Choose SC117/Qwen3.8-Flash-Next-GSQ-RCO-abliterated-GGUF if…
No advantage on the data we track — pick it for provider preference or output quality on your own prompts.
OpenAI: GPT-5 Image Mini comes out ahead on the data we track: 6 advantages and none for SC117/Qwen3.8-Flash-Next-GSQ-RCO-abliterated-GGUF.
| Spec | SC117/Qwen3.8-Flash-Next-GSQ-RCO-abliterated-GGUF | OpenAI: GPT-5 Image Mini |
|---|---|---|
| Provider | Hugging Face | OpenAI |
| Input price (per 1M tokens) | n/a | $2.50 |
| Output price (per 1M tokens) | n/a | $2.00 |
| Blended price (3:1 input/output) | n/a | $2.38 |
| Cheaper than … of all models we track | n/a | 24% |
| Context window | n/a | 400K tokens (~600 pages) |
| Larger context than … of all models | n/a | 63% |
| Max output per response | n/a | 128K tokens (~96,000 words) |
| Input types | text | file, image, text |
| Output types | image | image, text |
| Free variant | No | No |
| Listed since | n/a | 2025-10-16 |
Monthly cost at list price for five common workloads. Token counts per unit are stated so you can scale them to your own traffic. A workload that does not fit a model's context window is marked rather than priced.
| Workload (per month) | SC117/Qwen3.8-Flash-Next-GSQ-RCO-abliterated-GGUF | OpenAI: GPT-5 Image Mini | Difference |
|---|---|---|---|
| Customer-support chatbot 50,000 conversations — each a 6-turn conversation (1,500 in / 400 out tokens) | n/a | $228 | — |
| RAG search over documents 20,000 questions — each a question answered from ~8 retrieved passages (6,000 in / 500 out tokens) | n/a | $320 | — |
| Coding / tool-using agent 2,000 tasks — each a multi-step task with tool calls and file context (60,000 in / 6,000 out tokens) | n/a | $324 | — |
| Batch summarisation 10,000 documents — each a 6,000-word report summarised to a page (8,000 in / 600 out tokens) | n/a | $212 | — |
| Long-document analysis 500 documents — each a 150-page contract or codebase read in one pass (100,000 in / 2,000 out tokens) | n/a | $127 | — |
| Capability | SC117/Qwen3.8-Flash-Next-GSQ-RCO-abliterated-GGUF | OpenAI: GPT-5 Image Mini | What it lets you do |
|---|---|---|---|
| Tool / function calling | — | — | call your APIs and run agent loops |
| Structured output (JSON schema) | — | ✓ Yes | return JSON that validates against your schema |
| Reasoning / thinking mode | ✓ Yes | ✓ Yes | spend extra tokens thinking before answering hard problems |
| Image input | — | ✓ Yes | read screenshots, charts and scanned pages |
| Audio input | — | — | take speech or audio directly |
| File / PDF input | — | ✓ Yes | accept documents without your own parsing step |
| Image output | ✓ Yes | ✓ Yes | generate images, not just text |
| Built-in web search | — | ✓ Yes | answer from live web results |
| Seed (reproducible sampling) | — | ✓ Yes | repeat a generation for tests and evals |
| Log-probabilities | — | ✓ Yes | read token confidence for classification and scoring |
From each model's published parameters and input/output types. “—” means not advertised, not proven absent.
No advantage on the data we track — pick it for provider preference or output quality on your own prompts.
OpenAI: GPT-5 Image Mini comes out ahead on the data we track: 6 advantages and none for SC117/Qwen3.8-Flash-Next-GSQ-RCO-abliterated-GGUF.
Tool calling — SC117/Qwen3.8-Flash-Next-GSQ-RCO-abliterated-GGUF: not advertised, OpenAI: GPT-5 Image Mini: not advertised. JSON-schema structured output — SC117/Qwen3.8-Flash-Next-GSQ-RCO-abliterated-GGUF: not advertised, OpenAI: GPT-5 Image Mini: yes.
Only OpenAI: GPT-5 Image Mini accepts image input; SC117/Qwen3.8-Flash-Next-GSQ-RCO-abliterated-GGUF is text-only for input.
No free variant is listed for either; both are pay-per-token.
No description provided yet.
Full SC117/Qwen3.8-Flash-Next-GSQ-RCO-abliterated-GGUF specs →GPT-5 Image Mini combines OpenAI's advanced language capabilities, powered by [GPT-5 Mini](https://openrouter.ai/openai/gpt-5-mini), with GPT Image 1 Mini for efficient image generation. This natively multimodal model features superior instruction following, text...
Full OpenAI: GPT-5 Image Mini specs →