Llama 4 Scout vs GPT-5
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 Llama 4 Scout if you need a 10-million-token context window for long text and image sequences.
- ✓Choose Llama 4 Scout if you need the lowest output price at $0.3 per million tokens.
- ✓Choose Llama 4 Scout if you need an open-weight model for full control and customization.
- ✓Choose Llama 4 Scout if you need strong reasoning over extremely long multimodal inputs.
Choose GPT-5 if you need
- ✓Choose GPT-5 if you need the highest intelligence index of 21.8.
- ✓Choose GPT-5 if you need faster output at 173.7 tokens per second.
- ✓Choose GPT-5 if you need seamless text-image-file integration.
- ✓Choose GPT-5 if you need a proprietary model with verified multimodal performance.
Verdict
GPT-5 leads in raw intelligence (21.8 vs 13.5) and output speed (173.7 t/s vs 112.48 t/s) while Llama 4 Scout dominates context length (10M vs 400k tokens) and price ($0.3 vs $10 per 1M tokens). Llama 4 Scout is open-weight from Meta; GPT-5 is proprietary from OpenAI. The choice hinges on whether extreme context and cost efficiency outweigh higher measured intelligence and velocity.
Llama 4 Scout vs GPT-5: side by side
| Spec | Llama 4 Scout | GPT-5 | Winner |
|---|---|---|---|
| Intelligence | 13.5 | 21.8 | GPT-5 |
| Output speed | 112 t/s | 174 t/s | GPT-5 |
| Output price | $0.30/1M | $10.00/1M | Llama 4 Scout |
| Context | 10000K | 400K | Llama 4 Scout |
| Params | — | — | Tie |
| Type | Open-weight | Proprietary | Tie |
| Provider | Meta | OpenAI | Tie |
Detailed analysis
Intelligence
Winner: GPT-5GPT-5 scores 21.8 on the intelligence index compared with Llama 4 Scout's 13.5. This gap favors GPT-5 for complex reasoning tasks. Both models support native multimodal input.
Speed
Winner: GPT-5GPT-5 delivers 173.7 tokens per second versus Llama 4 Scout's 112.48 t/s. The speed advantage holds for typical workloads. Both may show latency on maximum-length multimodal inputs.
Pricing
Winner: Llama 4 ScoutLlama 4 Scout costs $0.3 per million output tokens while GPT-5 costs $10 per million. The 33x price difference favors Llama 4 Scout for high-volume use. Both list context-related resource costs at maximum length.
Context Window
Winner: Llama 4 ScoutLlama 4 Scout provides a 10-million-token context versus GPT-5's 400k tokens. This gives Llama 4 Scout a 25x advantage for long sequences. Both models are described as supporting very large contexts.
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
Pros
- +Very large context window
- +Native multimodal input support
- +Seamless text-image-file integration
Cons
- –Hypothetical model with unverified performance
- –High resource demands for maximum context
- –Potential latency on large multimodal tasks
Summary: Llama 4 Scout vs GPT-5
Select Llama 4 Scout when maximum context length, low cost, and open weights are priorities. Select GPT-5 when higher intelligence scores and faster generation speed matter most. The models trade off context and price against intelligence and velocity.
Frequently asked questions
GPT-5 scores higher on intelligence and speed; Llama 4 Scout wins on context size and price. No single winner exists across all metrics.