Llama vs Llama 3

Llama

Fine-tuning

Llama 3

Writing

Tagline

Llama

Meta's open-weight LLM family covering 1B mobile models up to 405B frontier and natively multimodal 10M-context Llama 4 variants.

Llama 3

Meta's open-weights LLM family that put serious frontier-adjacent models in everyone's hands.

Pricing

Llama

Freemium· Basic: $15 · Pro: $30 · Enterprise: $100

Llama 3

Free· Weights free under Meta Llama Community License; inference cost via self-hosting or 3rd-party providers

Lowest paid tier

Llama

$15 · Basic

captured 2026-08-10

Llama 3

—

Free trial

Llama

Yes

Llama 3

Yes

API

Llama

Yes

Llama 3

Not listed

Platforms

Llama

api

Llama 3

cli

Open source

Llama

Yes

Llama 3

Yes

Model used

Llama

Llama 4 (Maverick, Scout), Llama 3.3/3.2/3.1

Llama 3

Llama 3 / 3.1 (8B, 70B, 405B)

Best for

Llama

Pick Llama if you need open weights you can fine-tune, quantise, and self-host with a license that survives commercial deployment at scale.

Llama 3

Pick Llama 3 if you want a capable, ownable LLM you can fine-tune, quantize, and deploy without a per-token vendor relationship.

Not for

Llama

Skip it if you want a turnkey hosted chatbot with first-class tool use and you don't care about owning the weights.

Llama 3

Skip it if you need a fully managed, SLA-backed first-party API with no DevOps and the latest multimodal frontier features out of the box.

Editorial score

Llama

8.3 / 10

Llama 3

8.3 / 10

Use cases

Llama

self-hosted-llmfine-tuningmultimodal-chatsynthetic-dataedge-inferencerag-backbone

Llama 3

chatlong-context reasoningfine-tuning baselocal inferenceRAG backboneagent workloads

Pros

Llama

• Open weights from 1B edge models to 405B frontier with permissive commercial license
• Natively multimodal Llama 4 with up to 10M-token context
• Runs anywhere: Ollama, vLLM, llama.cpp, Bedrock, Groq, Together
• Aggressive inference pricing on partner clouds (~$0.19-$0.49/M tokens)
• Huge fine-tuning ecosystem and community tooling

Llama 3

• Open weights with permissive commercial use up to 700M MAU
• Massive ecosystem: Ollama, llama.cpp, vLLM, Hugging Face, Unsloth
• Multiple sizes from laptop-friendly 8B to frontier-class 405B
• 128K context in 3.1 generation, strong instruction tuning
• Cheap inference via Groq, Together, Fireworks, Replicate

Cons

Llama

• License is source-available, not OSI-approved (700M MAU clause)
• Tool-use and agentic reasoning still trail GPT-4o and Claude on hardest tasks
• No polished first-party chat product or hosted playground
• Largest models require serious GPU budget to self-host

Llama 3

• No first-party hosted API; you bring your own infrastructure or provider
• License excludes very large platforms (>700M MAU)
• Original 3.0 release was English-heavy; multilingual lags closed models
• 405B variant needs serious GPU budget to self-host

Website

Llama

www.llama.com

Llama 3

llama.meta.com

Editorial score: rule-based, 0–10, from AI-assisted profile inputs (see /methodology) — not a user rating; “—” means unscored. “Not listed” means we have no record of it, not that it is absent. GitHub figures and prices carry the date they were checked or captured; prices are shown as published, unconverted.