From: Ettore Di Giacinto <redacted>
Date: Wed, 1 Apr 2026 09:50:17 +0000 (+0200)
Subject: memory: respect unified KV cache in hybrid memory for eval tasks (#21224)
X-Git-Tag: upstream/0.0.8681~68
X-Git-Url: https://git.djapps.eu/?a=commitdiff_plain;h=e1cb817483ebda4e3ebc30fd07f4292c654f4339;p=pkg%2Fggml%2Fsources%2Fllama.cpp

memory: respect unified KV cache in hybrid memory for eval tasks (#21224)

The hybrid memory paths (`llama-memory-hybrid.cpp` and
`llama-memory-hybrid-iswa.cpp`) always used sequential equal split,
ignoring the unified KV cache flag. This caused hellaswag, winogrande,
and multiple-choice evaluations to fail on hybrid models (models with
both attention and recurrent/SSM layers, such as Qwen3.5-35B-A3B) with:

  split_equal: sequential split is not supported when there are
  coupled sequences in the input batch (you may need to use the
  -kvu flag)

PR #19954 fixed this for `llama-kv-cache-iswa.cpp` by automatically
enabling unified KV mode and setting n_parallel >= 4 for multi-choice
eval tasks. However, the hybrid memory paths were not updated.

This commit mirrors the iswa fix: use non-sequential split when KV
cache is unified (n_stream == 1), which is automatically set by
llama-perplexity for hellaswag/winogrande/multiple-choice since #19954.

Tested on Qwen3.5-35B-A3B (hybrid attention+SSM MoE model):
- HellaSwag: 83.0% (400 tasks)
- Winogrande: 74.5% (400 tasks)
- MMLU: 41.2%
- ARC-Challenge: 56.2%
- TruthfulQA: 37.7%
All previously failed with llama_decode() error.
---

diff --git a/src/llama-memory-hybrid-iswa.cpp b/src/llama-memory-hybrid-iswa.cpp
index 411769672..10e6b4597 100644
--- a/src/llama-memory-hybrid-iswa.cpp
+++ b/src/llama-memory-hybrid-iswa.cpp
@@ -73,9 +73,9 @@ llama_memory_context_ptr llama_memory_hybrid_iswa::init_batch(llama_batch_allocr
                 // if all tokens are output, split by sequence
                 ubatch = balloc.split_seq(n_ubatch);
             } else {
-                // TODO: non-sequential equal split can be done if using unified KV cache
-                //       for simplicity, we always use sequential equal split for now
-                ubatch = balloc.split_equal(n_ubatch, true);
+                // Use non-sequential split when KV cache is unified (needed for hellaswag/winogrande/multiple-choice)
+                const bool unified = (mem_attn->get_base()->get_n_stream() == 1);
+                ubatch = balloc.split_equal(n_ubatch, !unified);
             }
 
             if (ubatch.n_tokens == 0) {
diff --git a/src/llama-memory-hybrid.cpp b/src/llama-memory-hybrid.cpp
index a1b45e4a3..4ce1af592 100644
--- a/src/llama-memory-hybrid.cpp
+++ b/src/llama-memory-hybrid.cpp
@@ -73,9 +73,9 @@ llama_memory_context_ptr llama_memory_hybrid::init_batch(llama_batch_allocr & ba
                 // if all tokens are output, split by sequence
                 ubatch = balloc.split_seq(n_ubatch);
             } else {
-                // TODO: non-sequential equal split can be done if using unified KV cache
-                //       for simplicity, we always use sequential equal split for now
-                ubatch = balloc.split_equal(n_ubatch, true);
+                // Use non-sequential split when KV cache is unified (needed for hellaswag/winogrande/multiple-choice)
+                const bool unified = (mem_attn->get_n_stream() == 1);
+                ubatch = balloc.split_equal(n_ubatch, !unified);
             }
 
             if (ubatch.n_tokens == 0) {