Llama 4 Scout vs Grok 4.20
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
- ✓Need a 10M-token context window for long text and image sequences
- ✓Require the lowest price at $0.3 per million tokens
- ✓Want an open-weight model from Meta for customization or self-hosting
- ✓Prioritize strong reasoning over very long multimodal inputs
Choose Grok 4.20 if you need
- ✓Need higher intelligence scoring 37 versus 10
- ✓Want faster output at 134.25 tokens per second
- ✓Require native support for file inputs in addition to text and images
- ✓Prefer a proprietary model with strong multimodal integration
Verdict
Grok 4.20 leads in intelligence (37 vs 10) and output speed (134.25 t/s vs 109.63 t/s) while supporting file inputs alongside text and images. Llama 4 Scout dominates on context length (10M vs 2M tokens) and price ($0.3 vs $2.5 per 1M tokens) and offers open weights. The choice hinges on whether raw capability or extreme context at low cost matters most.
Llama 4 Scout vs Grok 4.20: side by side
| Spec | Llama 4 Scout | Grok 4.20 | Winner |
|---|---|---|---|
| Intelligence | 10 | 37 | Grok 4.20 |
| Output speed | 111 t/s | 133 t/s | Grok 4.20 |
| Output price | $0.30/1M | $2.50/1M | Llama 4 Scout |
| Context | 10000K | 2000K | Llama 4 Scout |
| Params | — | — | Tie |
| Provider | Meta | xAI | Tie |
Detailed analysis
Intelligence
Winner: Grok 4.20Grok 4.20 scores 37 on the intelligence index while Llama 4 Scout scores 10. This gap indicates Grok delivers stronger overall performance on complex tasks. Both models support native multimodal inputs but differ sharply in measured capability.
Speed
Winner: Grok 4.20Grok 4.20 outputs at 134.25 tokens per second compared with Llama 4 Scout's 109.63 t/s. The speed advantage holds across typical workloads. Both models can experience latency when processing maximum context lengths.
Pricing
Winner: Llama 4 ScoutLlama 4 Scout costs $0.3 per million tokens versus Grok 4.20 at $2.5 per million tokens. The eightfold price difference favors Llama for high-volume usage. Neither model publishes parameter counts for further cost analysis.
Context & Modalities
Winner: Llama 4 ScoutLlama 4 Scout provides a 10M-token context window against Grok 4.20's 2M tokens. Llama supports text and image inputs while Grok adds file inputs. Both lack audio or video support.
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
Grok 4.20
Pros
- +Handles extremely large contexts up to 2M tokens
- +Native support for text, image, and file inputs
- +Multimodal integration in a single model
Cons
- –No audio or video modality support
- –Very large context can increase latency
- –Performance depends on input quality and structure
Summary: Llama 4 Scout vs Grok 4.20
Select Llama 4 Scout when maximum context length, low cost, and open weights are priorities. Choose Grok 4.20 when higher intelligence, faster speed, and file-input support matter more. The models trade off capability against scale and accessibility.
Frequently asked questions
Grok 4.20 scores higher on intelligence and speed; Llama 4 Scout wins on context size and price. No single winner exists across all metrics.