Mistral Nemo vs Databricks DBRX Instruct

Performance benchmarks + pricing comparison — updated April 2026

Mistral Nemo

Mistral

Compact 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

Databricks

Databricks' open MoE model. Competitive with GPT-3.5 for coding and general tasks.

Input	$0.750/M
Output	$2.25/M
Context	32K tokens
Best For	Custom fine-tuning, coding assistance, enterprise NLP

Estimated cost per project with 30% cache hit rate. Actual costs may vary based on usage patterns.

Scenario	Mistral Nemo	Databricks DBRX Instruct	Savings
Small Script (1K lines)	<$0.01	$0.09	Mistral Nemo saves $0.08 (90%)
Medium Feature (10K lines)	$0.08	$0.71	Mistral Nemo saves $0.63 (88%)
Large Project (50K lines)	$0.41	$3.56	Mistral Nemo saves $3.15 (88%)
Code Review (5K lines)	$0.03	$0.19	Mistral Nemo saves $0.16 (84%)

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.

Anthropic's balanced model for coding and general tasks. Best price-performance ratio in the Claude family.

Anthropic's most powerful model. Best for complex reasoning and challenging coding tasks.

Previous generation Sonnet. Still excellent for coding tasks at the same price point.

Fast, cost-effective model for high-volume tasks. Great for code review and simple queries.

First generation Opus. Highest reasoning capability in the Claude 3 family.

First generation Sonnet. Balanced performance for general tasks.