Recipe

qwen35-9b-q4km-rtx4080-llamacpp-tp1

qwen35-9b-q4km-rtx4080-llamacpp-tp1

Candidate derived from lfm2-5-8b-a1b-q4-k-m-rtx-3060-ti-8gb-llama-cpp-tp1 for rtx-4080-16gb; the launch contract is copied, the evidence is not. Pending acceptance on the target card.

Record

Status
validated
Source
0xsero
Engine
llama.cpp
Engine version
b9653 / 9dbc6621a
Accelerators
1
Tensor parallel
1
Context tokens
65,536
chat
unknown
reasoning
unknown
tools
unknown
vision
unknown

Hugging Face model card

Identity

https://huggingface.co/unsloth/Qwen3.5-9B-GGUF
Repository
unsloth/Qwen3.5-9B-GGUF
Status
known
Link type
Exact Hub repository

Public Hugging Face repository confirmed by the Hub API.

Validated: pinned artifact, pinned runtime, and accepted evidence. This is a launch contract.

Docker configuration

llama.cpp

Container · validated · docker

Validated launch contract

Image
ghcr.io/ggml-org/llama.cpp:server-cuda12-b10481@sha256:b2497f8834f5ecb4e38530f6bf2734b8e0be107ff48e4720145911c86930f2ce
Digest
sha256:b2497f8834f5ecb4e38530f6bf2734b8e0be107ff48e4720145911c86930f2ce
Port
8080

Launch arguments

  1. -hf
  2. unsloth/Qwen3.5-9B-GGUF
  3. --n-gpu-layers
  4. 999
  5. --host
  6. 0.0.0.0
  7. --port
  8. 8080
  9. -c
  10. 65536
FlagValue
-hfunsloth/Qwen3.5-9B-GGUF
--n-gpu-layers999
--host0.0.0.0
--port8080
-c65536

Environment

VariableValue
LLAMA_CACHE/root/.cache/huggingface

Mounts

SourceTarget
~/.cache/huggingface/root/.cache/huggingface

Launch

Exact materialization of this validated launch contract: digest-pinned image, pinned model revision, and the audited arguments. Self-contained — required assets are fetched from this registry and verified against their recorded sha256 before mounting. Also available as local-ai run qwen35-9b-q4km-rtx4080-llamacpp-tp1.

  1. Pulls the exact container image by sha256 digest — the bytes that were validated, not a floating tag.
  2. Fetches any required engine assets from this registry and verifies each against its recorded sha256; the audited launch script verifies them again inside the container before use.
  3. Downloads the pinned model revision into your Hugging Face cache on first run (reused afterwards).
  4. Serves an OpenAI-compatible API on localhost:8080 — point any client at it.
docker run --rm \
  --gpus all \
  --shm-size 16g \
  -p 8080:8080 \
  -e LLAMA_CACHE=/root/.cache/huggingface \
  -v ~/.cache/huggingface:/root/.cache/huggingface \
  --entrypoint /app/llama-server \
  ghcr.io/ggml-org/llama.cpp:server-cuda12-b10481@sha256:b2497f8834f5ecb4e38530f6bf2734b8e0be107ff48e4720145911c86930f2ce \
  -hf \
  unsloth/Qwen3.5-9B-GGUF \
  --n-gpu-layers \
  999 \
  --host \
  0.0.0.0 \
  --port \
  8080 \
  -c \
  65536

Measured speed

ConcurrencyContextPrefillDecodeTTFT msStatusSweep
165,536—102.1451.7acceptedqwen35-9b-q4km-rtx4080-llamacpp-tp1-acceptance

Remaining fields

Identity, launch, related records, and measured speed are shown above. This is the rest of the normalized record.

hardware count
1
hardware id
rtx-4080-16gb
id
qwen35-9b-q4km-rtx4080-llamacpp-tp1
model instance id
unsloth-qwen3-5-9b-gguf--q4-k-m
recipe source
0xsero
schema version
local-ai-registry/v1
speed sweep ids
qwen35-9b-q4km-rtx4080-llamacpp-tp1-acceptance
status
validated

capabilities

engine

name
llama.cpp
version
b9653 / 9dbc6621a

serving

max context tokens
65,536
tensor parallel
1
Provenance & metadata (3)

facts

metadata

acceptance · accepted at
2026-09-02T16:59:20Z
acceptance · harness
validate_rented.py on vast RTX 4080
acceptance · served model id
unsloth/Qwen3.5-9B-GGUF
derived from
lfm2-5-8b-a1b-q4-k-m-rtx-3060-ti-8gb-llama-cpp-tp1

provenance

captured at
2026-09-02T16:35:13Z

sources

captured atkindurl
2026-09-02T16:35:13Znormalized-recipegithub.com/0xSero/local-ai-registry ↗