CodeLlama 7B

Released
2023-08-24
Last refreshed
2026-10-07
Status
Researched 148d ago
Open weightsCommercial use: restrictedClassificationJSON / Tool use
AI at Meta releases · 11 in the last 12 monthsChangelog →
Specifications
Released
2023-08-24
Context
100K
Parameters
7B
Architecture
Decoder Only
Knowledge cutoff
2022-09
Specialization
general
Openness
Open weights
License
Llama 2 CommunityRestricted
Weights
Available
Code
Unknown
Training
Fine-tuned
Created by

Large-scale open-source AI for social technologies.

Menlo Park, California, United States
Founded 2013
Website
Pricing
Output / 1M
$0.200
Input / 1M
$0.200

Cheapest of 5 routes · Fireworks AI

About

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 .

Overview

CodeLlama 7B is Meta's 7-billion-parameter code-generation model, released August 24, 2023. It is produced by continuing training of Llama 2 7B on approximately 500 billion tokens of code-heavy data. The model supports code completion, fill-in-the-middle (FIM) infilling—predicting code within an existing structure—and natural language to code translation. The listing carries a 100K-token context, so treat it as a long-context hosted listing and verify the selected provider's actual limit before relying on full-window code prompts.

CodeLlama 7B handles multiple programming languages commonly represented in public code repositories, with strength in Python, C, C++, Java, PHP, TypeScript, C#, and Bash. The 7B scale makes it the most lightweight member of the CodeLlama family suitable for IDE integration, local self-hosting, and latency-sensitive inference pipelines. It fits in approximately 14GB VRAM in FP16, enabling single-GPU deployment while still leaving room for extended repository snippets when a host exposes the full 100K row context.

The model is available as open weights on Hugging Face (meta-llama/CodeLlama-7b-hf) under Meta's Code Llama Community License, and is hosted on Together AI, Fireworks AI, Baseten, Azure AI Foundry, and Replicate. Teams needing Python-specific specialization should evaluate CodeLlama 7B Python; those requiring stronger general code capability can scale to CodeLlama 13B or 34B. For new deployments, later code models such as DeepSeek Coder V2 or Qwen3-Coder offer substantially better benchmark performance.

Providers(5)

Compare all 5

Compare API pricing across 5 tracked provider routes for input and output tokens, batch, and cached reads when available.

ProviderInput / 1MOutput / 1MRoute
Fireworks AI$0.200$0.200
Provisioned
Together AI$0.200$0.200
Serverless
Replicate API$0.050$0.250
Serverless
Microsoft Foundry$0.520$0.670
Provisioned
Baseten API--
ServerlessPartial

Available via routers & gateways(6)

Capabilities

Structured Outputs

Benchmark peer barsfor Classification

No task-mapped benchmark peers are available for this model yet.

Migration checks

No linked migration route is available for this model yet.