Qwythos-Claude-Mythos-5

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What Qwythos-Claude-Mythos-5 is

Qwythos-9B-Claude-Mythos-5-1M-GGUF Developed by Empero GGUF quantizations of empero-ai/Qwythos-9B-Claude-Mythos-5-1M for llama.cpp, Ollama, LM Studio, jan, KoboldCpp, and other GGUF runtimes. Qwythos-9B is a full-parameter reasoning model post-trained on over 500 million tokens of high-quality Claude Mythos / Claude Fable traces with chain-of-thought generated in-house by Empero AI's internal rethink tool. It dominates the base Qwen3.5-9B under matched evaluation (+34 pts MMLU, +30 pts gsm8k-strict, +19 pts gsm8k-flex), supports native function calling per the Qwen3.5 spec, and ships with a 1,048,576-token (1M) context window via YaRN rope-scaling enabled by default. For full training details, evaluation numbers, and capability writeup, see the base model card. Files Normal text weights — fixed v3 replacements If you don't know which to pick, Q4KM is the right starting point — it's the smallest practical quant with good quality preservation. MTP-enabled text weights — fixed v3 variants These include the restored Qwen3.5-compatible MTP head inside the GGUF. Use them with llama.cpp builds that support MTP draft speculation, for example --spec-type draft-mtp. Vision projector — for image input Qwythos inherits its vision tower from the Qwen3.5-9B base model — the vision path was frozen during SFT (training was text-only), so the vision behavior is identical to base Qwen3.5-9B's multimodal capability. The mmproj is interchangeable with any community-built Qwen3.5-9B mmproj-.gguf. Quick start llama.cpp (llama-cli) Ollama LM Studio / jan / KoboldCpp Drop any of the .gguf files into your runtime's model directory. Qwythos uses the standard Qwen3.5 chat template; modern GGUF runtimes load it automatically from the file. llama.cpp with MTP draft speculation MTP support requires a recent llama.cpp build. If your runtime does not support MTP yet, use the normal fixed v3 files above. Vision (image input) Qwythos supports image input out of the box. Download both a text quant and the mmproj-.gguf file from this repo, then run with llama.cpp's multimodal CLI or server. llama.cpp (llama-mtmd-cli) llama.cpp server (OpenAI-compatible API with images) Then POST to /v1/chat/comple

Summarised from the published model card. Read the full card on the HuggingFace links below.

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Variants

Sizes & precisions

Open weights ship in several sizes and precisions. One page, all the variants — pick the one that fits your GPU. VRAM figures are estimates from model size.

Using it via the API

Call it like any OpenAI endpoint

Once AxForge deploys qwythos-claude-mythos-5 for you, it answers on the OpenAI-compatible API — the same base URL and keys as every other model. (qwythos-claude-mythos-5 below is illustrative; you get the exact model name on deployment.)

$ curl -sS https://api.axforge.ai/v1/chat/completions \
  -H "Authorization: Bearer $AXFORGE_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"qwythos-claude-mythos-5","messages":[{"role":"user","content":"Hello"}]}'

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