Developer Tools2 options compared

LLM Token Counter

Calculates token counts for various large language models including GPT-4, Claude, and Llama, estimating API costs and optimizing prompts based on token limits. Helps developers ensure efficient model usage by providing accurate token count estimates and optimization tips, crucial for managing resources effectively in applications that utilize AI text generation.

Editors’ Top PickBased on community votes
Other OptionsRanked by votes

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LLM Token Counter options compared

ToolBest forStrengthsLimitations
Inventive HQ
inventivehq.com
Quick token counts across many models
  • Supports GPT, Claude, Gemini, and open models like Llama, Gemma, Qwen
  • Can search any model on Hugging Face for custom tokenization
  • Live page excerpt not available, so exact UI details are unknown
DevBolt
devbolt.dev
Private, offline token counting
  • All processing happens in your browser; data never leaves your device
  • Shows context window usage and compares costs across 19 models from 6 providers
  • Fewer model options than Inventive HQ; community votes are 0, indicating less real-world testing

Buyer's guide

How to choose a llm token counter

When picking a token counter, first decide if you need to count tokens for many different models or just the major ones like GPT-4, Claude, and Gemini. If you are optimizing prompts for a specific model and want cost estimates, choose a tool that shows context window usage and pricing per 1M tokens. If privacy is your top concern — you don't want any text sent to a server — pick a browser-based tool that processes everything locally. Otherwise, a wider model search feature is more useful for developers working with less common LLMs.

Questions

LLM Token Counter FAQ

Can I count tokens for any LLM model?
Yes, Inventive HQ lets you search any model on Hugging Face, while DevBolt supports 19 models from 6 providers including GPT-4o, Claude, Gemini, Llama, Mistral, and DeepSeek.
Do I need to install anything to use these tools?
No, both tools run in your browser. DevBolt emphasizes that everything processes locally, so your text never leaves your device.
How accurate are the token counts?
Token counts use BPE tokenization (cl100k_base) as the standard method, which is the same approach major models like GPT-4o and Claude use for their context windows.
Can I estimate API costs with these tools?
Yes, both tools provide cost estimates. DevBolt lists per-1M-token prices for multiple models, and Inventive HQ includes API cost estimation as part of its core features.
Which tool should I use if I want to check a very long prompt?
DevBolt shows context window usage as a percentage, which helps you see how much of the model's limit your prompt occupies. Inventive HQ also checks context window fit, but exact UI details are not available in the stored notes.
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