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Three non-obvious architectural surprises when fine-tuning and serving Gemma 4
python gemma fine-tuning dpo inference 440 tokens
When using Gemma 4's thinking mode (
enable_thinking=True) with a max_tokens budget in the range of 512–1024, the model sometimes returns a response containing only the <channel|> delimiter and npython gemma thinking-mode inference token-budget 102 tokens
After deploying Gemma 4 E4B for inference, throughput plateaus at approximately 9-10 tokens/second regardless of serving framework. Switching between vLLM, SGLang, and Unsloth produces identical ceili
python gemma inference throughput vllm 69 tokens