Using DeepSeek Coder V2 Lite Instruct on Fireworks AI
Implementation guide · DeepSeek Coder V2 · DeepSeek
Fireworks AI exposes DeepSeek Coder V2 Lite Instruct through model ID accounts/fireworks/models/deepseek-coder-v2-lite-instruct. 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-coder-v2-lite-instruct— see the documentation for request format. - 3
Code Examples
pip install openaiFIREWORKS_API_KEYaccounts/fireworks/models/deepseek-coder-v2-lite-instructFireworks 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-coder-v2-lite-instruct",
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 Coder V2 Lite Instruct
DeepSeek Coder V2 Lite Instruct is DeepSeek's DeepSeek Coder V2 model focused on code generation and software engineering. It offers a 128K-token context window with weights openly available for self-hosting.