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Model Comparison

ggml-org/embeddinggemma-300m-ggufvsggml-org/smolvlm-256m-instruct-gguf

Side-by-side comparison of ggml-org/embeddinggemma-300m-gguf and ggml-org/smolvlm-256m-instruct-gguf: downloads, license, context length, tasks, and benchmarks.

ggml-org/embeddinggemma-300m-gguf

ggml-org · —

# embeddinggemma-300M GGUF Recommended way to run this model: ``sh llama-server -hf ggml-org/embeddinggemma-300M-GGUF --embeddings ` Then the endpoint can be accessed at http://localhost:8080/embedding, for example using curl: `console curl --request POST \ --url http://localhos…

ggml-org/smolvlm-256m-instruct-gguf

ggml-org · —

Original model: https://huggingface.co/HuggingFaceTB/SmolVLM-256M-Instruct For more info, please refer to this PR: https://github.com/ggml-org/llama.cpp/pull/13050

Side-by-side Specifications

ggml-org/embeddinggemma-300m-ggufggml-org/smolvlm-256m-instruct-gguf
Authorggml-orgggml-org
Pipeline Task——
Library——
Downloads349,29033,083
Likes2614
LicenseUnknownUnknown
Context Length——
Created2025-09-042025-04-21
Last Modified2025-09-042025-04-30
Tags
ggufbase_model:google/embeddinggemma-300mbase_model:quantized:google/embeddinggemma-300mendpoints_compatibleregion:us
ggufbase_model:HuggingFaceTB/SmolVLM-256M-Instructbase_model:quantized:HuggingFaceTB/SmolVLM-256M-Instructlicense:apache-2.0endpoints_compatibleregion:usconversational

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