Mistral Nemo vs Groq Llama 3.3 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 |
Groq Llama 3.3 70B
GroqLlama 3.3 70B running on Groq's ultra-fast LPU inference. Sub-100ms responses for 70B model.
| Input | $0.590/M |
| Output | $0.790/M |
| Context | 128K tokens |
| Best For | Real-time applications, fast chat, low-latency coding |
Cost Comparison by Scenario
Estimated cost per project with 30% cache hit rate. Actual costs may vary based on usage patterns.
| Scenario | Mistral Nemo | Groq Llama 3.3 70B | Savings |
|---|---|---|---|
| Small Script (1K lines) | <$0.01 | $0.04 | Mistral Nemo saves $0.03 (78%) |
| Medium Feature (10K lines) | $0.08 | $0.36 | Mistral Nemo saves $0.28 (77%) |
| Large Project (50K lines) | $0.41 | $1.82 | Mistral Nemo saves $1.41 (77%) |
| Code Review (5K lines) | $0.03 | $0.12 | Mistral Nemo saves $0.09 (76%) |
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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