How to Fix 422 Unprocessable Entity - Prompt token count exceeds maximum context (Mistral AI)

Quick Answer: This error occurs when the total number of tokens in your input prompt and system instructions exceeds the maximum context window supported by the chosen Mistral AI model. The fastest fix is to shorten your input text, remove unnecessary context, or switch to a model with a larger context window.

What Causes This Error

• The input prompt or conversation history is too long for the selected model's context limit.
• System prompts or instructions are excessively verbose, eating up available token space.
• Included code snippets, large documents, or raw text payloads exceed expected size limits.
• Tokenization of specialized languages or non-English text resulted in a higher-than-expected token count.

Step-by-Step Fixes

Fix 1: Fix 1: Truncate Input Data and Conversation History

Review your prompt and identify outdated or redundant conversation history in multi-turn chats.,Trim the input text to remove unnecessary background details or filler sentences.,Resend the API request with the shortened prompt.

Fix 2: Fix 2: Switch to a Larger Context Model

Check which Mistral model you are currently calling (e.g., Mistral Small, Medium, or Large).,Update your API request payload to target a model that supports a larger maximum context window if your use case requires long inputs.,Verify your account tier supports the selected model.

Fix 3: Fix 3: Implement Text Chunking or Summarization

Break down large documents into smaller, manageable paragraphs or chunks.,Process each chunk independently or use an initial summarization step to condense the information.,Pass only the synthesized summary or relevant section into the final prompt.

Advanced Fixes

Advanced Fix 1: Advanced: Programmatic Token Counting and Pre-flight Validation

Integrate Mistral's official tokenizer library or tokenizer tools into your application pipeline before making API calls.,Count the exact number of tokens your payload will consume dynamically.,Implement automatic truncation or chunking logic in your middleware if the calculated token count nears the model threshold.

FAQs

Q: What is the token limit for Mistral AI models?

A: Token limits vary depending on the specific model. For instance, models like Mistral Large support up to 128,000 tokens, while older or smaller variants may have significantly lower limits such as 8,192 or 32,768 tokens. Always check the official documentation for the exact model you are using.

Q: Does the response length affect this error?

A: No, this specific 422 error is triggered strictly by the *prompt* (input) token count exceeding the context limit. However, many models reserve parts of the total window for generation, so extremely long inputs can still indirectly cause issues.