Using DeepSeek V2 Lite Chat on Fireworks AI
Implementation guide · DeepSeek V2 · DeepSeek
ServerlessOpen Weights
Fireworks AI exposes DeepSeek V2 Lite Chat through model ID accounts/fireworks/models/deepseek-v2-lite-chat. Use the setup steps, sourced pricing, capabilities, and official provider links below to validate this route before deployment.
Last refreshed 2026-05-19. Next refresh: weekly.
Quick Start
- 1
- 2Use the Fireworks AI SDK or REST API to call
accounts/fireworks/models/deepseek-v2-lite-chat— see the documentation for request format. - 3
Code Examples
Install
pip install openaiAPI key
FIREWORKS_API_KEYModel ID
accounts/fireworks/models/deepseek-v2-lite-chatFireworks model IDs use "accounts/fireworks/models/{model-name}" format, e.g. "accounts/fireworks/models/llama4-scout-instruct-basic" or "accounts/fireworks/models/deepseek-r1".
import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],
base_url="https://api.fireworks.ai/inference/v1"
)
response = client.chat.completions.create(
model="accounts/fireworks/models/deepseek-v2-lite-chat",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Pricing on Fireworks AI
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.20 |
| Output tokens | $0.20 |
Capabilities
No model capability flags are currently sourced.
About DeepSeek V2 Lite Chat
DeepSeek V2 Lite Chat is DeepSeek's DeepSeek V2 model. It offers a 32K-token context window with weights openly available for self-hosting.
Model Specs
Released2024-05-16
Parameters16B
Context32k
ArchitectureMixture of Experts