Llama 4 Scout vs o3-mini
Compare Meta (via Together AI) and OpenAI AI models
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
Llama 4 Scout
o3-mini
Cost Differences
o3-mini costs more than Llama 4 Scout
Feature Comparison
| Feature | Llama 4 Scout | o3-mini |
|---|---|---|
| Provider | Meta (via Together AI) | OpenAI |
| Input Price | $0.08/1M tokens | $1.10/1M tokens |
| Output Price | $0.30/1M tokens | $4.40/1M tokens |
| Context Window | 10,000,000 tokens | 500,000 tokens |
| Max Output | 32,768 tokens | 65,536 tokens |
| Category | efficient | reasoning |
| Capabilities | textvisioncode | textreasoningcode |
| Release Date | 4/5/2025 | 1/31/2025 |
Llama 4 Scout vs o3-mini: Which Should You Choose?
Choosing between Llama 4 Scout and o3-mini 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 — 93% cheaper than o3-mini. Meanwhile, Llama 4 Scout offers a significantly larger context window at 10,000,000 tokens vs 500,000 for o3-mini.
These models come from different providers — Meta (via Together AI) and OpenAI — which means different API ecosystems, SDKs, rate limits, and terms of service. If you're already integrated with Meta (via Together AI), switching to OpenAIinvolves migration effort beyond just pricing. Factor in your existing infrastructure when deciding.
These models target different tiers: Llama 4 Scout is a efficient model while o3-mini is reasoning. This means they're optimized for different workloads. o3-mini targets more demanding workloads, while Llama 4 Scout provides a cost-effective option for everyday tasks.
Output costs matter too. Llama 4 Scout charges $0.30/1M output tokens vs $4.40 for o3-mini. 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 o3-mini is text-only. If your application needs image understanding, this narrows your choice.
Best Use Cases
Choose Llama 4 Scout when:
- • Budget is a primary concern
- • You need a larger context window (10,000,000 tokens)
- • You're already using Meta (via Together AI)'s API ecosystem
- • You're running high-volume, latency-sensitive workloads
Choose o3-mini when:
- • You need longer outputs (up to 65,536 tokens)
- • You're already using OpenAI's API ecosystem
Try Different Scenarios
Use the calculator below to see how costs change with different usage patterns
Llama 4 Scout (Meta (via Together AI))
o3-mini (OpenAI)
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