DeepSeek Reasoner (R1) vs Llama 4 Scout
Performance benchmarks + pricing comparison — updated April 2026
DeepSeek Reasoner (R1)
DeepSeekDeepSeek's reasoning model. Comparable to OpenAI's o1 but at much lower cost.
| Input | $0.550/M |
| Output | $2.19/M |
| Context | 128K tokens |
| Best For | Complex reasoning, math, advanced coding |
| Benchmark | 72/100 |
Llama 4 Scout
MetaMeta's Llama 4 mid-tier multimodal model. Native multimodal with efficient inference.
| Input | $0.200/M |
| Output | $0.800/M |
| Context | 10M tokens |
| Best For | Multimodal applications, image + text tasks |
Cost Comparison by Scenario
Estimated cost per project with 30% cache hit rate. Actual costs may vary based on usage patterns.
| Scenario | DeepSeek Reasoner (R1) | Llama 4 Scout | Savings |
|---|---|---|---|
| Small Script (1K lines) | $0.08 | $0.03 | Llama 4 Scout saves $0.05 (64%) |
| Medium Feature (10K lines) | $0.63 | $0.23 | Llama 4 Scout saves $0.40 (64%) |
| Large Project (50K lines) | $3.15 | $1.15 | Llama 4 Scout saves $2.00 (64%) |
| Code Review (5K lines) | $0.15 | $0.06 | Llama 4 Scout saves $0.10 (64%) |
Verdict
Llama 4 Scout wins on both price and performance — $0.200/M input with a benchmark score of N/A/100.
For most developers, this is the clear choice between these two models.
Compare with Other Models
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