Last refreshed 2026-09-18. Next refresh: weekly.
Why use DeepSeek Coder 1.3B on Fireworks AI?
Fireworks AI offers DeepSeek Coder 1.3B with pay-as-you-go pricing at $0.10/1M input tokens. Fireworks AI offers a generative AI platform as a service, focusing on rapid product iteration and cost-efficient AI deployment.
Setup recipe
Python + curlpip install openaiexport FIREWORKS_API_KEY=...import os
from openai import OpenAI
client = OpenAI(
api_key=os.environ["FIREWORKS_API_KEY"],accounts/fireworks/models/deepseek-coder-1b-baseRequest example
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-1b-base",
messages=[{"role": "user", "content": "Hello"}]
)
print(response.choices[0].message.content)Gotchas
- Use provider model ID "accounts/fireworks/models/deepseek-coder-1b-base", not the LLMReference slug "deepseek-coder-1.3b".
- Fireworks model IDs use "accounts/fireworks/models/{model-name}" format, e.g. "accounts/fireworks/models/llama4-scout-instruct-basic" or "accounts/fireworks/models/deepseek-r1".
- The examples expect FIREWORKS_API_KEY; rename it only if your application config maps the new variable.
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.10 |
| Output tokens | $0.10 |
Capabilities
No model capability flags are currently sourced.
About DeepSeek Coder 1.3B
DeepSeek Coder 1.3B is a robust language model designed for coding tasks, featuring 1.3 billion parameters. It's adept in code generation and completion, trained on an expansive dataset of 2 trillion tokens, primarily consisting of various programming languages and supplemented with English and Chinese natural language data. This extensive training allows the model to excel in tasks like repository-level code completion and project-level tasks, supported by a 16K context window. Instruction-tuned and quantized versions are available, balancing model size with performance, though quantization can affect quality.