Llama 3.3 70B vs Llama 4 Scout
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 Scout
Cost Differences
Llama 4 Scout costs less than Llama 3.3 70B
Feature Comparison
| Feature | Llama 3.3 70B | Llama 4 Scout |
|---|---|---|
| Provider | Meta (via Together AI) | Meta (via Together AI) |
| Input Price | $0.88/1M tokens | $0.08/1M tokens |
| Output Price | $0.88/1M tokens | $0.30/1M tokens |
| Context Window | 131,072 tokens | 10,000,000 tokens |
| Max Output | 4,096 tokens | 32,768 tokens |
| Category | standard | efficient |
| Capabilities | textcode | textvisioncode |
| Release Date | 12/6/2024 | 4/5/2025 |
Llama 3.3 70B vs Llama 4 Scout: Which Should You Choose?
Choosing between Llama 3.3 70B and Llama 4 Scout depends on your priorities: cost efficiency, context length, or raw capability. Llama 4 Scout is the more affordable option at $0.08/1M input tokens — 91% cheaper than Llama 3.3 70B. Meanwhile, Llama 4 Scout offers a significantly larger context window at 10,000,000 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 Scout is efficient. This means they're optimized for different workloads. Llama 4 Scout 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 $0.30 for Llama 4 Scout. For generation-heavy workloads (content creation, code generation, summarization), output pricing often dominates your bill. Llama 4 Scout has the edge here at $0.30/1M output tokens.
Multimodal capabilities: Llama 4 Scout 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 Scout when:
- • Budget is a primary concern
- • You need a larger context window (10,000,000 tokens)
- • You need more capabilities (vision)
- • You need longer outputs (up to 32,768 tokens)
- • You're already using Meta (via Together AI)'s API ecosystem
- • You're running high-volume, latency-sensitive workloads
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 Scout (Meta (via Together AI))
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