Model ID
google/gemma-3-27b-it
Capabilities
Gemma 3 27B IT
Gemma 3 27B IT is a large multimodal instruction-tuned transformer model built using the same research foundation as Gemini models. It features a 27B parameter architecture with 62 transformer layers, 32 attention heads, and a 5,376 hidden size, optimized for advanced reasoning and instruction following. It supports a 128K token context window with RoPE scaling. The model integrates a SigLIP-based vision encoder with 27 layers and supports multimodal processing with 256 tokens per image, enabling joint understanding of text and visual inputs for complex multimodal tasks.
About this model
Gemma 3 27B IT is a large multimodal instruction-tuned transformer model built using the same research foundation as Gemini models. It features a 27B parameter architecture with 62 transformer layers, 32 attention heads, and a 5,376 hidden size, optimized for advanced reasoning and instruction following. It supports a 128K token context window with RoPE scaling. The model integrates a SigLIP-based vision encoder with 27 layers and supports multimodal processing with 256 tokens per image, enabling joint understanding of text and visual inputs for complex multimodal tasks.
Model specifications and capabilities are published by the model author and reproduced here from HF Model Card (google/gemma-3-27b-it). Released under Gemma. Further reading: Paper · Blog
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Hardware
MI325X
2,048 GB
B200
1,440 GB
Engine
vLLM
SGLang
Deployment code
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Performance under load
Tokens/s (total)
Benchmarks measured by Vultr on MI325X · vLLM. Throughput and latency vary with concurrency, input length and engine configuration, so treat these as a comparison baseline, not a service guarantee.
AMD Instinct MI325X
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