Llama 3.3 70B vs Llama 4 Maverick
Compare Meta (via Together AI) and Meta (via Together AI) AI models
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Llama 3.3 70B
Llama 4 Maverick
Cost Differences
Llama 4 Maverick costs less than Llama 3.3 70B
Feature Comparison
| Feature | Llama 3.3 70B | Llama 4 Maverick |
|---|---|---|
| Provider | Meta (via Together AI) | Meta (via Together AI) |
| Input Price | $0.88/1M tokens | $0.27/1M tokens |
| Output Price | $0.88/1M tokens | $0.85/1M tokens |
| Context Window | 131,072 tokens | 1,000,000 tokens |
| Max Output | 4,096 tokens | 65,536 tokens |
| Category | standard | flagship |
| Capabilities | textcode | textvisioncode |
| Release Date | 12/6/2024 | 4/5/2025 |
Llama 3.3 70B vs Llama 4 Maverick: Which Should You Choose?
Choosing between Llama 3.3 70B and Llama 4 Maverick depends on your priorities: cost efficiency, context length, or raw capability. Llama 4 Maverick is the more affordable option at $0.27/1M input tokens — 69% cheaper than Llama 3.3 70B. Meanwhile, Llama 4 Maverick offers a significantly larger context window at 1,000,000 tokens vs 131,072 for Llama 3.3 70B.
These models target different tiers: Llama 3.3 70B is a standard model while Llama 4 Maverick is flagship. This means they're optimized for different workloads. Llama 4 Maverick targets more demanding workloads, while Llama 3.3 70B provides a cost-effective option for everyday tasks.
Output costs matter too. Llama 3.3 70B charges $0.88/1M output tokens vs $0.85 for Llama 4 Maverick. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. Llama 4 Maverick has the edge here at $0.85/1M output tokens.
Multimodal capabilities: Llama 4 Maverick supports vision (image inputs) while Llama 3.3 70B is text-only. If your application needs image understanding, this narrows your choice.
Best Use Cases
Choose Llama 3.3 70B when:
- • You're already using Meta (via Together AI)'s API ecosystem
Choose Llama 4 Maverick when:
- • Budget is a primary concern
- • You need a larger context window (1,000,000 tokens)
- • You need more capabilities (vision)
- • You need longer outputs (up to 65,536 tokens)
- • You're already using Meta (via Together AI)'s API ecosystem
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
Llama 3.3 70B (Meta (via Together AI))
Llama 4 Maverick (Meta (via Together AI))
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