gemma-4-E2B-it-FP8-Dynamic
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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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An uncensored GGUF merge of Qwen 3.5 9B, ready for local deployment with Ollama, llama.cpp, or any GGUF-compatible runtime. This model is built upon HauhauCS/Qwen3.5-9B-Uncensored-HauhauCS-Aggressive. The original base model has the following known issues: 1. **Ollama deployment failure** — The base model cannot be directly deployed via Ollama due to architecture/format incompatibilities. This GGUF version resolves the issue by converting and merging the weights into a single GGUF file that Ollama can load natively. 2. **Broken multimodal input** — The base model's packaging causes multimodal (e.g., image) input to malfunction. Although the underlying Qwen 3.5 architecture supports vision capabilities, the way the original model was packaged breaks multimodal inference.
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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.