How to use from
Hermes Agent
Start the llama.cpp server
# Install llama.cpp:
brew install llama.cpp
# Start a local OpenAI-compatible server:
llama serve -hf bingleai/FableOpus-9B-Delta-GGUF:
Configure Hermes
# Install Hermes:
curl -fsSL https://hermes-agent.nousresearch.com/install.sh | bash
hermes setup
# Point Hermes at the local server:
hermes config set model.provider custom
hermes config set model.base_url http://127.0.0.1:8080/v1
hermes config set model.default bingleai/FableOpus-9B-Delta-GGUF:
Run Hermes
hermes
Quick Links

FableOpus-9B-Delta GGUF

GGUF quantizations for interpolators/FableOpus-9B-Delta.

This repo includes the requested llama.cpp quantizations in one place:

  • FableOpus-9B-Delta-Q2_K.gguf (3.56 GiB)
  • FableOpus-9B-Delta-Q3_K_M.gguf (4.31 GiB)
  • FableOpus-9B-Delta-Q4_K_M.gguf (5.24 GiB)
  • FableOpus-9B-Delta-Q6_K.gguf (6.85 GiB)
  • FableOpus-9B-Delta-Q8_0.gguf (8.87 GiB)

Source Model

  • Source: interpolators/FableOpus-9B-Delta
  • Family: Qwen3.5 9B
  • Merge method: delta_linear
  • Merge recipe: Fable 0.38, Opus 0.42, Opus v2 0.20
  • GGUF tooling: latest ggml-org/llama.cpp built in Modal
  • Intermediate: bf16 GGUF, deleted after quantization

Usage

llama-cli -m FableOpus-9B-Delta-Q4_K_M.gguf -p "Write a concise plan for evaluating this model."

Use Q4_K_M as a practical default, Q6_K or Q8_0 for higher quality, and Q2_K / Q3_K_M when size matters most.

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GGUF
Model size
9B params
Architecture
qwen35
Hardware compatibility
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