Image-Text-to-Text
GGUF
llama.cpp
qwen
qwen3.8
qwen3.8-flash-next
amd
rocm
gfx1151
ryzen-ai-max-395
strix-halo
mixture-of-experts
iu4
mtp
speculative-decoding
nvme
ple
long-context
local-inference
vision
conversational
Instructions to use jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- llama.cpp
How to use jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4 with llama.cpp:
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh # Start a local OpenAI-compatible server with a web UI: llama serve -hf jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4:Q8_0 # Run inference directly in the terminal: llama cli -hf jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4:Q8_0
Install from WinGet (Windows)
winget install llama.cpp # Start a local OpenAI-compatible server with a web UI: llama serve -hf jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4:Q8_0 # Run inference directly in the terminal: llama cli -hf jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4:Q8_0
Use pre-built binary
# Download pre-built binary from: # https://github.com/ggerganov/llama.cpp/releases # Start a local OpenAI-compatible server with a web UI: ./llama-server -hf jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4:Q8_0 # Run inference directly in the terminal: ./llama-cli -hf jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4:Q8_0
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git cd llama.cpp cmake -B build cmake --build build -j --target llama-server llama-cli # Start a local OpenAI-compatible server with a web UI: ./build/bin/llama-server -hf jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4:Q8_0 # Run inference directly in the terminal: ./build/bin/llama-cli -hf jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4:Q8_0
Use Docker
docker model run hf.co/jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4:Q8_0
- LM Studio
- Jan
- vLLM
How to use jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4:Q8_0
- Ollama
How to use jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4 with Ollama:
ollama run hf.co/jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4:Q8_0
- Unsloth Desktop
- Pi
How to use jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4 with Pi:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4:Q8_0
Configure the model in Pi
# Install Pi: npm install -g @earendil-works/pi-coding-agent # Add to ~/.pi/agent/models.json: { "providers": { "llama-cpp": { "baseUrl": "http://localhost:8080/v1", "api": "openai-completions", "apiKey": "none", "models": [ { "id": "jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4:Q8_0" } ] } } }Run Pi
# Start Pi in your project directory: pi
- Docker Model Runner
How to use jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4 with Docker Model Runner:
docker model run hf.co/jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4:Q8_0
- Lemonade
How to use jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4 with Lemonade:
Pull the model
# Download Lemonade from https://lemonade-server.ai/ lemonade pull jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4:Q8_0
Run and chat with the model
lemonade run user.Qwen3.8-Flash-CIRU-STRIX-IU4-Q8_0
List all available models
lemonade list
- Hermes Agent
How to use jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4 with Hermes Agent:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4:Q8_0
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 jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4:Q8_0
Run Hermes
hermes
- Atomic Chat
- OpenClaw
How to use jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4 with OpenClaw:
Start the llama.cpp server
# Install llama.cpp: brew install llama.cpp # Start a local OpenAI-compatible server: llama serve -hf jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4:Q8_0
Configure OpenClaw
# Install OpenClaw: npm install -g openclaw@latest # Register the local server and set it as the default model: openclaw onboard --non-interactive --mode local \ --auth-choice custom-api-key \ --custom-base-url http://127.0.0.1:8080/v1 \ --custom-model-id "jcbtc/Qwen3.8-Flash-CIRU-STRIX-IU4:Q8_0" \ --custom-provider-id llama-cpp \ --custom-compatibility openai \ --custom-text-input \ --accept-risk \ --skip-health
Run OpenClaw
openclaw agent --local --agent main --message "Hello from Hugging Face"
| { | |
| "iu4": { | |
| "incident": { | |
| "baseline_tg": 21.350579495494976, | |
| "candidate_tg": 37.67012469837982, | |
| "gain_percent": 76.43607615581726, | |
| "mirror_gain_percent": [ | |
| 75.26914202822906, | |
| 77.60025663606757 | |
| ], | |
| "mirror_gap_points": 2.331114607838515, | |
| "prompt_tokens": 12960, | |
| "acceptance": { | |
| "A1": { | |
| "accepted": 329, | |
| "drafted": 1085 | |
| }, | |
| "C1": { | |
| "accepted": 362, | |
| "drafted": 444 | |
| }, | |
| "C2": { | |
| "accepted": 362, | |
| "drafted": 444 | |
| }, | |
| "A2": { | |
| "accepted": 329, | |
| "drafted": 1085 | |
| } | |
| }, | |
| "status": "NARROW_PENDING_MODEL_QUALIFICATION" | |
| }, | |
| "source-review": { | |
| "baseline_tg": 22.244778256121172, | |
| "candidate_tg": 30.954780957141466, | |
| "gain_percent": 39.15526871401171, | |
| "mirror_gain_percent": [ | |
| 39.62234502629596, | |
| 38.69308478438438 | |
| ], | |
| "mirror_gap_points": 0.9292602419115781, | |
| "prompt_tokens": 3329, | |
| "acceptance": { | |
| "A1": { | |
| "accepted": 324, | |
| "drafted": 1121 | |
| }, | |
| "C1": { | |
| "accepted": 315, | |
| "drafted": 583 | |
| }, | |
| "C2": { | |
| "accepted": 315, | |
| "drafted": 583 | |
| }, | |
| "A2": { | |
| "accepted": 324, | |
| "drafted": 1121 | |
| } | |
| }, | |
| "status": "NARROW_PENDING_MODEL_QUALIFICATION" | |
| } | |
| }, | |
| "orca": { | |
| "selected": { | |
| "depth": 4, | |
| "LLAMA_MTP_QSA_MIN_T": 1, | |
| "draft_p_min": 0 | |
| }, | |
| "workloads": { | |
| "incident": { | |
| "control_tg": 37.56460367523702, | |
| "candidate_tg": 38.30411707417262, | |
| "gain_percent": 1.9686442197794252, | |
| "control_pp": 991.7686265014659, | |
| "candidate_pp": 995.9648820938194, | |
| "pair_gains_percent": [ | |
| 2.3038325154211448, | |
| 1.6338616801269135 | |
| ], | |
| "mirror_gap_points": 0.6699708352942313, | |
| "control_acceptance": 0.6623376623376623, | |
| "candidate_acceptance": 0.8179916317991632 | |
| }, | |
| "source-review": { | |
| "control_tg": 24.249480937725053, | |
| "candidate_tg": 27.841974293466993, | |
| "gain_percent": 14.814722694344674, | |
| "control_pp": 854.5405843245323, | |
| "candidate_pp": 803.1933752591107, | |
| "pair_gains_percent": [ | |
| 13.502375238681918, | |
| 16.14210887575236 | |
| ], | |
| "mirror_gap_points": 2.6397336370704405, | |
| "control_acceptance": 0.32122370936902483, | |
| "candidate_acceptance": 0.4199475065616798 | |
| }, | |
| "inventory": { | |
| "control_tg": 19.58849066156083, | |
| "candidate_tg": 24.730783521796663, | |
| "gain_percent": 26.25160329645373, | |
| "control_pp": 207.92221923165724, | |
| "candidate_pp": 218.44565862706233, | |
| "pair_gains_percent": [ | |
| 26.364382670543506, | |
| 26.138606024076672 | |
| ], | |
| "mirror_gap_points": 0.22577664646683537, | |
| "control_acceptance": 0.21236959761549926, | |
| "candidate_acceptance": 0.31520532741398444 | |
| } | |
| }, | |
| "qualifier": "Same host, production sampler/context/weights, fixed 512-token probes. Quality validation follows separately.", | |
| "metadata_correction": "Historical screen/confirmation output model alias and base profile hash remained IU4; actual Orca model and MTP paths, size/mtime, and native server_props.model_path verify Orca weights. New quality session uses corrected Orca alias and actual profile hash. Raw historical rows preserved.", | |
| "geomean_tg_gain_percent": 13.911361508316912, | |
| "decision": "Use depth4/sparse for requested full quality and garden runs; deployment awaits quality review. No further sweep." | |
| } | |
| } | |