# Qwen3.8 Flash Next GSQ RCO Abliterated GGUF

URL: https://interfaze.ai/models/sc117qwen38-flash-next-gsq-rco-abliterated-gguf

[All models](https://interfaze.ai/models)

Qwen3.8 Flash Next GSQ RCO Abliterated GGUF by SC117, a image-text-to-text model with multimodal capabilities. Understand and compare multimodal features, benchmarks, and capabilities.

## Comparison

| Feature | Qwen3.8 Flash Next GSQ RCO Abliterated GGUF | Interfaze |
| --- | --- | --- |
| Input Modalities | text, image, video | image, text, audio, video, document |
| Native OCR | No | Yes |
| Long Document Processing | No | Yes |
| Language Support | unknown | 162+ |
| Native Speech-to-Text | No | Yes |
| Native Object Detection | No | Yes |
| Guardrail Controls | Yes | Yes |
| Context Input Size | 262.1K | 1M |
| Tool Calling | Yes | Tool calling supported + built in browser, code execution and web search |

### Scaling

| Feature | Qwen3.8 Flash Next GSQ RCO Abliterated GGUF | Interfaze |
| --- | --- | --- |
| Scaling | Self-hosted/Provider-hosted with quantization | Unlimited |

[Try Interfaze](https://interfaze.ai/dashboard)[Read the Docs](https://interfaze.ai/docs)

View model card on [Hugging Face](https://huggingface.co/SC117/Qwen3.8-Flash-Next-GSQ-RCO-abliterated-GGUF)

llama-mtmd-cli -m IQ3\_S/Qwen3.8-Flash-Next-GSQ-RCO-abliterated-IQ3\_S-00001-of-00002.gguf  
\--mmproj mmproj-Qwen3.8-Flash-Next-BF16.gguf -lm mmap --lazy-mode on  
\--image photo.jpg -p "Describe this image."Speculative decoding with the MTP draft headllama-cli -m IQ3\_S/Qwen3.8-Flash-Next-GSQ-RCO-abliterated-IQ3\_S-00001-of-00002.gguf  
\-md mtp-Qwen3.8-Flash-Next-Q8\_0.gguf --draft-max 4 -lm mmap --lazy-mode on -ngl 99\-lm mmap --lazy-mode on keeps the n-gram table memory-mapped on disk: it is 28.8 GB and one row is read per token. Shard 1 wants to be resident (VRAM or RAM); shard 2 is fine on an SSD. The vision projector is a standard clip GGUF shared with the upstream tiers, 0.91 GB. Native context is 262,144 tokens and the KV cache grows with it, so start at \-c 32768 and work up.

## Want more deterministic results?

[Try Interfaze](https://interfaze.ai/dashboard)[Read the Docs](https://interfaze.ai/docs)