Meta Llama 4 family vs OpenAI GPT family (GPT-5 / GPT-4o / o3 / o4)

Meta Llama 4 family vs OpenAI GPT family (GPT-5 / GPT-4o / o3 / o4): side-by-side comparison of two foundation models (substrate reference) systems — architecture, taxonomy, license, pricing, MCP/A2A support, and direct edges.

Meta Llama 4 family · OpenAI GPT family (GPT-5 / GPT-4o / o3 / o4)

Recommend between these two →

Cost & capability

Meta Llama 4 familyOpenAI GPT family (GPT-5 / GPT-4o / o3 / o4)
Capability bandfrontierfrontier
Capability composite8095
Cost tiermidmid
$/Mtok input0.201.25
$/Mtok output3.0010
Use casesScoped Agentic, Code Generation Focused, Analytical Summarization, Memory Augmented Chat, Offline CapableScoped Agentic, Code Generation Focused, Analytical Summarization, Memory Augmented Chat

Where they differ (13)

Rows where both sides have data and the values disagree — the shortlist of dimensions that actually distinguish these two systems.

Meta Llama 4 familyOpenAI GPT family (GPT-5 / GPT-4o / o3 / o4)
Capability composite8095
$/Mtok input0.201.25
$/Mtok output3.0010
Use casesScoped Agentic, Code Generation Focused, Analytical Summarization, Memory Augmented Chat, Offline CapableScoped Agentic, Code Generation Focused, Analytical Summarization, Memory Augmented Chat
TypeOpen-weights frontier model family (Llama 4 Scout / Maverick / Behemoth)Frontier foundation model family (GPT-5 / GPT-4o / o3 / o4)
Created2023-02 (Llama 1); 2023-07 (Llama 2); 2024-04 (Llama 3); 2024-12 (Llama 3.3); 2025-04 (Llama 4)2018 (GPT-1); 2020-06 (GPT-3); 2023-03 (GPT-4); 2024-05 (GPT-4o); 2024-09 (o1); 2025-01 (o3); 2025-08 (GPT-5)
Latest releaseLlama 4 Scout + Maverick (2025-04); Behemoth in preview as of 2025GPT-5 (2025-08), o4-mini, GPT-4.1 series
PricingFree for self-hosting (Llama community license, <700M MAU); hosted via Together $0.20-$3/M (Maverick); AWS Bedrock + Azure AI consumptionPay-per-token API (GPT-5 $1.25/$10 per 1M; GPT-4o $2.50/$10; o3 $2/$8); ChatGPT Free + Plus ($20/mo) + Pro ($200/mo) + Team + Enterprise
FundingMeta (META) public; ~$1.5T market cap; AI infra capex $60-65B 2025$57.9B+ total raised; $500B valuation (2025 secondary tender); Microsoft $13B+ strategic investment
DeploymentSelf-hostable (open-weights) + hosted via AWS Bedrock + Azure AI + Together AI + Groq + Fireworks + Replicate + DatabricksManaged-only (OpenAI API + Microsoft Azure OpenAI)
API surfaceHTTP via Together / Bedrock / Azure; native via HuggingFace Transformers, vLLM, llama.cppREST + SDK (Python, TS, Java, Go, .NET); Azure OpenAI variant; Realtime API (WebRTC)
Optimised foropen-weights frontier-tier deployers; cost-efficient inference via MoE; on-prem regulated deploymentsgeneral-purpose reasoning, coding, multimodal, voice/real-time
Anti-fit700M MAU license trigger; not for users wanting weight transparency on dataset (Meta non-disclosing); Behemoth requires extreme GPU (2T MoE)weights closed; data residency limited (US/EU/Asia regions only); rate-limited without enterprise; no open-weights option; Sora video gated

At a glance

Meta Llama 4 familyOpenAI GPT family (GPT-5 / GPT-4o / o3 / o4)
SectionFoundation models (substrate reference) Foundation models (substrate reference)
TierT1 T1
TypeOpen-weights frontier model family (Llama 4 Scout / Maverick / Behemoth) Frontier foundation model family (GPT-5 / GPT-4o / o3 / o4)
Created2023-02 (Llama 1); 2023-07 (Llama 2); 2024-04 (Llama 3); 2024-12 (Llama 3.3); 2025-04 (Llama 4) 2018 (GPT-1); 2020-06 (GPT-3); 2023-03 (GPT-4); 2024-05 (GPT-4o); 2024-09 (o1); 2025-01 (o3); 2025-08 (GPT-5)
Latest releaseLlama 4 Scout + Maverick (2025-04); Behemoth in preview as of 2025 GPT-5 (2025-08), o4-mini, GPT-4.1 series
LicenseLlama 4 community license (Meta-custom; commercial OK <700M MAU)
GitHubgithub.com/meta-llama/llama (combined Llama repos); ~58k stars
PricingFree for self-hosting (Llama community license, <700M MAU); hosted via Together $0.20-$3/M (Maverick); AWS Bedrock + Azure AI consumption Pay-per-token API (GPT-5 $1.25/$10 per 1M; GPT-4o $2.50/$10; o3 $2/$8); ChatGPT Free + Plus ($20/mo) + Pro ($200/mo) + Team + Enterprise
FundingMeta (META) public; ~$1.5T market cap; AI infra capex $60-65B 2025 $57.9B+ total raised; $500B valuation (2025 secondary tender); Microsoft $13B+ strategic investment
DeploymentSelf-hostable (open-weights) + hosted via AWS Bedrock + Azure AI + Together AI + Groq + Fireworks + Replicate + Databricks Managed-only (OpenAI API + Microsoft Azure OpenAI)
API surfaceHTTP via Together / Bedrock / Azure; native via HuggingFace Transformers, vLLM, llama.cpp REST + SDK (Python, TS, Java, Go, .NET); Azure OpenAI variant; Realtime API (WebRTC)
Optimised foropen-weights frontier-tier deployers; cost-efficient inference via MoE; on-prem regulated deployments general-purpose reasoning, coding, multimodal, voice/real-time
Anti-fit700M MAU license trigger; not for users wanting weight transparency on dataset (Meta non-disclosing); Behemoth requires extreme GPU (2T MoE) weights closed; data residency limited (US/EU/Asia regions only); rate-limited without enterprise; no open-weights option; Sora video gated

Taxonomy

AxisMeta Llama 4 familyOpenAI GPT family (GPT-5 / GPT-4o / o3 / o4)
storageparametricparametric
retrievalparametric-recallparametric-recall
persistenceparametric-permanentparametric-permanent
updateread-onlyread-only
unitweightweight
governanceopaqueopaque
conflictn/an/a

Pros & cons

Meta Llama 4 family

Pros: Open weights (community license) — only frontier-tier family runnable on-prem; MoE architecture cheap to serve (17B active params); 10M context (Scout) matches Gemini 3.

Cons: License excludes 700M+ MAU products; dataset opacity; multimodal less mature than GPT-4o / Gemini 3; Behemoth not yet released as of 2025-12.

OpenAI GPT family (GPT-5 / GPT-4o / o3 / o4)

Pros: Most-deployed frontier LLM (800M+ MAU ChatGPT); full multimodal stack (vision + audio + image gen + video gen); largest ecosystem of fine-tunes / RAG / agent integrations; Azure distribution.

Cons: Closed weights; expensive at Pro/o3 tier; legal exposure (multiple ongoing NYT / Authors Guild lawsuits); Sora & advanced features behind waitlists; SWE-bench trails Claude Opus 4.5.

Rows last verified 2026-05-14 / 2026-05-14. Data is CC-BY-4.0 — see how to read this.