Llama 4 Maverick vs GPT-4.1
Detailed pricing comparison and cost analysis.
Updated September 2026
Cost Simulator
| Feature | Llama 4 Maverick | GPT-4.1 |
|---|---|---|
| Provider | Meta | OpenAI |
| Input Price (1M) | $0.20 | $2.00 |
| Output Price (1M) | $0.80 | $8.00 |
| Context Window | 1,000,000 | 1,000,000 |
Verdict
Llama 4 Maverick costs $0.20 per 1M input tokens and $0.80 per 1M output tokens. GPT-4.1 costs $2.00 per 1M input tokens and $8.00 per 1M output tokens. Llama 4 Maverick is 90% cheaper on input tokens than GPT-4.1. For output tokens, Llama 4 Maverick is the more affordable option at $0.80/1M vs $8.00.
On context window, Llama 4 Maverick supports 1,000,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose Llama 4 Maverick
- ✓ You need the lowest input token cost ($ 0.20/1M)
- ✓ Your workload is output-heavy — Llama 4 Maverick generates text cheaper
- ✓ You are already integrated with Meta
When to choose GPT-4.1
- ✓ You are already integrated with OpenAI
Use the calculator above to simulate your specific workload and find the exact break-even point. For most applications, the cheapest model is the one that minimises your total monthly bill given your input-to-output token ratio.
Frequently Asked Questions
Is Llama 4 Maverick cheaper than GPT-4.1? ▼
Llama 4 Maverick is cheaper on input tokens at $0.20/1M vs $2.00/1M for GPT-4.1 — a 90% saving.
What is the context window of Llama 4 Maverick vs GPT-4.1? ▼
Llama 4 Maverick has a 1,000,000-token context window. GPT-4.1 has a 1,000,000-token context window. Llama 4 Maverick supports the larger context, suitable for longer documents and agentic workflows.
Which model is better: Llama 4 Maverick or GPT-4.1? ▼
The best choice depends on your use case. For cost efficiency on input tokens, Llama 4 Maverick is the cheaper option. For maximum context length, Llama 4 Maverick supports 1,000,000 tokens. Use the comparison table above to find the right fit for your workload.