GPT-5.3 Codex vs Llama 4 Scout
Compare OpenAI and Meta (via Together AI) AI models
Cost Comparison (1000 input + 500 output tokens, 100 requests/day)
GPT-5.3 Codex
Llama 4 Scout
Cost Differences
Llama 4 Scout costs less than GPT-5.3 Codex
Feature Comparison
| Feature | GPT-5.3 Codex | Llama 4 Scout |
|---|---|---|
| Provider | OpenAI | Meta (via Together AI) |
| Input Price | $1.75/1M tokens | $0.08/1M tokens |
| Output Price | $14.00/1M tokens | $0.30/1M tokens |
| Context Window | 256,000 tokens | 10,000,000 tokens |
| Max Output | 32,768 tokens | 32,768 tokens |
| Category | coding | efficient |
| Capabilities | textcode | textvisioncode |
| Release Date | 3/1/2026 | 4/5/2025 |
GPT-5.3 Codex vs Llama 4 Scout: Which Should You Choose?
Choosing between GPT-5.3 Codex 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 — 95% cheaper than GPT-5.3 Codex. Meanwhile, Llama 4 Scout offers a significantly larger context window at 10,000,000 tokens vs 256,000 for GPT-5.3 Codex.
These models come from different providers — OpenAI and Meta (via Together AI) — which means different API ecosystems, SDKs, rate limits, and terms of service. If you're already integrated with OpenAI, switching to Meta (via Together AI)involves migration effort beyond just pricing. Factor in your existing infrastructure when deciding.
These models target different tiers: GPT-5.3 Codex is a coding model while Llama 4 Scout is efficient. This means they're optimized for different workloads. Llama 4 Scout targets more demanding workloads, while GPT-5.3 Codex provides a cost-effective option for everyday tasks.
Output costs matter too. GPT-5.3 Codex charges $14.00/1M 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 GPT-5.3 Codex is text-only. If your application needs image understanding, this narrows your choice.
Best Use Cases
Choose GPT-5.3 Codex when:
- • You're already using OpenAI'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'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
GPT-5.3 Codex (OpenAI)
Llama 4 Scout (Meta (via Together AI))
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