GPT-4.1 nano vs Codestral: Pricing Comparison
Compare pricing, capabilities, and costs for your LLM workloads.
OpenAI
GPT-4.1 nano
Pricing (per 1M tokens)
Input$0.1000
Output$0.4000
Cached Input$0.0250
Batch Input$0.0500
Batch Output$0.2000
Context & Output
Context Window1.0M tokens
Max Output32.8K tokens
Capabilities
Categorybudget
Multimodaltext + image
Fine-tuningNo
StreamingYes
Mistral
Codestral
Pricing (per 1M tokens)
Input$0.3000
Output$0.9000
Context & Output
Context Window256K tokens
Max Output32.8K tokens
Capabilities
Categorymid
Multimodaltext
Fine-tuningNo
StreamingYes
Quick Verdict
Cheaper Input Price
GPT-4.1 nano
66.7% cheaper
Cheaper Output Price
GPT-4.1 nano
55.6% cheaper
Larger Context Window
GPT-4.1 nano
+791.6K tokens
Cost Comparison
Sample workload: 1,000,000 input tokens + 1,000,000 output tokens
GPT-4.1 nano
$0.5000
$0.1000/1M input + $0.4000/1M output
Codestral
$1.20
$0.3000/1M input + $0.9000/1M output
GPT-4.1 nano is 58.3% cheaper for this workload.
Frequently Asked Questions
Which is cheaper, GPT-4.1 nano or Codestral?
For input tokens, GPT-4.1 nano is cheaper at $0.1000 per 1M tokens. For output tokens, GPT-4.1 nano is cheaper at $0.4000 per 1M tokens. The overall cost depends on your workload's input/output ratio.
What is the context window size of GPT-4.1 nano vs Codestral?
GPT-4.1 nano has a context window of 1.0M tokens, while Codestral has 256K tokens. GPT-4.1 nano supports a larger context window of 1.0M tokens, which is beneficial for processing longer documents.
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