Model Comparison → Meta
Llama 4 Maverick
Llama 4 Maverick — Meta's most capable open-weight model with 1M token context.
✓ Vision✓ Tool use✗ Prompt caching✗ ReasoningFast
Pricing (verified 2026-08-19)
| Type | Price / 1M tokens | Notes |
|---|---|---|
| Input | $0.27 | Per 1M input tokens |
| Output | $0.85 | Per 1M output tokens |
Source: Meta official pricing page · Last verified 2026-08-19
Context Window
1M tokens
≈ 750K words · 3 pages of text
Llama 4 Maverick competes with GPT-5.4 on benchmarks at a fraction of the cost. At $0.27/M input via Together AI, it's the strongest open-weight model for high-quality generation.
Best for
- High-volume production inference needing GPT-4+ quality
- Teams with GPU infrastructure for self-hosting
- Long-context (up to 1M token) research tasks
- Fine-tuning on proprietary data
Not ideal for
- Real-time latency-critical apps (MoE routing adds overhead)
- Teams without the capacity to manage open-weight deployment
Real cost scenarios
| Scenario | Est. monthly cost | Breakdown |
|---|---|---|
| Content generation — 100k docs/month at 3k tokens each | $81 | 300M input at $0.27/M = $81 |
| Self-hosted on 8× A100 80GB cluster (RunPod) | $14,600 | $2.49/hr × 730hr × 8 GPUs = unlimited tokens |
Estimates with typical token distributions. Use the Prompt Cost Calculator for your exact workload.
How to cut costs on Llama 4 Maverick
- At $0.27/M, Llama 4 Maverick is 9× cheaper than GPT-5.4 on input. For GPT-4-class tasks at scale, this is the first model to evaluate.
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Frequently Asked Questions
What is Llama 4 Maverick vs Llama 4 Scout?
Maverick (400B total, 17B active) is larger and more capable than Scout (109B total, 17B active). Both use MoE architecture so they run at similar speeds. Maverick benchmarks closer to GPT-5.4; Scout is closer to GPT-5 mini — but both are dramatically cheaper.
Pricing verified 2026-08-19 from Meta official pricing. All prices in USD per 1M tokens. See methodology and price changelog.