LLM Reference

CodeLlama 7B Python

Released
2023-08-24
Last refreshed
2026-06-01
Status
Researched 12d ago
Open WeightsCommercial use with conditionsClassificationJSON / Tool use

CodeLlama 7B Python is worth evaluating for classification and json / tool use when its provider route and context window match the workload.

Use it for

  • Teams evaluating classification and json / tool use
  • Workloads that can use a 100k context window
  • Buyers comparing 4 tracked provider routes

Do not use it for

  • Vision or document-understanding workloads
Specifications
Released
2023-08-24
Context
100k
Parameters
7B
Architecture
Decoder Only
Knowledge cutoff
2022-09
Specialization
general
Openness
Open weights
License
Llama 2 CommunityCommercial use with conditions
Training
finetuned
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 4 routes · Fireworks AI

About

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 .

CodeLlama 7B Python is a Python-specialized variant of Meta's CodeLlama 7B, released August 24, 2023. It is produced by further fine-tuning CodeLlama 7B on approximately 100 billion additional Python-specific tokens, sharpening its Python code completion, generation, and fill-in-the-middle (FIM) infilling accuracy. This LLMReference seed row lists 7 billion parameters and a 100K-token context, making it the long-context Python-specific 7B entry in the current model data.

Unlike CodeLlama 7B Instruct, the Python variant is not instruction-tuned for natural language prompts; it operates as a completion and FIM model that expects code context rather than conversational instructions. This makes it appropriate for IDE autocomplete backends, code synthesis pipelines, and batch code generation tasks where Python is the exclusive or primary language. Before relying on the full 100K context for repository-scale Python prompts, verify the limit on the provider row selected for deployment.

CodeLlama 7B Python is available as open weights on Hugging Face (meta-llama/CodeLlama-7b-Python-hf) under Meta's Code Llama Community License, and is hosted on Together AI, Fireworks AI, Azure AI Foundry, and Replicate. The 13B Python variant offers higher Python generation accuracy at greater compute cost. For new deployments, Qwen2.5-Coder or Qwen3-Coder family models offer significantly improved Python benchmarks.

CodeLlama 7B Python has a 100k-token context window.

CodeLlama 7B Python input tokens at $0.05/1M, output at $0.25/1M.

Top use-case fit

Classification

Included by capability and metadata signals in the decision map.

JSON / Tool use

Included by capability and metadata signals in the decision map.

Provider price ladder

Compare all 4

Compare API pricing across 4 providers 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

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.