Last refreshed 2026-07-09. Next refresh: weekly.
Why use CodeLlama 7B Python on Replicate API?
Replicate API offers CodeLlama 7B Python with pay-as-you-go pricing at $0.05/1M input tokens. Replicate is a cloud-based platform that enables users to run machine learning models easily and efficiently.
Compare CodeLlama 7B Python across 4 providers to find the best fit for your use caseSetup recipe
Python + curlpip install replicateexport REPLICATE_API_TOKEN=...import replicate
output = replicate.run(
"meta/codellama-7b-python",
input={"prompt": "Hello"}meta/codellama-7b-pythonRequest example
import replicate
# reads REPLICATE_API_TOKEN from env
# meta/codellama-7b-python format: "owner/model-name" (latest version) or "owner/model-name:version-hash"
output = replicate.run(
"meta/codellama-7b-python",
input={"prompt": "Hello"}
)
# Output is a list or generator depending on the model
print("".join(output))Gotchas
- Use provider model ID "meta/codellama-7b-python", not the LLMReference slug "codellama-7b-python".
- Replicate uses "owner/model-name" format (e.g. "meta/meta-llama-3-8b-instruct") for the latest version, or "owner/model-name:version-sha" to pin to a specific version. The REST endpoint splits owner and model-name into the path: /v1/models/{owner}/{model-name}/predictions.
- The examples expect REPLICATE_API_TOKEN; rename it only if your application config maps the new variable.
Compare CodeLlama 7B Python Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Together AI | $0.20 | $0.20 |
| Fireworks AI | $0.20 | $0.20 |
| Microsoft Foundry | $0.52 | $0.67 |
| Replicate API | $0.05 | $0.25 |
Pricing
| Type | Price (per 1M) |
|---|---|
| Input tokens | $0.05 |
| Output tokens | $0.25 |
Capabilities
About CodeLlama 7B Python
CodeLlama 7B Python is a specialized variant of Meta's CodeLlama family, designed for Python programming tasks. With 7 billion parameters, it excels in code completion, infilling, and instruction following. The model utilizes an optimized auto-regressive transformer architecture and has been trained on diverse programming tasks. It's suitable for both commercial and research applications, offering AI engineers a powerful tool for enhancing productivity in Python-centric environments. For more details, visit the model's page on Hugging Face .