Ready-to-arrange model bundle for the R9V dual-RDNA4 inference profile.
target/: Unsloth UD-IQ4_XS target GGUF shards from
unsloth/Qwen3.8-Flash-Next-GGUF.vision/: ggml-org Q8_0 vision projector. This projector was not quantized
by R9V.mtp/: R9V-assembled minimal MTP checkpoint. Dense/nonexpert tensors come
from the official BF16 checkpoint; routed experts come from the official
block-FP8 checkpoint. R9V did not train these weights.metadata/: official Qwen tokenizer, processor, and model configuration.manifests/: the reference dual-R9700 hot-expert placement.sources.lock.json: exact upstream revisions, sizes, and hashes.Unsloth and ggml-org are credited for the target quantization and vision projector. Qwen remains the model author and upstream rights holder.
The 26.82 GiB per_layer_token_embd.weight payload is already present inside
target shard 2 and is intentionally not uploaded again. Extract it to the fast
SSD with R9V's metadata-driven tool. The extraction utility is shipped in the
R9V source repository, not this model repository; follow the complete
build, extraction, and launch instructions.
The immutable 22-file model package is public and remotely hash-verified. The R9V runtime has passed its reference-machine performance qualification and remains a release candidate until the documented package installation passes from a clean host. See the R9V qualification report for exact benchmark cells and protocol.
These model artifacts are distributed under Qwen Community License 1.0; see
LICENSE. The R9V Apache-2.0 code license does not apply to model weights.
Users are responsible for reviewing the Qwen license, including its separate
terms for certain commercial MaaS/AI-work-assistant uses and scale thresholds.
Artifact attribution and exact upstream revisions are recorded in
THIRD_PARTY_NOTICES.md.
Ready-to-arrange model bundle for the R9V dual-RDNA4 inference profile.
target/: Unsloth UD-IQ4_XS target GGUF shards from
unsloth/Qwen3.8-Flash-Next-GGUF.vision/: ggml-org Q8_0 vision projector. This projector was not quantized
by R9V.mtp/: R9V-assembled minimal MTP checkpoint. Dense/nonexpert tensors come
from the official BF16 checkpoint; routed experts come from the official
block-FP8 checkpoint. R9V did not train these weights.metadata/: official Qwen tokenizer, processor, and model configuration.manifests/: the reference dual-R9700 hot-expert placement.sources.lock.json: exact upstream revisions, sizes, and hashes.Unsloth and ggml-org are credited for the target quantization and vision projector. Qwen remains the model author and upstream rights holder.
The 26.82 GiB per_layer_token_embd.weight payload is already present inside
target shard 2 and is intentionally not uploaded again. Extract it to the fast
SSD with R9V's metadata-driven tool. The extraction utility is shipped in the
R9V source repository, not this model repository; follow the complete
build, extraction, and launch instructions.
The immutable 22-file model package is public and remotely hash-verified. The R9V runtime has passed its reference-machine performance qualification and remains a release candidate until the documented package installation passes from a clean host. See the R9V qualification report for exact benchmark cells and protocol.
These model artifacts are distributed under Qwen Community License 1.0; see
LICENSE. The R9V Apache-2.0 code license does not apply to model weights.
Users are responsible for reviewing the Qwen license, including its separate
terms for certain commercial MaaS/AI-work-assistant uses and scale thresholds.
Artifact attribution and exact upstream revisions are recorded in
THIRD_PARTY_NOTICES.md.