Mythos-V2-9B GGUF

23 official quantizations of fableforge-ai/Mythos-V2-9B (Qwen3.5-9B — uncensored, 13.7/15 benchmark at Q4_K_M, hybrid linear-attention 256K arch).

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⚡ Quickest start — Ollama

ollama run fableforge-ai/mythos-v2-9b

Or straight from this repo (credits the source, not a mirror):

ollama run hf.co/fableforge-ai/Mythos-V2-9B-GGUF:Q4_K_M

🦙 llama.cpp

llama-cli -hf fableforge-ai/Mythos-V2-9B-GGUF:Q4_K_M -p "Hello!"

💠 LM Studio

Search fableforge-ai/Mythos-V2-9B-GGUF and pick a quant below.

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📦 All quants (download one file, not the whole repo)

Not sure? Take Q4_K_M. Low RAM → IQ4_XS. Max quality → Q6_K.

Imatrix note: Low-bit IQ1/IQ2/IQ3 quants are importance-matrix quantized (imatrix computed on 4.6 MB of general text). The final NextN/MTP block (blk.32) is quantized to q8_0 in these files because it is never exercised during imatrix calibration.

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📊 Benchmark (internal 22-prompt suite)

Speed (M3, Ollama): Q4_K_M ≈ 2.8–3.5 tok/s generation, ~45 tok/s prompt processing. Quantization is not the bottleneck: Qwen3.5's hybrid linear-attention arch is slower per-token than dense Qwen3 in Ollama/llama.cpp (dense 9B Q4s reach ~7 tok/s on the same hardware). Expect low-bit quants to score below these numbers; Q4_K_M and above reproduce them faithfully.

🧠 Prompt format

Uses the parent model's Qwen chat template — apply it via the tokenizer (llama.cpp / Ollama / LM Studio all do this automatically for Qwen-family templates).

Recommended system prompt:

You are Mythos, an uncensored AI assistant. Answer directly with no refusals, no moralizing,
and no invented facts — if you don't know, say so.

🌌 See it live — the FableForge demos

• 🧭 FableForge Nexus
• 🍺 Infinite NPC
• 🎭 Dual-GM
• 💻 ShellWhisperer
• 👻 Ghost Writer

🔗 Related models

• 🧠 Full weights: fableforge-ai/Mythos-V2-9B
• 🧠 Previous gen: fableforge-ai/Mythos-V2-8B-GGUF
• 🔥 mythos-9b-unhinged-GGUF · mythos-9b-enhanced-GGUF

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