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Model Comparison

ggml-org/smolvlm2-2.2b-instruct-ggufvstvall43/qwen3.5-14b-a3b-claude-4.6-opus-reasoning-distilled-reap-gguf

Side-by-side comparison of ggml-org/smolvlm2-2.2b-instruct-gguf and tvall43/qwen3.5-14b-a3b-claude-4.6-opus-reasoning-distilled-reap-gguf: downloads, license, context length, tasks, and benchmarks.

ggml-org/smolvlm2-2.2b-instruct-gguf

ggml-org · —

Original model: https://huggingface.co/HuggingFaceTB/SmolVLM2-2.2B-Instruct For more info, please refer to this PR: https://github.com/ggml-org/llama.cpp/pull/13050

tvall43/qwen3.5-14b-a3b-claude-4.6-opus-reasoning-distilled-reap-gguf

tvall43 · text-generation

can i fit moe qwen3.5 in 10gb vram? since thats already risky, lets yolo and use claude distil too. 0.65 compression this time. my original goal was 8gb vram but i mathed wrong somewhere. that fits fine on my gpro x080 but not single gpu in the radeon v340l. maybe ill give it an…

Side-by-side Specifications

ggml-org/smolvlm2-2.2b-instruct-gguftvall43/qwen3.5-14b-a3b-claude-4.6-opus-reasoning-distilled-reap-gguf
Authorggml-orgtvall43
Pipeline Task—text-generation
Library—transformers
Downloads24,92020,490
Likes3218
LicenseUnknownUnknown
Context Length——
Created2025-04-212026-03-09
Last Modified2025-04-302026-03-09
Tags
ggufbase_model:HuggingFaceTB/SmolVLM2-2.2B-Instructbase_model:quantized:HuggingFaceTB/SmolVLM2-2.2B-Instructlicense:apache-2.0endpoints_compatibleregion:usconversational
transformersgguftext-generation-inferenceunslothqwen3_5_moeqwenqwen3.5reasoningchain-of-thoughttext-generation

View full details: ggml-org/smolvlm2-2.2b-instruct-gguf · tvall43/qwen3.5-14b-a3b-claude-4.6-opus-reasoning-distilled-reap-gguf