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Duplicate from empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF

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Co-authored-by: Empero <empero-ai@users.noreply.huggingface.co>

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+ ---
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+ license: apache-2.0
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+ base_model: empero-ai/Qwythos-9B-Claude-Mythos-5-1M
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+ base_model_relation: quantized
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+ language:
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+ - en
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+ pipeline_tag: text-generation
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+ library_name: gguf
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+ tags:
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+ - gguf
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+ - llama.cpp
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+ - quantized
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+ - qwen3.5
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+ - reasoning
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+ - uncensored
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+ - long-context
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+ - 1M-context
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+ - function-calling
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+ - multimodal
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+ - vision
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+ - cybersecurity
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+ - biomedical
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+ - agentic
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+ ---
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+
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+ <p align="center">
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+ <img src="https://huggingface.co/empero-ai/Qwythos-9B-Claude-Mythos-5-1M/resolve/main/assets/qwythos.png" alt="Qwythos-9B" width="640"/>
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+ </p>
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+
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+ <table>
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+ <tr>
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+ <td>
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+
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+ ## 🚨 v2 released — please redownload the GGUFs
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+
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+ The v2 GGUFs replace the original normal filenames and add explicit `-MTP-` variants. If you downloaded this repo before v2, please redownload your GGUF.
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+
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+ Fixes in v2:
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+
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+ - tokenizer metadata normalized for Qwen3.5 GGUF runtimes;
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+ - embedded chat template updated for reliable tool/function calling and OpenCode-style agent loops;
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+ - Qwythos/Empero identity prompt embedded in the template;
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+ - MTP-enabled variants added as `Qwythos-9B-Claude-Mythos-5-1M-MTP-*.gguf`;
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+ - Q4/Q8 tool-calling, MTP draft speculation, 1M-context allocation, and vision projector smoke-tested with current llama.cpp.
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+
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+ Use the normal files for maximum runtime compatibility. Use the `-MTP-` files when you want llama.cpp MTP draft speculation.
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+
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+ </td>
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+ </tr>
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+ </table>
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+
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+ # Qwythos-9B-Claude-Mythos-5-1M-GGUF
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+
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+ **Developed by [Empero](https://empero.org)**
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+
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+ GGUF quantizations of **[empero-ai/Qwythos-9B-Claude-Mythos-5-1M](https://huggingface.co/empero-ai/Qwythos-9B-Claude-Mythos-5-1M)** for [llama.cpp](https://github.com/ggml-org/llama.cpp), Ollama, LM Studio, jan, KoboldCpp, and other GGUF runtimes.
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+
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+ 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.
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+
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+ For full training details, evaluation numbers, and capability writeup, see the **[base model card](https://huggingface.co/empero-ai/Qwythos-9B-Claude-Mythos-5-1M)**.
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+
62
+ ---
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+
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+ ## Files
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+
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+ ### Normal text weights — fixed v2 replacements
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+
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+ | File | Quant | Size | Notes |
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+ |---|---|---|---|
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+ | `Qwythos-9B-Claude-Mythos-5-1M-Q4_K_M.gguf` | Q4_K_M | 5.24 GiB / 5.63 GB | **recommended default** — fixed v2, best compatibility |
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+ | `Qwythos-9B-Claude-Mythos-5-1M-Q5_K_M.gguf` | Q5_K_M | 6.02 GiB / 6.47 GB | fixed v2, balanced quality / size |
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+ | `Qwythos-9B-Claude-Mythos-5-1M-Q6_K.gguf` | Q6_K | 6.85 GiB / 7.36 GB | fixed v2, high quality |
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+ | `Qwythos-9B-Claude-Mythos-5-1M-Q8_0.gguf` | Q8_0 | 8.87 GiB / 9.53 GB | fixed v2, near-lossless |
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+ | `Qwythos-9B-Claude-Mythos-5-1M-BF16.gguf` | BF16 | 16.69 GiB / 17.92 GB | fixed v2, full precision conversion base |
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+
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+ If you don't know which to pick, **Q4_K_M is the right starting point** — it's the smallest practical quant with good quality preservation.
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+
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+ ### MTP-enabled text weights — v2 variants
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+
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+ 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`.
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+
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+ | File | Quant | Size | Notes |
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+ |---|---|---|---|
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+ | `Qwythos-9B-Claude-Mythos-5-1M-MTP-Q4_K_M.gguf` | Q4_K_M + MTP | 5.48 GiB / 5.89 GB | **recommended MTP default** |
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+ | `Qwythos-9B-Claude-Mythos-5-1M-MTP-Q5_K_M.gguf` | Q5_K_M + MTP | 6.26 GiB / 6.73 GB | MTP, balanced quality / size |
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+ | `Qwythos-9B-Claude-Mythos-5-1M-MTP-Q6_K.gguf` | Q6_K + MTP | 7.09 GiB / 7.62 GB | MTP, high quality |
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+ | `Qwythos-9B-Claude-Mythos-5-1M-MTP-Q8_0.gguf` | Q8_0 + MTP | 9.11 GiB / 9.79 GB | MTP, near-lossless |
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+ | `Qwythos-9B-Claude-Mythos-5-1M-MTP-BF16.gguf` | BF16 + MTP | 17.14 GiB / 18.41 GB | MTP, full precision conversion base |
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+
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+ ### Vision projector — for image input
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+
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+ | File | Size | Notes |
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+ |---|---|---|
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+ | `mmproj-Qwythos-9B-Claude-Mythos-5-1M-F16.gguf` | 0.86 GiB / 0.92 GB | CLIP-style vision encoder + projector; **required for images**, pairs with any normal or MTP quant above |
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+
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+ 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`.
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+
98
+ ---
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+
100
+ ## Quick start
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+
102
+ ### llama.cpp (`llama-cli`)
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+
104
+ ```bash
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+ llama-cli \
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+ -m Qwythos-9B-Claude-Mythos-5-1M-Q4_K_M.gguf \
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+ -p "Walk through the biochemistry of how organophosphate nerve agents inhibit acetylcholinesterase." \
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+ -n 8192 \
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+ --temp 0.6 --top-p 0.95 --top-k 20 --repeat-penalty 1.05 \
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+ -c 16384
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+ ```
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+
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+ ### Ollama
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+
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+ ```bash
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+ ollama run hf.co/empero-ai/Qwythos-9B-Claude-Mythos-5-1M-GGUF:Q4_K_M
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+ ```
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+
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+ ### LM Studio / jan / KoboldCpp
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+
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+ 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.
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+
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+ ### llama.cpp with MTP draft speculation
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+
125
+ ```bash
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+ llama-server \
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+ -m Qwythos-9B-Claude-Mythos-5-1M-MTP-Q4_K_M.gguf \
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+ --spec-type draft-mtp \
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+ --spec-draft-n-max 6 \
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+ -c 16384 --port 8080
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+ ```
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+
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+ MTP support requires a recent llama.cpp build. If your runtime does not support MTP yet, use the normal v2 files above.
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+
135
+ ---
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+
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+ ## Vision (image input)
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+
139
+ 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.
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+
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+ ### llama.cpp (`llama-mtmd-cli`)
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+
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+ ```bash
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+ llama-mtmd-cli \
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+ -m Qwythos-9B-Claude-Mythos-5-1M-Q4_K_M.gguf \
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+ --mmproj mmproj-Qwythos-9B-Claude-Mythos-5-1M-F16.gguf \
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+ --image ./photo.jpg \
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+ -p "Describe this image in detail." \
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+ --temp 0.6 --top-p 0.95 --top-k 20 \
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+ -c 16384
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+ ```
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+
153
+ ### llama.cpp server (OpenAI-compatible API with images)
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+
155
+ ```bash
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+ llama-server \
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+ -m Qwythos-9B-Claude-Mythos-5-1M-Q4_K_M.gguf \
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+ --mmproj mmproj-Qwythos-9B-Claude-Mythos-5-1M-F16.gguf \
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+ -c 16384 --port 8080
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+ ```
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+
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+ Then POST to `/v1/chat/completions` with an image URL or base64 payload — the standard OpenAI vision API shape works.
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+
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+ ### LM Studio
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+
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+ Load the text quant; LM Studio detects the matching `mmproj-*.gguf` in the same folder and enables the image-attach button automatically.
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+
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+ ### What vision unlocks
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+
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+ Since Qwythos inherits its vision tower unchanged from Qwen3.5-9B base, expect Qwen3.5-9B's documented vision capabilities: detailed image description, OCR (printed + handwritten), chart/table reading, UI/document understanding, basic spatial reasoning.
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+
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+ **Honest note:** the SFT used to produce Qwythos was **text-only** — we did not fine-tune the vision tower or train on any image-paired data. Image-grounded reasoning therefore inherits the base model's behavior; it has not been independently evaluated as part of this release. If your application is *primarily* vision-driven, validate on your own use case first.
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+
174
+ ---
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+
176
+ ## Sampling recommendations
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+
178
+ Qwythos is a reasoning model — every response opens with a `<think>...</think>` block before the final answer. Use these settings as defaults:
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+
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+ | Parameter | Value |
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+ |---|---|
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+ | `temperature` | 0.6 |
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+ | `top_p` | 0.95 |
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+ | `top_k` | 20 |
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+ | `repeat_penalty` | 1.05 |
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+ | `max_new_tokens` | 16384 (generous budget for `<think>` + answer) |
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+
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+ These match Qwen3.5's official thinking-mode recommendations. **Avoid greedy decoding and very-low-temperature sampling (T ≤ 0.3)** — both can cause repetition loops on long reasoning generations.
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+
190
+ ---
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+
192
+ ## Long context (1M tokens)
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+
194
+ The GGUFs ship with YaRN rope-scaling baked in for a **1,048,576-token context window** (4× extension over the 262k native).
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+
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+ To use the full 1M window in `llama-cli`, set `-c 1010000` (or any context length up to that). For shorter prompts, lower `-c` to reduce KV-cache memory — at default settings llama.cpp will autosize.
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+
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+ A single H100/H200-class GPU comfortably handles **256k–512k**; the full 1M typically needs tensor-parallel multi-GPU or aggressive KV-cache offload.
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+
200
+ ---
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+
202
+ ## Capabilities (from the base model card)
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+
204
+ - **+34 pts MMLU, +30 pts gsm8k-strict, +19 pts gsm8k-flex** vs. base Qwen3.5-9B under matched lm-eval-harness evaluation
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+ - **Native function calling** per Qwen3.5's chat-template spec — emits `<tool_call><function=NAME><parameter=NAME>VAL</parameter></function></tool_call>` blocks ready for any tool-use loop
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+ - **Self-correcting with tools**: in a 7-prompt tool-use harness (Python executor + DuckDuckGo search), Qwythos produced source-cited correct answers on 7/7, including 4/4 closed-book failure-modes from the original review
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+ - **Uncensored** — engages seriously with technically demanding questions across cybersecurity, red-teaming, biology, pharmacology, and clinical medicine
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+ - **1,048,576-token (1M) context** — YaRN rope-scaling enabled by default
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+
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+ For full eval transcripts and per-task numbers, see the [base model card's `evals/` folder](https://huggingface.co/empero-ai/Qwythos-9B-Claude-Mythos-5-1M/tree/main/evals).
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+
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+ ---
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+
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+ ## Limitations
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+
216
+ - **Reasoning model.** Every answer opens with a `<think>` block; allow generous `max_new_tokens` and parse/strip `<think>...</think>` for end users.
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+ - **Use recommended sampling.** Greedy / very-low-temp can cause repetition loops.
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+ - **Verify specifics in safety-critical contexts.** Like all closed-book LLMs in this weight class, Qwythos can over-commit to specific identifiers (CVEs, hashcat modes, drug positions) it isn't certain about. Pair with retrieval or function calling in such deployments — the model uses tools cleanly when offered them.
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+ - **Uncensored — add your own application-level review/safety layer** for end-user-facing deployments where that matters.
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+
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+ ---
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+
223
+ ## Stay in the loop
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+
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+ Sign up for the Empero newsletter at **[empero.org](https://empero.org)** for releases, evals, and research notes.
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+
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+ ## Support / Donate
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+
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+ If this model helped you, consider supporting the project:
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+
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+ - **BTC**: `bc1qx6zepu6sfkvshgdmc4ewu6pk6rpadvpgffpp7v`
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+ - **LTC**: `ltc1qv2mefzps2vtjcpwfx8xxdrpplrcvltswm68r7x`
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+ - **XMR**: `42Dbm5xg5Nq26fdyzfEU7KBnAJfhi7Cvz5J2ex5CzHXkfKuNEJzYCcmJ1GTbgjFZ5MBx72sdG1G9239Cd6rsZfv4QeDkYJY`
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+
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+ ---
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+
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+ ## Provenance & licensing
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+
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+ Weights are released under **Apache-2.0**, inherited from the Qwen3.5-9B base. Shared for research and experimentation, as-is.
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+
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+ ## Acknowledgements
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+
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+ - Developed and released by [Empero](https://empero.org)
244
+ - Base model: [Qwen3.5-9B](https://huggingface.co/Qwen/Qwen3.5-9B) (Alibaba Qwen team)
245
+ - Quantization: [llama.cpp](https://github.com/ggml-org/llama.cpp) (ggml-org)
246
+ - Vision projector (`mmproj`): inherited from Qwen3.5-9B (vision tower unchanged); F16 GGUF re-hosted with thanks to [Unsloth](https://huggingface.co/unsloth) for the original conversion
247
+ - HF model: [empero-ai/Qwythos-9B-Claude-Mythos-5-1M](https://huggingface.co/empero-ai/Qwythos-9B-Claude-Mythos-5-1M)
SHA256SUMS ADDED
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1
+ c49e2e419c0fc9f7cca0a7e0699fa3075fa1ec2913bda6f6841194b19cf4ce29 ./Qwythos-9B-Claude-Mythos-5-1M-BF16.gguf
2
+ c704996e63c3e31a1e7040278b1204aabf8a6dad0b07f3c8da7b429d2ed30b31 ./Qwythos-9B-Claude-Mythos-5-1M-MTP-BF16.gguf
3
+ 24ee22e0f5d9f0d3d615809607f365c728d9b0c3f3fb6eb19d8bd83a1c2933d8 ./Qwythos-9B-Claude-Mythos-5-1M-MTP-Q4_K_M.gguf
4
+ c4e3c47b17a93cc1566abcee4a0c9a4413b172a6f8be7f2a8824495907e9e893 ./Qwythos-9B-Claude-Mythos-5-1M-MTP-Q5_K_M.gguf
5
+ eae2adb4b451f673218fba96ebdc024fb95c4026ef35a56837dc9af47f99ca39 ./Qwythos-9B-Claude-Mythos-5-1M-MTP-Q6_K.gguf
6
+ 34eada291b4f4d1b8592f53d1739c7a2e029011b5bc2624b979b0a544562a5e9 ./Qwythos-9B-Claude-Mythos-5-1M-MTP-Q8_0.gguf
7
+ 0de41ff56ab4eff26764437b276f0bd5d20f44232add34e14c4f593fa1aeb08f ./Qwythos-9B-Claude-Mythos-5-1M-Q4_K_M.gguf
8
+ 51dee6e6ddaeb08a06bee258ac5c58f4186f55d156d6403c2db67cf2f3226280 ./Qwythos-9B-Claude-Mythos-5-1M-Q5_K_M.gguf
9
+ 05f2420a669a83ae239d1328c6e83d9fc19e8a4b8dab5d0673cab28cc161dfc5 ./Qwythos-9B-Claude-Mythos-5-1M-Q6_K.gguf
10
+ ecf51ef3904694e04a1967a06fe7539619c34e6e81a721fc5f5415827081d8f6 ./Qwythos-9B-Claude-Mythos-5-1M-Q8_0.gguf
11
+ f977efc337a2ac2ba183eea0c73e25b75fc240d56c05ed4d9b56ab451f64c82c ./mmproj-Qwythos-9B-Claude-Mythos-5-1M-F16.gguf
TEST_REPORT.md ADDED
@@ -0,0 +1,53 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # Qwythos GGUF v2 release verification
2
+
3
+ Release verification was performed on 2026-06-22 with llama.cpp `d0f9d2e5ac5d4f51763755958b8f353fed01aaa2` and an NVIDIA RTX 5090.
4
+
5
+ ## Artifact manifest
6
+
7
+ | Artifact | Bytes | SHA-256 |
8
+ |---|---:|---|
9
+ | `Qwythos-9B-Claude-Mythos-5-1M-BF16.gguf` | 17,920,697,344 | `c49e2e419c0fc9f7cca0a7e0699fa3075fa1ec2913bda6f6841194b19cf4ce29` |
10
+ | `Qwythos-9B-Claude-Mythos-5-1M-Q4_K_M.gguf` | 5,629,109,248 | `0de41ff56ab4eff26764437b276f0bd5d20f44232add34e14c4f593fa1aeb08f` |
11
+ | `Qwythos-9B-Claude-Mythos-5-1M-Q5_K_M.gguf` | 6,467,970,048 | `51dee6e6ddaeb08a06bee258ac5c58f4186f55d156d6403c2db67cf2f3226280` |
12
+ | `Qwythos-9B-Claude-Mythos-5-1M-Q6_K.gguf` | 7,359,259,648 | `05f2420a669a83ae239d1328c6e83d9fc19e8a4b8dab5d0673cab28cc161dfc5` |
13
+ | `Qwythos-9B-Claude-Mythos-5-1M-Q8_0.gguf` | 9,527,501,824 | `ecf51ef3904694e04a1967a06fe7539619c34e6e81a721fc5f5415827081d8f6` |
14
+ | `Qwythos-9B-Claude-Mythos-5-1M-MTP-BF16.gguf` | 18,407,321,536 | `c704996e63c3e31a1e7040278b1204aabf8a6dad0b07f3c8da7b429d2ed30b31` |
15
+ | `Qwythos-9B-Claude-Mythos-5-1M-MTP-Q4_K_M.gguf` | 5,887,668,160 | `24ee22e0f5d9f0d3d615809607f365c728d9b0c3f3fb6eb19d8bd83a1c2933d8` |
16
+ | `Qwythos-9B-Claude-Mythos-5-1M-MTP-Q5_K_M.gguf` | 6,726,528,960 | `c4e3c47b17a93cc1566abcee4a0c9a4413b172a6f8be7f2a8824495907e9e893` |
17
+ | `Qwythos-9B-Claude-Mythos-5-1M-MTP-Q6_K.gguf` | 7,617,818,560 | `eae2adb4b451f673218fba96ebdc024fb95c4026ef35a56837dc9af47f99ca39` |
18
+ | `Qwythos-9B-Claude-Mythos-5-1M-MTP-Q8_0.gguf` | 9,786,060,736 | `34eada291b4f4d1b8592f53d1739c7a2e029011b5bc2624b979b0a544562a5e9` |
19
+ | `mmproj-Qwythos-9B-Claude-Mythos-5-1M-F16.gguf` | 918,165,472 | `f977efc337a2ac2ba183eea0c73e25b75fc240d56c05ed4d9b56ab451f64c82c` |
20
+
21
+ `shasum -a 256 -c SHA256SUMS` passed for all 11 GGUF artifacts after conversion and testing.
22
+
23
+ ## Structural checks
24
+
25
+ All ten text GGUFs passed these shared assertions:
26
+
27
+ - GGUF v3 and `qwen35` architecture;
28
+ - 1,048,576-token declared context;
29
+ - Qwen3.6-derived chat template markers present;
30
+ - fixed Qwythos/Empero AI identity instruction present.
31
+
32
+ The five normal v2 replacement files additionally verified as 32-block trunk-only GGUFs with no `nextn_predict_layers` key and no MTP tensors.
33
+
34
+ The five `-MTP-` v2 variants additionally verified as 33-block GGUFs with `qwen35.nextn_predict_layers = 1`, all 15 restored MTP tensors present, and MTP matrices retained at Q8_0 in every quantized variant.
35
+
36
+ The MTP tensors come from pinned Qwen3.5-9B base commit `c202236235762e1c871ad0ccb60c8ee5ba337b9a`. The source fine-tune declares one MTP layer but does not publish its MTP tensors. Only the draft head is restored; the Qwythos trunk and output layers remain unchanged.
37
+
38
+ ## Live tests
39
+
40
+ | Variant / mode | Identity | Generation | Tools | Other |
41
+ |---|---:|---:|---:|---|
42
+ | BF16 MTP | Pass | Pass | — | — |
43
+ | Q4_K_M MTP | Pass | Pass | Pass | Tool result round trip passed |
44
+ | Q5_K_M MTP | Pass | Pass | — | — |
45
+ | Q6_K MTP | Pass | Pass | — | — |
46
+ | Q8_0 MTP | Pass | Pass | Pass | Tool result round trip passed; no malformed output |
47
+ | Q4_K_M MTP + draft speculation | Pass | Pass | Pass | 76/150 draft tokens accepted (50.7%) |
48
+ | Q4_K_M MTP + 1M context | Pass | Pass | — | Server loaded `n_ctx = 1048576` |
49
+ | Q4_K_M MTP + F16 mmproj | Pass | Pass | — | Correctly identified a generated red-square image |
50
+
51
+ The normal v2 replacement files were rebuilt from the same fixed tokenizer/template source with `--no-mtp` and structurally verified after quantization. The 1M-context check verifies full context allocation and successful generation at that setting; it is not a million-token retrieval benchmark.
52
+
53
+ Machine-readable responses are in `reports/`; relevant llama.cpp logs are in `logs/`.
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:f977efc337a2ac2ba183eea0c73e25b75fc240d56c05ed4d9b56ab451f64c82c
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+ size 918165472
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+ oid sha256:f70dc3509053962b0d0d3ee8a7eacebf5d60aa560cad78254ae8698516ae029f
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