpora with specialized optimizations for mathematical reasoning and algorithmic tasks. The inference stack achieves competitive throughput while maintaining low latency, making it suitable for production deployment. Researchers and engineers can leverage these models for tasks ranging from natural language processing to complex analytical problem-solving.
DeepSeek-R1-0528 is a version upgrade of the DeepSeek R1 model. This upgrade has significantly improved the depth of reasoning and inference capabilities of the model by leveraging increased computational resources and introducing algorithmic optimization mechanisms during post-training. DeepSeek-R1-0528 has demonstrated outstanding performance across various benchmark evaluations, including mathematics, programming, and general logic.
Price per 1M input tokens
$1.00
Price per 1M output tokens
$3.00
Release Date
06/16/2025
Context Size
32,768
Quantization
fp4
# Assume openai>=1.0.0
from openai import OpenAI
# Create an OpenAI client with your deepinfra token and endpoint
openai = OpenAI(
api_key="$DEEPINFRA_TOKEN",
base_url="https://api.deepinfra.com/v1/openai",
)
chat_completion = openai.chat.completions.create(
model="deepseek-ai/DeepSeek-R1-0528-Turbo",
messages=[{"role": "user", "content": "Hello"}],
)
print(chat_completion.choices[0].message.content)
print(chat_completion.usage.prompt_tokens, chat_completion.usage.completion_tokens)
# Hello! It's nice to meet you. Is there something I can help you with, or would you like to chat?
# 11 25
Price per 1M input tokens
$1.00
Price per 1M output tokens
$3.00
Release Date
06/3/2025
Context Size
32,768
Quantization
fp4
# Assume openai>=1.0.0
from openai import OpenAI
# Create an OpenAI client with your deepinfra token and endpoint
openai = OpenAI(
api_key="$DEEPINFRA_TOKEN",
base_url="https://api.deepinfra.com/v1/openai",
)
chat_completion = openai.chat.completions.create(
model="deepseek-ai/DeepSeek-V3-0324-Turbo",
messages=[{"role": "user", "content": "Hello"}],
)
print(chat_completion.choices[0].message.content)
print(chat_completion.usage.prompt_tokens, chat_completion.usage.completion_tokens)
# Hello! It's nice to meet you. Is there something I can help you with, or would you like to chat?
# 11 25
DeepSeek's models are a suite of advanced AI systems that prioritize efficiency, scalability, and real-world applicability.
Model | Context | $ per 1M input tokens | $ per 1M output tokens | Actions |
---|---|---|---|---|
DeepSeek-R1 | 160k | $0.45 | $2.15 | |
DeepSeek-R1-0528 | 160k | $0.50 | $2.15 | |
DeepSeek-R1-Turbo | 32k | $1.00 | $3.00 | |
DeepSeek-R1-0528-Turbo | 32k | $1.00 | $3.00 | |
DeepSeek-V3-0324 | 160k | $0.28 | $0.88 | |
DeepSeek-V3 | 160k | $0.38 | $0.89 | |
DeepSeek-V3-0324-Turbo | 32k | $1.00 | $3.00 | |
DeepSeek-Prover-V2-671B | 160k | $0.50 | $2.18 | |
DeepSeek-R1-Distill-Llama-70B | 128k | $0.10 | $0.40 | |
DeepSeek-R1-Distill-Qwen-32B | 128k | $0.075 | $0.15 |