AI Models with Long Output
397 AI models with 8K+ output tokens per response. 378 models support 16K+ tokens and 337 support 32K+ - enough to generate full articles, complete code files, or detailed reports in a single response.
All Long Output Models - Sorted by Max Output
Why Output Length Matters
Long-Form Writing
A 16K output limit produces ~12,000 words - enough for a full blog post or report chapter. Models with 32K+ can write entire research papers or documentation sets in one shot.
Code Generation
Generating complete files, modules, or refactoring large codebases requires high output limits. 8K tokens covers ~250 lines of code; 32K covers full application files.
Output vs Context
Context window is the total input+output capacity. Max output is how much the model can generate in one response. A 128K context model might only output 4K tokens per response.
Cost Implications
You pay per output token. Longer outputs cost more but may be more efficient than multiple short requests. Budget models under $1/1M make long outputs affordable at scale.
Long-output models can generate responses exceeding 4,000 tokens (about 3,000 words) in a single response. They are ideal for generating long-form content, complete code files, detailed reports, and comprehensive analyses.
Output length is limited by the model's architecture and the provider's settings. Longer outputs cost more compute and time. Most standard models cap at 4,096 output tokens, while long-output models support 8K-32K+ tokens.
Claude 3.5 supports up to 8,192 output tokens, while some models via API support 16K or 32K output. Check the output capacity column in our table for specific model limits.