- Developers evaluating open MoE models with extreme long-context needs
- Teams comparing Llama 4 Maverick against GPT-5 for coding and reasoning workloads
- Builders who need a permissively licensed open model with multiple size variants
Models
Llama 4
Meta's flagship open MoE model family with Scout (109B, 10M context) and Maverick (400B, rivaling GPT-5 on coding).
7.5K Stars
Llama 4 Community License License
Open sourceLocal firstSelf-hosted
About
Llama 4 overview
Meta's flagship open MoE model family with Scout (109B, 10M context) and Maverick (400B, rivaling GPT-5 on coding).
Compare
How it compares
Evaluate Llama 4 against nearby options by workload fit, license, and deployment model.
FAQ
Questions
What should I check before using Llama 4?
Run your own prompt set across reasoning, coding, latency, context length, and license constraints.
Is Llama 4 open source?
Llama 4 is listed on OpenAgent.bot with Llama 4 Community License based on the current resource metadata. Re-check the official repository, docs, and license before production use.
Tags
Capabilities
Decision brief
JSON
Should you use Llama 4?
- Teams that cannot review the Llama 4 Community License terms before deployment
- Use cases requiring verified multimodal input beyond text-based reasoning
- Verified 2026-06-16
- License: Llama 4 Community License
- Repo: meta-llama/llama-models
- Open-source signal
Deployment
local, self hosted, cloud
Permission surface
shell/files, memory
Decision signals
Local first, Self-hostable
Agent packet
Structured decision data for Llama 4
This packet is the compact machine-readable view agents should use before following source links or taking action.
Capabilities
local inference, inference
Constraints
open source, open weights, self hosted, local first
Deployment
local, self hosted, cloud
Permission surface
shell/files, memory
Recommended workflows
Local or private AI stack
Overview
What Llama 4 does
What it is
Llama 4 is a model in the models category. Meta's flagship open MoE model family with Scout (109B, 10M context) and Maverick (400B, rivaling GPT-5 on coding).
Why it matters
Llama 4 represents Meta's latest open MoE model family, with Scout offering an unprecedented 10M token context window and Maverick rivaling GPT-5 on coding benchmarks, making it a top contender for open model evaluation.
How to evaluate it
Evaluate Llama 4 by starting from the official sources, checking its docs, demo interface surface, and running one narrow workflow before expanding scope. Recorded integrations include GitHub, Hugging Face.
Facts
Known metadata and operating surface
These fields are separated from editorial interpretation so agents can reason over facts and missing checks.
Resource type model
Category Models
Maturity active
Difficulty Unknown
License Llama 4 Community License
Pricing open source
Verified 2026-06-16
Source confidence medium
Risk level elevated
Fit matrix
Where Llama 4 fits in an agent stack
strong
Local or private AI stack
Llama 4 has multiple signals for local or private ai stack, including matching tags, capabilities, category, or positioning.
- Verify hardware requirements, data path, storage, and whether all calls stay in your environment.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial
Coding agent workflow
Llama 4 has at least one signal for coding agent workflow, but should be checked against a real task before adoption.
- Run a small repository change and inspect the diff, tests, and rollback path.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial
Evaluation and observability
Llama 4 has at least one signal for evaluation and observability, but should be checked against a real task before adoption.
- Add one repeatable test case and confirm results can run again in review or CI.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
partial
Memory or RAG workflow
Llama 4 has at least one signal for memory or rag workflow, but should be checked against a real task before adoption.
- Create, update, retrieve, correct, and delete memory or retrieval objects with real data.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
weak
Browser automation
Llama 4 is not primarily positioned for browser automation in the current metadata.
- Run one non-sensitive website task and inspect clicks, waits, retries, and changed URLs.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
weak
Connector or protocol layer
Llama 4 is not primarily positioned for connector or protocol layer in the current metadata.
- Connect one low-risk service, then inspect schemas, auth scope, errors, and logs.
- Confirm official docs, current maintenance, license, and runtime constraints before production use.
Inputs and outputs
What an agent should inspect
Likely inputs
- Repositories, files, issues, terminal output, and test results
- Prompts, messages, documents, images, or model inputs
- Official setup instructions and a small real workflow
Likely outputs
- Diffs, commits, explanations, test results, or review notes
- Scores, traces, regression results, dashboards, or failure cases
- A decision on whether this resource fits the target workflow
Evidence
Sources, claims, and missing checks
Claims are marked separately from source links so future crawlers and reviewers can update them without rewriting the page.
Llama 4 is listed as open source.
License metadata: Llama 4 Community LicenseLlama 4 has a recorded GitHub repository: meta-llama/llama-models.
Resource facts and GitHub source link.Llama 4 supports these recorded deployment modes: local, self hosted, cloud.
OpenAgent decision signal metadata.Llama 4 is tagged with local inference, inference capabilities.
OpenAgent capability taxonomy.- Dedicated docs link is missing.
- Repository freshness has not been recorded.
Next action
How to start evaluating Llama 4
Inspect repository
Check license, recent activity, issues, examples, and security-sensitive code paths.
Open source Compare
Alternatives and nearby resources
Use related resources to compare category fit, license, deployment model, and first-workflow behavior.
FAQ
Common questions about Llama 4
What is Llama 4 used for?
Llama 4 is used as a model for models workflows. The most relevant recorded capabilities are local inference, inference.
Is Llama 4 open source?
Llama 4 is listed as open source with Llama 4 Community License license metadata. Re-check the official repository or source link before production use.
Can agents use Llama 4 directly?
Llama 4 has recorded interfaces such as docs, demo. Agents should prefer the JSON or Markdown profile first, then follow official docs for real execution.
What should I check before production use?
Check source confidence (medium), risk level (elevated), license, maintenance freshness, permission surface, required credentials, and whether the first workflow succeeds in a sandbox.