runanywhere/SmolVLM-500M-Instruct-GGUF

SmolVLM 500M Instruct — GGUF

SmolVLM-500M-Instruct quantized to GGUF format for llama.cpp, packaged for use with the RunAnywhere SDK.

Files:

• SmolVLM-500M-Instruct-Q8_0.gguf — Language model (~416 MB)
• mmproj-SmolVLM-500M-Instruct-f16.gguf — Vision encoder (~190 MB)

Usage with RunAnywhere SDK

Swift (iOS / macOS)

import RunAnywhere

RunAnywhere.registerModel(
    id: "smolvlm-500m-instruct-q8_0",
    name: "SmolVLM 500M Instruct Q8_0",
    repo: "runanywhere/SmolVLM-500M-Instruct-GGUF",
    files: ["SmolVLM-500M-Instruct-Q8_0.gguf", "mmproj-SmolVLM-500M-Instruct-f16.gguf"],
    framework: .llamaCpp,
    modality: .multimodal,
    memoryRequirement: 600_000_000
)

// VLM inference with image
let result = try await RunAnywhere.generateVLM(
    prompt: "Describe what you see in this image.",
    image: imageData,
    modelId: "smolvlm-500m-instruct-q8_0"
)

Kotlin (Android / JVM)

import com.runanywhere.sdk.RunAnywhere
import com.runanywhere.sdk.models.*

RunAnywhere.registerModel(
    id = "smolvlm-500m-instruct-q8_0",
    name = "SmolVLM 500M Instruct Q8_0",
    repo = "runanywhere/SmolVLM-500M-Instruct-GGUF",
    files = listOf("SmolVLM-500M-Instruct-Q8_0.gguf", "mmproj-SmolVLM-500M-Instruct-f16.gguf"),
    framework = InferenceFramework.LLAMA_CPP,
    modality = ModelCategory.MULTIMODAL,
    memoryRequirement = 600_000_000L
)

val result = RunAnywhere.generateVLM(
    prompt = "Describe what you see.",
    image = imageData,
    modelId = "smolvlm-500m-instruct-q8_0"
)

Web (TypeScript)

import { RunAnywhere, LLMFramework, ModelCategory } from '@anthropic/runanywhere-web';

RunAnywhere.registerModels([{
  id: 'smolvlm-500m-instruct-q8_0',
  name: 'SmolVLM 500M Instruct Q8_0',
  repo: 'runanywhere/SmolVLM-500M-Instruct-GGUF',
  files: ['SmolVLM-500M-Instruct-Q8_0.gguf', 'mmproj-SmolVLM-500M-Instruct-f16.gguf'],
  framework: LLMFramework.LlamaCpp,
  modality: ModelCategory.Multimodal,
  memoryRequirement: 600_000_000,
}]);

await RunAnywhere.downloadModel('smolvlm-500m-instruct-q8_0');
await RunAnywhere.loadModel('smolvlm-500m-instruct-q8_0');

const result = await RunAnywhere.generateVLM('Describe what you see.', imageData, 'smolvlm-500m-instruct-q8_0');

React Native (TypeScript)

import { RunAnywhere } from 'runanywhere-react-native';

RunAnywhere.registerModel({
  id: 'smolvlm-500m-instruct-q8_0',
  name: 'SmolVLM 500M Instruct Q8_0',
  repo: 'runanywhere/SmolVLM-500M-Instruct-GGUF',
  files: ['SmolVLM-500M-Instruct-Q8_0.gguf', 'mmproj-SmolVLM-500M-Instruct-f16.gguf'],
  framework: 'llamaCpp',
  modality: 'multimodal',
  memoryRequirement: 600_000_000,
});

const result = await RunAnywhere.generateVLM('Describe what you see.', imageData, 'smolvlm-500m-instruct-q8_0');

Flutter (Dart)

import 'package:runanywhere_flutter/runanywhere_flutter.dart';

RunAnywhere.registerModel(
  id: 'smolvlm-500m-instruct-q8_0',
  name: 'SmolVLM 500M Instruct Q8_0',
  repo: 'runanywhere/SmolVLM-500M-Instruct-GGUF',
  files: ['SmolVLM-500M-Instruct-Q8_0.gguf', 'mmproj-SmolVLM-500M-Instruct-f16.gguf'],
  framework: InferenceFramework.llamaCpp,
  modality: ModelCategory.multimodal,
  memoryRequirement: 600000000,
);

final result = await RunAnywhere.generateVLM('Describe what you see.', imageData, 'smolvlm-500m-instruct-q8_0');

Model Details

Property	Value
Base Model	SmolVLM-500M-Instruct
Parameters	500M
Quantization	Q8_0
Runtime	llama.cpp (with multimodal/mtmd)
Vision Encoder	SigLIP (F16)

Attribution

Original model by HuggingFace. GGUF conversion by ggml-org.