Llama 4 Scout vs GPT-5.2-Codex
A side-by-side comparison of two multimodal models — real specs, pricing, strengths and weaknesses, and a clear verdict on which to choose. Kept current by our agents.
Quick verdict: which should you choose?
Choose Llama 4 Scout if you need
- ✓Choose GPT-5.2-Codex if you need higher intelligence_index performance at 40.1 for complex multimodal tasks.
- ✓Choose GPT-5.2-Codex if you need faster output at 145.81 tokens per second.
- ✓Choose GPT-5.2-Codex if you need strong coding specialization with seamless text-image integration.
- ✓Choose GPT-5.2-Codex if you need proprietary OpenAI integration for reliable enterprise use.
Choose GPT-5.2-Codex if you need
- ✓Choose Llama 4 Scout if you need an extremely large 10M token context window.
- ✓Choose Llama 4 Scout if you need dramatically lower pricing at $0.3 per million tokens.
- ✓Choose Llama 4 Scout if you need open-weight access from Meta for customization.
- ✓Choose Llama 4 Scout if you need strong reasoning over very long text and image sequences.
Verdict
GPT-5.2-Codex leads in intelligence and output speed for multimodal text-image tasks, making it stronger for specialized coding workflows despite its smaller context. Llama 4 Scout counters with a dramatically larger context window and far lower cost, suiting extended sequence reasoning where budget and scale matter most. Neither dominates outright; selection hinges on whether performance metrics or accessibility take priority.
Llama 4 Scout vs GPT-5.2-Codex: side by side
| Spec | Llama 4 Scout | GPT-5.2-Codex | Winner |
|---|---|---|---|
| Intelligence | 10 | 40.1 | GPT-5.2-Codex |
| Output speed | 111 t/s | 146 t/s | GPT-5.2-Codex |
| Output price | $0.30/1M | $14.00/1M | Llama 4 Scout |
| Context | 10000K | 400K | Llama 4 Scout |
| Params | — | — | Tie |
| Provider | Meta | OpenAI | Tie |
Detailed analysis
Intelligence
Winner: GPT-5.2-CodexGPT-5.2-Codex scores 40.1 on the intelligence index compared to Llama 4 Scout's 10. This gap indicates superior capability on complex multimodal reasoning and coding tasks grounded in the provided metrics.
Pricing
Winner: Llama 4 ScoutLlama 4 Scout costs $0.3 per million tokens versus GPT-5.2-Codex at $14 per million. The 46x price advantage makes Llama 4 Scout far more accessible for high-volume usage.
Context Window
Winner: Llama 4 ScoutLlama 4 Scout offers a 10 million token context while GPT-5.2-Codex is limited to 400,000 tokens. This gives Llama 4 Scout a clear edge for processing extremely long multimodal sequences.
Speed
Winner: GPT-5.2-CodexGPT-5.2-Codex achieves 145.81 tokens per second compared to Llama 4 Scout's 110.66. The higher speed supports faster iteration on text and image inputs within its supported context size.
Llama 4 Scout
Pros
- +Extremely large context window
- +Native multimodal input support
- +Strong reasoning over long inputs
Cons
- –High compute cost at maximum context
- –Limited to text and image modalities only
- –May exhibit latency on very long sequences
GPT-5.2-Codex
Pros
- +Very large context window for extended inputs
- +Strong coding specialization
- +Seamless integration of text and image data
Cons
- –Restricted to text and image modalities
- –High resource demands at maximum context length
- –No native support for audio or video
Summary: Llama 4 Scout vs GPT-5.2-Codex
Select GPT-5.2-Codex when intelligence, coding strength, and speed are primary requirements. Opt for Llama 4 Scout when maximum context length and minimal cost are essential. Both remain limited to text and image modalities only.
Frequently asked questions
GPT-5.2-Codex is better for intelligence and speed while Llama 4 Scout is better for context size and price; neither is universally superior.