baguettotron-tiny-random
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From language to images, open weights to APIs. Understand capabilities and compare real costs.
Find the right engine for your next idea.
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This model is for debugging. It is randomly initialized with the config from deepseek-ai/DeepSeek-V3 but is of smaller size. **⚠️Note: At this moment, this repo does not contain the Multi-Token Prediction (MTP) module as explained here.**
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This tiny model is for debugging. It is randomly initialized with the config adapted from google/gemma-3-27b-it.
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Adjust provider, category or input/output filters. New models are added continuously.
Adjust monthly token usage to compare estimated API costs.
Uses collected, comparable USD-per-million-token rates. Snapshots exclude cache discounts, tiers, extra reasoning output and taxes. Check current source prices.
Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.
Not necessarily. Check each version’s license, commercial restrictions and policies. Self-hosting also incurs compute and maintenance costs.
Rankings depend on tasks, versions and methods. Compare accuracy, latency, reliability and costs on your own workload.