Mistral Nemo vs GLM-4-Air

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

Zhipu AI

Zhipu AI's mid-tier model. Good balance of cost and performance for Chinese-language applications.

Input	$0.140/M
Output	$0.140/M
Context	128K tokens
Best For	Chinese-language applications, general AI tasks

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

Scenario	Mistral Nemo	GLM-4-Air	Savings
Small Script (1K lines)	<$0.01	<$0.01	GLM-4-Air saves <$0.01 (7%)
Medium Feature (10K lines)	$0.08	$0.08	GLM-4-Air saves <$0.01 (7%)
Large Project (50K lines)	$0.41	$0.39	GLM-4-Air saves $0.03 (7%)
Code Review (5K lines)	$0.03	$0.03	GLM-4-Air saves <$0.01 (7%)

GLM-4-Air wins on both price and performance — $0.140/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.