Llama 4 (Meta) vs LangGraph
Which one should you pick? Here's the full breakdown.
Llama 4 (Meta)
Meta's open-weights flagship family -- Scout (10M context), Maverick (multimodal 400B MoE), Behemoth in preview
LangGraph
LangChain's graph-based framework for building stateful, controllable multi-agent and human-in-the-loop AI workflows
| Category | Llama 4 (Meta) | LangGraph |
|---|---|---|
| Ease of Use | 5.0 | 6.0 |
| Output Quality | 8.5 | 9.0 |
| Value | 9.0 | 8.5 |
| Features | 9.0 | 9.5 |
| Overall | 7.9 | 8.3 |
Pricing Comparison
| Feature | Llama 4 (Meta) | LangGraph |
|---|---|---|
| Free Tier | Yes | Yes |
| Starting Price | $0 | $0 |
Benchmark Head-to-Head
Llama 4 Maverick (17B/400B MoE) benchmarks — LangGraph has no published benchmarks
| Benchmark | Description | Score |
|---|---|---|
| MMLU-Pro | Harder multi-subject reasoning | 80.5% |
| GPQA Diamond | Graduate-level science questions | 69.8% |
| HumanEval | Python code generation | 88% |
| MMMU (multimodal) | 73.4% |
Which Should You Pick?
Pick Llama 4 (Meta) if...
Developers and teams who need a permissively-licensed open-weights model with strong tooling, long context (Scout), or multimodal (Maverick). Safe default choice given the ecosystem.
Visit Llama 4 (Meta)Pick LangGraph if...
- ✓Easier to use (6 vs 5)
Developers building complex, stateful, or human-in-the-loop agent workflows where the logic is genuinely a graph -- loops, branches, approvals, retries. Also the right pick for teams already on LangChain who want serious production tracing and evaluation.
Visit LangGraphOur Verdict
LangGraph edges out Llama 4 (Meta) with a 8.3 vs 7.9 overall score. Both are solid picks, but LangGraph has the advantage in output quality.