Mistral Nemo vs Llama 3.1 70B
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 3.1 70B
MetaMeta's mid-size Llama 3.1. Strong general performance with open weights for custom deployment.
| Input | $0.200/M |
| Output | $0.400/M |
| Context | 128K tokens |
| Best For | General AI tasks, custom deployment, fine-tuning |
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 3.1 70B | Savings |
|---|---|---|---|
| Small Script (1K lines) | <$0.01 | $0.02 | Mistral Nemo saves <$0.01 (49%) |
| Medium Feature (10K lines) | $0.08 | $0.15 | Mistral Nemo saves $0.07 (45%) |
| Large Project (50K lines) | $0.41 | $0.75 | Mistral Nemo saves $0.34 (45%) |
| Code Review (5K lines) | $0.03 | $0.04 | Mistral Nemo saves $0.01 (33%) |
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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