b11223

server : allow RANK pooling batch splitting for causal LLM rerankers (ie. Qwen3 and Qwen3-VL) (#28876)

• server : allow splitting RANK pooling for causal LLM rerankers

Rerank models fall into two categories: bidirectional cross-encoders
(BERT, etc.) that require all tokens in a single physical batch, and
causal LLMs repurposed as rerankers (Qwen3, Qwen3-VL) that can use
chunked prefill like any other decoder.

Previously the server rejected all RANK-pooling inputs larger than
n_ubatch, and the graph builder hardcoded QWEN3/QWEN3VL arch checks to
determine last-token pooling. This broke long-document and multimodal
reranking for causal models.

Fix: expose llama_get_causal_attn(ctx) so the server can check the
effective runtime attention type (reflecting any --attention override
or set_causal_attn call). Also expose llama_model_is_causal(model)
for querying the static architectural property from GGUF metadata.

can_split() now permits chunked prefill for RANK pooling when the
context is causal. The graph builder's inline arch check is replaced
with the same cparams.causal_attn predicate, removing the duplication.

Assisted-by: Opencode/Qwen3.8-27B

• remove unused llama_model_is_causal, fix whitespace

Assisted-by: opencode

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Co-authored-by: timothywang21 [email protected]

Website:

• https://llama.app

Attestations:

• https://github.com/ggml-org/llama.cpp/attestations/50611983

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• Windows x64 (Vulkan)
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• UI