--- license: apache-2.0 base_model: Altworld/Astrea-R8-Chat-9B pipeline_tag: text-generation language: - en tags: - gguf - llama.cpp - qwen3.5 - chat - creative-writing - altworld --- # Astrea R8 Chat 9B — GGUF Official text-only GGUF builds of [Altworld/Astrea-R8-Chat-9B](https://huggingface.co/Altworld/Astrea-R8-Chat-9B), a compact conversational and creative-writing model built on Qwen3.5-9B. **[Try Astrea](https://chat.altworld.io)** · **[API](https://altworld.io/developer)** · **[Documentation](https://astrea.altworld.io/docs/)** ## Files | Quant | Size | Use case | |---|---:|---| | **Q5_K_M** | 6.02 GiB | Recommended balance of quality and size | | Q4_K_M | 5.24 GiB | Smaller and faster; passed the same chat-routing smoke tests | | Q6_K | 6.85 GiB | Higher fidelity | | Q8_0 | 8.87 GiB | Highest-fidelity quant in this repository | These are single-file, text-only models. The inherited vision components are not included because Astrea's visual behavior was not part of the release evaluation. ## Run with llama.cpp Use a current build of [llama.cpp](https://github.com/ggml-org/llama.cpp); Qwen3.5 support is recent. ```bash llama-cli \ -hf Altworld/Astrea-R8-Chat-9B-GGUF:Q5_K_M \ -cnv \ --reasoning off \ --temp 0.8 \ --min-p 0.025 \ --repeat-penalty 1.08 ``` For an OpenAI-compatible local server: ```bash llama-server \ -hf Altworld/Astrea-R8-Chat-9B-GGUF:Q5_K_M \ --reasoning off \ --temp 0.8 \ --min-p 0.025 \ --repeat-penalty 1.08 ``` Use `--temp 0.2` for factual chat. The model carries its official chat template inside the GGUF and does not require a system prompt. Reasoning is disabled in the examples because Astrea's release behavior is direct response without a visible thinking block. ## Validation Each file was loaded and generated from with llama.cpp. The checks covered: - bare greeting with no system prompt; - native Astrea/Altworld identity; - ordinary factual chat; - supportive conversation; - creative-writing routing from a plain request with no scene card; - multi-turn recall using the embedded chat template. Q4_K_M, the most aggressive quant here, correctly answered `Good afternoon.` as normal chat and produced a coherent story from `Write a short story about a dragon who collects spoons.` Q5_K_M correctly recalled a name across turns. The GGUFs declare the base architecture's 262,144-token context. Actual usable context depends on your hardware, llama.cpp build, and runtime settings. ## Conversion details Converted from the official merged BF16 release with llama.cpp commit [`76f46ad`](https://github.com/ggml-org/llama.cpp/commit/76f46ad29d61fd8c1401e8221842934bf62a6064). The source checkpoint contains no MTP tensors, so conversion used `--no-mtp`. Quantization used llama.cpp's `Q4_K_M`, `Q5_K_M`, `Q6_K`, and `Q8_0` presets. ## About Astrea Astrea was trained on top of Qwen3.5-9B using multi-round LoRA supervised fine-tuning, alternating conversational and narrative rounds and checking each round against Altworldbench. See the [BF16 model card](https://huggingface.co/Altworld/Astrea-R8-Chat-9B) for benchmarks, methodology, examples, limitations, and the evaluation protocol. Astrea is English-first and can still hallucinate. Verify high-stakes claims independently. Engine and quantization differences can affect output, so test your own prompts and settings. ## License Apache-2.0. See `LICENSE` and `NOTICE`.