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Tools/StarCoder vs Llama 3
StarCoder

StarCoder

open-source-model
vs
Llama 3

Llama 3

open-source-model

StarCoder vs Llama 3 — Comparison

Overview
What each tool does and who it's for

StarCoder

We’re on a journey to advance and democratize artificial intelligence through open source and open science.

The model was trained on GitHub code as well as additional selected data sources such as Arxiv and Wikipedia. As such it is not an instruction model and commands like "Write a function that computes the square root." do not work well. Here are some examples to get started with the model. You can find a script for fine-tuning in StarCoder2's GitHub repository. First, make sure to install transformers from source: The pretraining dataset of the model was filtered for permissive licenses and code with no license only. Nevertheless, the model can generate source code verbatim from the dataset. The code's license might require attribution and/or other specific requirements that must be respected. We provide a search index that let's you search through the pretraining data to identify where generated code came from and apply the proper attribution to your code. The model has been trained on source code from 600+ programming languages. The predominant language in source is English although other languages are also present. As such the model is capable to generate code snippets provided some context but the generated code is not guaranteed to work as intended. It can be inefficient, contain bugs or exploits. See the paper for an in-depth discussion of the model limitations. The model is licensed under the BigCode OpenRAIL-M v1 license agreement. You can find the full agreement here.

Llama 3

Discover Llama 4

Based on the provided social mentions, users view Llama 3 as a capable and accessible open-source model that performs well in various applications. The model demonstrates strong technical performance, with Llama 3.2 3B achieving ~85% on SimpleQA benchmarks when paired with research APIs, and showing 40% higher structural stability compared to GPT-2 in manifold audits. Users particularly appreciate its versatility for local deployment, experimenting with multi-agent systems, and research applications without requiring cloud APIs or fine-tuning. The sentiment suggests Llama 3 is seen as a solid, cost-effective alternative to proprietary models, especially for developers building autonomous AI systems and conducting research experiments.

Key Metrics
—
Avg Rating
—
0
Mentions (30d)
13
2,050
GitHub Stars
29,294
192
GitHub Forks
3,524
—
npm Downloads/wk
—
—
PyPI Downloads/mo
—
Community Sentiment
How developers feel about each tool based on mentions and reviews

StarCoder

0% positive100% neutral0% negative

Llama 3

0% positive100% neutral0% negative
Pricing

StarCoder

tiered

Llama 3

tieredFree tier

Pricing found: $0.19, $0.49, $0.19, $0.49, $0.19/mtok

Features

Only in StarCoder (6)

bigcode/the-stack-v2-train-full-ids💫 StarCoder2StarCoder 2 and The Stack v2: The Next GenerationEfficient Training of Language Models to Fill in the MiddleFlashAttention: Fast and Memory-Efficient Exact Attention with IO-AwarenessLongformer: The Long-Document Transformer

Only in Llama 3 (6)

Latest Llama modelsLlama 4Llama 3How Stoque is using LlamaHow Shopify is using Llama97.7%
Developer Ecosystem
29
GitHub Repos
12
1,804
GitHub Followers
10,591
20
npm Packages
20
—
HuggingFace Models
40
—
SO Reputation
—
Pain Points
Top complaints from reviews and social mentions

StarCoder

No data yet

Llama 3

token cost (1)
Product Screenshots

StarCoder

StarCoder screenshot 1StarCoder screenshot 2

Llama 3

Llama 3 screenshot 1Llama 3 screenshot 2Llama 3 screenshot 3Llama 3 screenshot 4
Company Intel
information technology & services
Industry
information technology & services
690
Employees
152,000
$395.7M
Funding
—
Series D
Stage
—
Supported Languages & Categories

StarCoder

AI/ML

Llama 3

AI/MLFinTechDevOpsDeveloper Tools
View StarCoder Profile View Llama 3 Profile