CodeLlama 70B Python
CodeLlama 70B 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 16k context window
- Buyers comparing 4 tracked provider routes
Do not use it for
- Vision or document-understanding workloads
- Family
- Code Llama
- Released
- 2024-01-29
- Context
- 16k
- Parameters
- 70B
- Architecture
- Decoder Only
- Knowledge cutoff
- 2022-09
- Specialization
- general
- Openness
- Open weights
- License
- Llama 2 CommunityCommercial use with conditions
- Training
- finetuned
Large-scale open-source AI for social technologies.
Cheapest of 4 routes · Fireworks AI
About
CodeLlama 70B Python is a specialized AI model by Meta, designed for Python code synthesis and understanding. With 70 billion parameters, it excels in code completion, infilling, and instruction following tasks. The model leverages an optimized transformer architecture and has been fine-tuned with up to 16,000 tokens, making it particularly effective for Python-centric development workflows. While it doesn't support long contexts of 100,000 tokens, it offers powerful capabilities for both commercial and research applications in Python programming environments. More details can be found in the research paper "Code Llama: Open Foundation Models for Code" .
CodeLlama 70B Python is Meta's highest-capacity Python-specialized code model, released as part of the CodeLlama 70B family in early 2024. It has 70 billion parameters and is produced by fine-tuning CodeLlama 70B on Python-specific training data, maximizing Python code generation accuracy. The context window is 16,384 tokens. Like other Python-specific CodeLlama variants, it is optimized for completion and fill-in-the-middle (FIM) infilling rather than instruction following—it operates on code completion prompts and FIM tokens rather than conversational prompts.
At 70 billion parameters, this model represents the highest CodeLlama scale for Python tasks. It outperforms the 7B and 13B Python variants on complex Python generation tasks: larger algorithm implementations, accurate inference of library APIs, and multi-function code blocks. The large parameter count enables better pattern recognition across diverse Python codebases and library usage styles. Serving in FP16 requires approximately 140GB VRAM, typically requiring 2–4 high-memory GPUs.
CodeLlama 70B Python is available as open weights on Hugging Face (meta-llama/CodeLlama-70b-Python-hf) under Meta's Code Llama Community License, and is hosted on Together AI, Fireworks AI, Azure AI Foundry, and Replicate. For instruction-following use with Python code generation, the CodeLlama 70B Instruct variant is more appropriate. For new Python-specialized deployments, Qwen2.5-Coder or Qwen3-Coder models offer better benchmark results with longer context windows.
CodeLlama 70B Python has a 16k-token context window.
CodeLlama 70B Python input tokens at $0.65/1M, output at $2.75/1M.
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 4Compare API pricing across 4 providers for input and output tokens, batch, and cached reads when available.
| Provider | Input / 1M | Output / 1M | Route |
|---|---|---|---|
| Fireworks AI | $0.900 | $0.900 | Provisioned |
| Together AI | $0.900 | $0.900 | Serverless |
| Replicate API | $0.650 | $2.75 | Serverless |
| Microsoft Foundry | $3.78 | $11.34 | Provisioned |
Available via routers & gateways(6)
Azure AI Foundry Model Router
RouterMicrosoft Azure AI Foundry's native model router that uses a trained ML model to route each prompt in real time to the optimal Azure-hosted model, with Balanced/Cost/Quality mode selection and automatic failover.
Helicone
GatewayObservability-first AI gateway with routing, caching, rate limiting, and request tracing; Apache 2.0 open-source core with a managed hosted tier for logging and analytics.
Kong AI Gateway
GatewayMulti-LLM AI gateway built on Kong Gateway 3.x, adding semantic routing, load balancing, guardrails, and MCP traffic analytics as plugins over Kong's existing API management platform.
LiteLLM
GatewayOpen-source Python SDK and proxy server that unifies 100+ LLM APIs behind a single OpenAI-compatible interface, with load balancing, cost tracking, and configurable failover.
OpenRouter
HybridUnified hybrid gateway to 400+ models from 60+ providers via a single OpenAI-compatible API, with optional auto-routing that selects the best model per prompt.
Portkey
GatewayProduction AI gateway routing to 1,600+ LLMs with failover, load balancing, semantic caching, and guardrails; Apache 2.0 core is fully self-hostable with the complete feature set.
Capabilities
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.
Large-scale open-source AI for social technologies.
Cheapest of 4 routes · Fireworks AI