Mistral Nemo vs Llama 4 Scout
Performance benchmarks + pricing comparison — updated April 2026
Mistral Nemo
MistralCompact 12B open-weight model co-developed with NVIDIA. Excellent coding performance at minimal cost.
| Input | $0.150/M |
| Output | $0.150/M |
| Context | 128K tokens |
| Best For | Self-hosted deployments, cost-sensitive coding, edge deployments |
| Benchmark | 48/100 |
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 | Mistral Nemo | Llama 4 Scout | Savings |
|---|---|---|---|
| Small Script (1K lines) | <$0.01 | $0.03 | Mistral Nemo saves $0.02 (69%) |
| Medium Feature (10K lines) | $0.08 | $0.23 | Mistral Nemo saves $0.15 (64%) |
| Large Project (50K lines) | $0.41 | $1.15 | Mistral Nemo saves $0.74 (64%) |
| Code Review (5K lines) | $0.03 | $0.06 | Mistral Nemo saves $0.03 (45%) |
Verdict
Mistral Nemo wins on both price and performance — $0.150/M input with a benchmark score of N/A/100.
For most developers, this is the clear choice between these two models.
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