Llama 4 Maverick vs GPT-5.2
Detailed pricing comparison and cost analysis.
Updated August 2026
Cost Simulator
| Feature | Llama 4 Maverick | GPT-5.2 |
|---|---|---|
| Provider | Meta | OpenAI |
| Input Price (1M) | $0.20 | $1.75 |
| Output Price (1M) | $0.80 | $14.00 |
| Context Window | 1,000,000 | 128,000 |
Verdict
Llama 4 Maverick costs $0.20 per 1M input tokens and $0.80 per 1M output tokens. GPT-5.2 costs $1.75 per 1M input tokens and $14.00 per 1M output tokens. Llama 4 Maverick is 89% cheaper on input tokens than GPT-5.2. For output tokens, Llama 4 Maverick is the more affordable option at $0.80/1M vs $14.00.
On context window, Llama 4 Maverick supports 1,000,000 tokens — meaning it can fit more conversation history, documents, or code in a single request. This matters for RAG pipelines, long document analysis, and agentic workflows where context builds up over many turns.
When to choose Llama 4 Maverick
- ✓ You need the lowest input token cost ($ 0.20/1M)
- ✓ Your workload is output-heavy — Llama 4 Maverick generates text cheaper
- ✓ You need a larger context window (1,000,000 tokens)
- ✓ You are already integrated with Meta
When to choose GPT-5.2
- ✓ 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-5.2? ▼
Llama 4 Maverick is cheaper on input tokens at $0.20/1M vs $1.75/1M for GPT-5.2 — a 89% saving.
What is the context window of Llama 4 Maverick vs GPT-5.2? ▼
Llama 4 Maverick has a 1,000,000-token context window. GPT-5.2 has a 128,000-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-5.2? ▼
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.