What are the hardware requirements for CodeLlama 34B Python Hf?

CodeLlama 34B Python Hf requires approximately 67.5 GB of VRAM and supports a context window of 16K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed CodeLlama 34B Python Hf and how large is it?

CodeLlama 34B Python Hf is developed by codellama, a model with 34b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does CodeLlama 34B Python Hf perform on standard benchmarks?

CodeLlama 34B Python Hf has the following published scores: MMLU 34.79, HumanEval (Python) 53.29. Compare against reference models on this page or on the LLM Explorer leaderboards.

CodeLlama 34B Python Hf by codellama — VRAM 67.5GB, 16K context

Name: CodeLlama 34B Python Hf
Author: codellama

CodeLlama 34B Python Hf is an open-source language model by codellama. Features: 34b LLM, VRAM: 67.5GB, Context: 16K, License: llama2, Code Generating, HF Score: 40.3, LLM Explorer Score: 0.14, Arc: 40.2, HellaSwag: 36.8, MMLU: 34.8, TruthfulQA: 44.3, WinoGrande: 71.2, GSM8K: 14.3, HumanEval: 53.3.

Arxiv:2308.12950 Code Codegen Deploy:azure Endpoints compatible Llama Llama2 Pytorch Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/codellama/CodeLlama-34b-Python-hf

CodeLlama 34B Python Hf Benchmarks

ARC: 40.19 vs 96.7 (so35)^-58.4%

HellaSwag: 36.82 vs 95.3 (gpt4)^-61.4%

MMLU: 34.79 vs 88.3 (so35)^-60.6%

TruthfulQA: 44.28 vs 59 (gpt4)^-24.9%

WinoGrande: 71.19 vs 87.5 (gpt4)^-18.6%

GSM8K: 14.33 vs 96.4 (so35)^-85.1%

HumanEvalA: 33.87

Python Eva: 53.29 vs 92 (so35)^-42.1%

Java Eval: 39.46

Javascript: 44.72

CPP Eval: 39.09

PHP Eval: 39.78

Julia Eval: 31.37

D Eval: 17.29

Lua Eval: 31.9

R Eval: 22.35

Racket Eva: 13.19

Rust Eval: 39.67

Swift Eval: 34.3

LLME Score: 0.14295

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

CodeLlama 34B Python Hf (codellama/CodeLlama-34b-Python-hf)

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CodeLlama 34B Python Hf Parameters and Internals

Model Type

text generation

Use Cases

Areas:

Commercial, Research

Applications:

Code synthesis and understanding, Python programming

Primary Use Cases:

Python specialist, Code completion

Limitations:

Use in languages other than English, Potentially objectionable content

Training Details

Hardware Used:

A100-80GB

Model Architecture:

Auto-regressive language model with optimized transformer architecture.

Responsible Ai Considerations

Mitigation Strategies:

Developers should perform safety testing and tuning tailored to their specific applications of the model.

Input Output

Input Format:

Text only

Output Format:

Text only

LLM Name	CodeLlama 34B Python Hf
Repository 🤗	https://huggingface.co/codellama/CodeLlama-34b-Python-hf
Model Size	34b
Required VRAM	67.5 GB
Updated	2026-04-25
Maintainer	codellama
Model Type	llama
Model Files	9.8 GB: 1-of-7 9.7 GB: 2-of-7 9.7 GB: 3-of-7 9.7 GB: 4-of-7 9.7 GB: 5-of-7 9.7 GB: 6-of-7 9.2 GB: 7-of-7 9.8 GB: 1-of-7 9.7 GB: 2-of-7 9.7 GB: 3-of-7 9.7 GB: 4-of-7 9.7 GB: 5-of-7 9.7 GB: 6-of-7 9.4 GB: 7-of-7
Supported Languages	code
Generates Code	Yes
Model Architecture	LlamaForCausalLM
License	llama2
Context Length	16384
Model Max Length	16384
Transformers Version	4.32.0.dev0
Tokenizer Class	CodeLlamaTokenizer
Beginning of Sentence Token	<s>
End of Sentence Token	</s>
Unk Token	<unk>
Vocabulary Size	32000
Torch Data Type	bfloat16

Quantized Models of the CodeLlama 34B Python Hf

Model	Likes	Downloads	VRAM
CodeLlama 34B Python Fp16	14	1377	67 GB
CodeLlama 34B Python Hf GGUF	1	787	12 GB

Best Alternatives to CodeLlama 34B Python Hf

Best Alternatives	Context / RAM	Downloads	Likes
...gpt 32K Codellama 34B Instruct	32K / 67.5 GB	502	2
CodeLlama 34B Instruct Hf	16K / 67.5 GB	21226	304
ReflectionCoder CL 34B	16K / 67.6 GB	8479	0
CodeLlama 34B Instruct Hf	16K / 1.4 GB	6	3
Speechless Codellama 34B V2.0	16K / 67.5 GB	1019	17
Phind CodeLlama 34B V2	16K / 67.5 GB	1566	833
Phind CodeLlama 34B V1	16K / 67.5 GB	1172	320
Phind CodeLlama 34B Python V1	16K / 67.5 GB	1229	252
CodeLlama 34B Hf	16K / 67.5 GB	1376	2
Tora Code 34B V1.0	16K / 67.5 GB	1015	14

Note: green Score (e.g. "73.2") means that the model is better than codellama/CodeLlama-34b-Python-hf.

Rank the CodeLlama 34B Python Hf Capabilities

🆘 Have you tried this model? Rate its performance. This feedback would greatly assist ML community in identifying the most suitable model for their needs. Your contribution really does make a difference! 🌟

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

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Release v20260328a

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CodeLlama 34B Python Hf by codellama