based on user reports and queries over the last 24 hours
Gemini outage statistics
- Google AI Studio feedback button at aistudio.google.com;
- Google Cloud Support Console for paid customers;
- Community forum at discuss.ai.google.dev;
- Documentation at ai.google.dev/gemini-api/docs;
- Stack Overflow with 'google-gemini' tag;
- GitHub issues for SDK problems;
- Google Cloud support tickets for billing/technical issues;
- Developer Discord communities for peer assistance;
- Enterprise support for Google Workspace customers.
- Official Website - https://gemini.google.com;
- Google AI Blog - https://blog.google/technology/ai;
- Developer Site - https://ai.google.dev;
- Documentation - https://ai.google.dev/gemini-api/docs;
- Google Cloud AI - https://cloud.google.com/ai;
- YouTube - https://www.youtube.com/@Google;
- X (Twitter) - https://x.com/Google and https://x.com/GoogleAI;
- GitHub - https://github.com/google-gemini;
- Status Page - https://status.cloud.google.com;
- API Updates - Check ai.google.dev for release notes.
Gemini service interruptions manifest as API endpoints failing, web interface not loading, or complete platform unavailability across all access points.
- Monitor Google Cloud status dashboard for reported incidents;
- Visit ai.google.dev/status for Gemini-specific service health;
- Test connectivity across different Google regions;
- Verify network firewall rules aren't blocking Google services;
- Switch between Gemini models (Pro, Flash, Ultra) if available;
- Clear browser cache if using web interface;
- Check API quota limits haven't been exhausted;
- Wait 15-25 minutes during peak traffic or maintenance windows;
- Try accessing through Google AI Studio versus API directly;
- Confirm issue affects multiple users via community forums.
Credential issues encompass API key rejection, OAuth failures, or authorization errors preventing service access.
- Generate fresh API key from Google AI Studio;
- Verify API key copied completely without extra spaces;
- Check API key restrictions match your usage (IP, domains);
- Confirm Gemini API enabled in Google Cloud Console;
- Review API key permissions and scopes granted;
- Verify billing account active if using paid tier;
- Test with newly created project to isolate issues;
- Check for API key expiration or revocation;
- Ensure correct authentication header format in requests;
- Contact Google Cloud support for persistent auth failures.
Content quality problems include inaccurate information, nonsensical responses, or outputs not matching prompt intent.
- Craft more specific and detailed prompts with context;
- Use system instructions to guide response style;
- Adjust temperature parameter (lower for factual, higher for creative);
- Specify output format explicitly (JSON, markdown, plain text);
- Provide few-shot examples demonstrating desired output;
- Break complex queries into sequential simpler requests;
- Use grounding with Google Search for factual accuracy;
- Verify appropriate model selected for task complexity;
- Implement safety settings appropriate to content type;
- Try alternative phrasing if initial prompt ineffective.
Throttling problems involve hitting request limits, quota exhaustion errors, or temporary access suspension.
- Check current quota usage in Google Cloud Console;
- Implement exponential backoff retry logic in code;
- Reduce request frequency to stay within limits;
- Upgrade to higher quota tier if consistently hitting limits;
- Monitor requests per minute (RPM) and tokens per minute (TPM);
- Cache responses to minimize redundant API calls;
- Distribute requests across multiple API keys if allowed;
- Request quota increase through Google Cloud support;
- Use batch processing during off-peak hours;
- Review pricing page for tier limits and costs.
Media processing issues include image uploads rejected, vision capabilities not working, or format incompatibility errors.
- Verify image format supported (JPEG, PNG, WebP, HEIC, HEIF);
- Check image file size under maximum limit (typically 20MB);
- Ensure image resolution within acceptable parameters;
- Use base64 encoding properly for image data;
- Test with different image to isolate file-specific issues;
- Verify using Gemini model with vision capabilities;
- Check image URL accessibility if using remote images;
- Compress large images before submission;
- Review vision API documentation for format requirements;
- Try simpler image analysis prompts initially.
Moderation issues involve legitimate content flagged, overly aggressive filtering, or inconsistent policy application.
- Review Google AI safety settings and categories;
- Adjust safety threshold parameters in API request;
- Rephrase prompts using neutral, technical language;
- Remove potentially sensitive keywords or topics;
- Check which safety category triggered the block;
- Provide additional context to clarify legitimate intent;
- Use harm_category and harm_probability settings appropriately;
- Document false positives for feedback to Google;
- Consider educational or research use case exemptions;
- Appeal through proper channels if wrongly filtered.
Search-enhanced features failing include grounding errors, search results not incorporating, or real-time information unavailable.
- Verify grounding feature enabled in API request;
- Check using Gemini model that supports grounding;
- Confirm Google Search integration activated correctly;
- Review search query formulation in your prompt;
- Check for API parameter configuration errors;
- Verify no network restrictions blocking Google Search;
- Test without grounding to isolate the issue;
- Review documentation for proper grounding syntax;
- Check if feature available in your region;
- Monitor for known issues with grounding service.
Token limit problems involve context overflow, conversation history lost, or extremely long inputs rejected.
- Check token limits for your Gemini model version;
- Implement conversation summarization for long histories;
- Use Gemini 1.5 Pro for extended 2M token context;
- Calculate tokens before sending to avoid overflow;
- Truncate older messages while preserving critical context;
- Break very long documents into manageable chunks;
- Use sliding window approach for sequential processing;
- Monitor token usage in API responses;
- Consider upgrading to model with larger context;
- Implement efficient context management strategies.
Programming assistance issues include buggy code outputs, syntax errors, or solutions that don't execute properly.
- Specify programming language and version explicitly;
- Provide detailed requirements and constraints clearly;
- Include example inputs and expected outputs;
- Request code comments and explanations inline;
- Test generated code in isolated sandbox environment;
- Ask model to explain reasoning before generating code;
- Provide error messages for debugging assistance;
- Reference relevant libraries and frameworks specifically;
- Break complex coding tasks into smaller functions;
- Manually review and validate all generated code.
Structured data problems include malformed JSON, schema violations, or parsing errors in outputs.
- Enable JSON mode explicitly in API request;
- Provide clear JSON schema in system instructions;
- Specify required fields and data types precisely;
- Use Gemini 1.5+ models with better JSON support;
- Request model to validate JSON before output;
- Implement JSON parsing error handling in code;
- Provide example valid JSON in few-shot prompts;
- Check for trailing commas or syntax issues;
- Use response_mime_type parameter correctly;
- Validate output against expected schema programmatically.
Function/tool integration problems include function calls not triggering, parameters incorrect, or execution failures.
- Define function schemas clearly and completely;
- Verify function declarations match actual implementations;
- Check parameter types and descriptions accurate;
- Provide clear examples of function usage;
- Implement proper function execution and response handling;
- Debug function call arguments in API responses;
- Verify model supports function calling feature;
- Test functions independently before integration;
- Review function calling documentation thoroughly;
- Handle function execution errors gracefully.
Financial concerns involve higher-than-expected costs, billing errors, or unclear pricing structure.
- Review detailed usage reports in Google Cloud Console;
- Understand token-based pricing model for inputs/outputs;
- Monitor costs using Google Cloud billing alerts;
- Check which model tier generating most costs;
- Implement cost controls and budget limits;
- Compare Gemini Flash vs Pro for cost optimization;
- Audit API calls for inefficient token usage;
- Use caching to reduce redundant processing costs;
- Review pricing calculator at ai.google.dev/pricing;
- Contact Google Cloud billing support with documentation.
Platform-specific issues with Google AI Studio include interface bugs, project loading failures, or feature malfunctions.
- Refresh browser and clear cache completely;
- Try different browser (Chrome, Firefox, Edge);
- Check browser extensions aren't interfering;
- Verify logged into correct Google account;
- Disable ad blockers temporarily;
- Check JavaScript enabled in browser settings;
- Try incognito/private browsing mode;
- Update browser to latest version;
- Test on different device to isolate issue;
- Report bugs through feedback button in Studio.
Gemini
Your message will be published in about
5 minutes
Service administration will see your message