DeepSeek-V4-Flash is a streamlined open-source Mixture-of-Experts model optimized for fast, cost-efficient inference while preserving strong reasoning and coding performance at 1M token context scale. It leverages the same hybrid attention innovations as Pro but is tuned for lower latency and higher throughput in real-time applications. It delivers near-Pro reasoning quality under sufficient compute budget, making it ideal for interactive agents and high-volume production workloads.
Provider: All DeepSeek models | Fireworks AI
https://api.fireworks.ai/inference/v1/chat/completionsInstall: pip install openai
from openai import OpenAI
client = OpenAI(
api_key="your-fireworks-api-key",
base_url="https://api.fireworks.ai/inference/v1",
)
response = client.chat.completions.create(
model="accounts/fireworks/models/deepseek-v4-flash",
messages=[
{"role": "user", "content": "Hello, how are you?"},
],
max_tokens=1024,
temperature=0.7,
)
print(response.choices[0].message.content)Additional examples: Basic invoke, Streaming
| Parameter | Type | Description |
|---|---|---|
| max_tokens | integer | Maximum tokens to generate. (≥1) |
| temperature | float | Controls randomness. (0–2) Default: 0.7. |
| top_p | float | Nucleus sampling threshold. (0–1) Default: 1. |
| stream | boolean | Stream response chunks as they are generated. Default: false. |
| stop | string | Stop sequence or array of stop sequences. |
Pay per token for public open models without managing GPU deployments.
Use OpenAI-compatible client libraries by changing the API base URL.