Last refreshed 2026-07-09. Next refresh: weekly.
Why use CodeLlama 7B on Replicate API?
Replicate API offers CodeLlama 7B 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 across 5 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",
input={"prompt": "Hello"}meta/codellama-7bRequest example
import replicate
# reads REPLICATE_API_TOKEN from env
# meta/codellama-7b format: "owner/model-name" (latest version) or "owner/model-name:version-hash"
output = replicate.run(
"meta/codellama-7b",
input={"prompt": "Hello"}
)
# Output is a list or generator depending on the model
print("".join(output))Gotchas
- Use provider model ID "meta/codellama-7b", not the LLMReference slug "codellama-7b".
- 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 Across Providers
| Provider | Input (per 1M) | Output (per 1M) |
|---|---|---|
| Baseten API | — | — |
| 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
CodeLlama 7B is a specialized code generation model released by Meta on August 24, 2023. With 7 billion parameters, it excels in code completion, infilling, and instruction-following tasks. Built on an optimized transformer architecture, it's designed for both commercial and research applications, particularly in English and various programming languages. The model offers robust capabilities for AI engineers looking to enhance coding workflows or develop code generation applications. More details can be found on the official Hugging Face page .