Google Gemini 3 family vs Meta Llama 4 family
Google Gemini 3 family vs Meta Llama 4 family: side-by-side comparison of two foundation models (substrate reference) systems — architecture, taxonomy, license, pricing, MCP/A2A support, and direct edges.
Cost & capability
| Google Gemini 3 family | Meta Llama 4 family | |
|---|---|---|
| Capability band | frontier | frontier |
| Capability composite | 93 | 80 |
| Cost tier | mid | mid |
| $/Mtok input | 1.25 | 0.20 |
| $/Mtok output | 10 | 3.00 |
| Use cases | Scoped Agentic, Code Generation Focused, Analytical Summarization, Memory Augmented Chat | Scoped Agentic, Code Generation Focused, Analytical Summarization, Memory Augmented Chat, Offline Capable |
Where they differ (13)
Rows where both sides have data and the values disagree — the shortlist of dimensions that actually distinguish these two systems.
| Google Gemini 3 family | Meta Llama 4 family | |
|---|---|---|
| Capability composite | 93 | 80 |
| $/Mtok input | 1.25 | 0.20 |
| $/Mtok output | 10 | 3.00 |
| Use cases | Scoped Agentic, Code Generation Focused, Analytical Summarization, Memory Augmented Chat | Scoped Agentic, Code Generation Focused, Analytical Summarization, Memory Augmented Chat, Offline Capable |
| Type | Frontier foundation model family (Gemini 3 Pro / Flash / Nano) | Open-weights frontier model family (Llama 4 Scout / Maverick / Behemoth) |
| Created | 2023-12 (Gemini 1.0); 2024-02 (1.5 Pro); 2024-12 (2.0); 2025-03 (2.5 Pro); 2025-12 (Gemini 3) | 2023-02 (Llama 1); 2023-07 (Llama 2); 2024-04 (Llama 3); 2024-12 (Llama 3.3); 2025-04 (Llama 4) |
| Latest release | Gemini 3 Pro (2025-12), Gemini 3 Flash, Gemini 3 Nano | Llama 4 Scout + Maverick (2025-04); Behemoth in preview as of 2025 |
| Pricing | Pay-per-token (Gemini 3 Pro $1.25/$10 per 1M; Flash $0.30/$2.50); Gemini Advanced ($20/mo consumer); Gemini Enterprise pricing via GCP | Free for self-hosting (Llama community license, <700M MAU); hosted via Together $0.20-$3/M (Maverick); AWS Bedrock + Azure AI consumption |
| Funding | Alphabet (GOOGL) public; ~$2T+ market cap; Google AI capex $75B+ 2025 | Meta (META) public; ~$1.5T market cap; AI infra capex $60-65B 2025 |
| Deployment | Managed cloud (Google AI Studio + GCP Vertex AI); on-prem via Gemini-Distributed-Cloud + Gemma open-weights | Self-hostable (open-weights) + hosted via AWS Bedrock + Azure AI + Together AI + Groq + Fireworks + Replicate + Databricks |
| API surface | REST + gRPC + SDK (Python, Node, Go, Java, .NET, Dart); Google AI Studio + Vertex AI | HTTP via Together / Bedrock / Azure; native via HuggingFace Transformers, vLLM, llama.cpp |
| Optimised for | multimodal reasoning, ultra-long context (10M tokens), GCP-native enterprise deployments | open-weights frontier-tier deployers; cost-efficient inference via MoE; on-prem regulated deployments |
| Anti-fit | Gemini Apps consumer privacy concerns; Vertex consumption pricing complex; weights closed (Gemma is separate open-weights family) | 700M MAU license trigger; not for users wanting weight transparency on dataset (Meta non-disclosing); Behemoth requires extreme GPU (2T MoE) |
At a glance
| Google Gemini 3 family | Meta Llama 4 family | |
|---|---|---|
| Section | Foundation models (substrate reference) | Foundation models (substrate reference) |
| Tier | T1 | T1 |
| Type | Frontier foundation model family (Gemini 3 Pro / Flash / Nano) | Open-weights frontier model family (Llama 4 Scout / Maverick / Behemoth) |
| Created | 2023-12 (Gemini 1.0); 2024-02 (1.5 Pro); 2024-12 (2.0); 2025-03 (2.5 Pro); 2025-12 (Gemini 3) | 2023-02 (Llama 1); 2023-07 (Llama 2); 2024-04 (Llama 3); 2024-12 (Llama 3.3); 2025-04 (Llama 4) |
| Latest release | Gemini 3 Pro (2025-12), Gemini 3 Flash, Gemini 3 Nano | Llama 4 Scout + Maverick (2025-04); Behemoth in preview as of 2025 |
| License | — | Llama 4 community license (Meta-custom; commercial OK <700M MAU) |
| GitHub | — | github.com/meta-llama/llama (combined Llama repos); ~58k stars |
| Pricing | Pay-per-token (Gemini 3 Pro $1.25/$10 per 1M; Flash $0.30/$2.50); Gemini Advanced ($20/mo consumer); Gemini Enterprise pricing via GCP | Free for self-hosting (Llama community license, <700M MAU); hosted via Together $0.20-$3/M (Maverick); AWS Bedrock + Azure AI consumption |
| Funding | Alphabet (GOOGL) public; ~$2T+ market cap; Google AI capex $75B+ 2025 | Meta (META) public; ~$1.5T market cap; AI infra capex $60-65B 2025 |
| Deployment | Managed cloud (Google AI Studio + GCP Vertex AI); on-prem via Gemini-Distributed-Cloud + Gemma open-weights | Self-hostable (open-weights) + hosted via AWS Bedrock + Azure AI + Together AI + Groq + Fireworks + Replicate + Databricks |
| API surface | REST + gRPC + SDK (Python, Node, Go, Java, .NET, Dart); Google AI Studio + Vertex AI | HTTP via Together / Bedrock / Azure; native via HuggingFace Transformers, vLLM, llama.cpp |
| Optimised for | multimodal reasoning, ultra-long context (10M tokens), GCP-native enterprise deployments | open-weights frontier-tier deployers; cost-efficient inference via MoE; on-prem regulated deployments |
| Anti-fit | Gemini Apps consumer privacy concerns; Vertex consumption pricing complex; weights closed (Gemma is separate open-weights family) | 700M MAU license trigger; not for users wanting weight transparency on dataset (Meta non-disclosing); Behemoth requires extreme GPU (2T MoE) |
Taxonomy
| Axis | Google Gemini 3 family | Meta Llama 4 family |
|---|---|---|
| storage | parametric | parametric |
| retrieval | parametric-recall | parametric-recall |
| persistence | parametric-permanent | parametric-permanent |
| update | read-only | read-only |
| unit | weight | weight |
| governance | opaque | opaque |
| conflict | n/a | n/a |
Pros & cons
Google Gemini 3 family
Pros: Largest context window (1M-10M tokens) of frontier tier; native multimodal (single architecture); GCP enterprise distribution; FedRAMP High; Gemma open-weights companion family.
Cons: Smaller LMSYS Arena share than Claude/GPT; consumer Gemini apps less polished than ChatGPT; pricing complexity at Vertex; lags Claude on agentic coding benchmarks.
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.