Llama 3.3 70B vs Llama 4 Scout
Llama 3.3 70B vs Llama 4 Scout: Llama 4 Scout is cheaper for input-heavy usage ($0.08/M vs $0.88/M input tokens), while Llama 4 Scout is better for long-context tasks (10,000,000 tokens).
Direct answer: choose Llama 4 Scout for lower token spend and choose Llama 4 Scout when your workload needs longer context.
Compare input and output token pricing, context windows, and monthly cost estimates on one page so you can pick the cheaper model fast.
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
Quick Recommendation
Winner for direct API pricing: Llama 4 Scout. At the default workload, Llama 4 Scout saves about $3.27/month ($39.785/year) versus 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
Pros and Caveats at a Glance
Llama 3.3 70B
- • Input pricing: $0.88/M tokens
- • Output pricing: $0.88/M tokens
- • Context window: 131,072 tokens
- • Max output: 4,096 tokens
Watch out for
- • Higher input cost than Llama 4 Scout
- • Higher output cost than Llama 4 Scout
- • Smaller context window than Llama 4 Scout
Llama 4 Scout
- • Input pricing: $0.08/M tokens
- • Output pricing: $0.30/M tokens
- • Context window: 10,000,000 tokens
- • Max output: 32,768 tokens
Watch out for
- • Trade-offs are minor in this matchup.
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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Sign Up for Meta (via Together AI) →Frequently Asked Questions
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What is the context window difference between Llama 3.3 70B and Llama 4 Scout?▼
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