From e28cec364ef98fb790b8df2ff573eefa153009c8 Mon Sep 17 00:00:00 2001
From: Georgi Gerganov <ggerganov@gmail.com>
Date: Tue, 28 Oct 2025 09:26:16 +0200
Subject: [PATCH] memory : remove KV cache size padding

---
 src/llama-kv-cache.cpp |  5 -----
 src/llama-kv-cache.h   |  2 --
 src/llama-model.cpp    | 23 ++++-------------------
 src/llama-model.h      |  3 +--
 4 files changed, 5 insertions(+), 28 deletions(-)

diff --git a/src/llama-kv-cache.cpp b/src/llama-kv-cache.cpp
index 736693e174..0b97d8a344 100644
--- a/src/llama-kv-cache.cpp
+++ b/src/llama-kv-cache.cpp
@@ -2010,8 +2010,3 @@ void llama_kv_cache_context::set_input_kq_mask(ggml_tensor * dst, const llama_ub
 void llama_kv_cache_context::set_input_pos_bucket(ggml_tensor * dst, const llama_ubatch * ubatch) const {
     kv->set_input_pos_bucket(dst, ubatch);
 }
-
-uint32_t llama_kv_cache::get_padding(const llama_cparams & cparams) {
-    // the FA kernels require padding to avoid extra runtime boundary checks
-    return cparams.flash_attn ? 256u : 32u;
-}
diff --git a/src/llama-kv-cache.h b/src/llama-kv-cache.h
index 85f0663d8c..698de64f87 100644
--- a/src/llama-kv-cache.h
+++ b/src/llama-kv-cache.h
@@ -19,8 +19,6 @@ struct llama_context;
 
 class llama_kv_cache : public llama_memory_i {
 public:
-    static uint32_t get_padding(const llama_cparams & cparams);
-
     struct stream_copy_info {
         bool empty() const {
             assert(ssrc.size() == sdst.size());
diff --git a/src/llama-model.cpp b/src/llama-model.cpp
index 05e4671800..0d5aae51fa 100644
--- a/src/llama-model.cpp
+++ b/src/llama-model.cpp
@@ -19641,7 +19641,7 @@ struct llm_build_apertus : public llm_graph_context {
     }
 };
 
-llama_memory_i * llama_model::create_memory(const llama_memory_params & params, llama_cparams & cparams) const {
+llama_memory_i * llama_model::create_memory(const llama_memory_params & params, const llama_cparams & cparams) const {
     llama_memory_i * res;
 
     switch (arch) {
@@ -19692,17 +19692,13 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
                         };
                     }
 
-                    const auto padding = llama_kv_cache::get_padding(cparams);
-
-                    cparams.n_ctx = GGML_PAD(cparams.n_ctx, padding);
-
                     res = new llama_memory_hybrid(
                         /* model             */ *this,
                         /* attn_type_k       */ params.type_k,
                         /* attn_type_v       */ params.type_v,
                         /* attn_v_trans      */ !cparams.flash_attn,
                         /* attn_kv_size      */ cparams.n_ctx,
-                        /* attn_n_pad        */ padding,
+                        /* attn_n_pad        */ 1,
                         /* attn_n_swa        */ hparams.n_swa,
                         /* attn_swa_type     */ hparams.swa_type,
                         /* recurrent_type_k  */ GGML_TYPE_F32,
@@ -19714,23 +19710,12 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
                         /* filter_attn       */ std::move(filter_attn),
                         /* filter_recr       */ std::move(filter_recr));
                 } else {
-                    const auto padding = llama_kv_cache::get_padding(cparams);
-
                     uint32_t n_ctx_per_stream = cparams.n_ctx;
 
                     if (!cparams.kv_unified) {
                         n_ctx_per_stream = (cparams.n_ctx + cparams.n_seq_max - 1)/cparams.n_seq_max;
-                        n_ctx_per_stream = GGML_PAD(n_ctx_per_stream, padding);
-
-                        cparams.n_ctx = n_ctx_per_stream*cparams.n_seq_max;
-                    } else {
-                        n_ctx_per_stream = GGML_PAD(n_ctx_per_stream, padding);
-
-                        cparams.n_ctx = n_ctx_per_stream;
                     }
 
-                    LLAMA_LOG_DEBUG("%s: n_ctx = %u (padded)\n", __func__, cparams.n_ctx);
-
                     llama_memory_i::layer_reuse_cb reuse = nullptr;
 
                     if (arch == LLM_ARCH_GEMMA3N) {
@@ -19757,7 +19742,7 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
                                 n_ctx_per_stream,
                                 cparams.n_seq_max,
                                 cparams.n_ubatch,
-                                padding,
+                                1,
                                 nullptr,
                                 reuse);
                     } else {
@@ -19772,7 +19757,7 @@ llama_memory_i * llama_model::create_memory(const llama_memory_params & params,
                                 cparams.kv_unified,
                                 n_ctx_per_stream,
                                 cparams.n_seq_max,
-                                padding,
+                                1,
                                 hparams.n_swa,
                                 hparams.swa_type,
                                 nullptr,
diff --git a/src/llama-model.h b/src/llama-model.h
index 248f854101..1ab1cf7f8e 100644
--- a/src/llama-model.h
+++ b/src/llama-model.h
@@ -500,9 +500,8 @@ struct llama_model {
 
     ggml_tensor * get_rope_factors(const llama_cparams & cparams, int il) const;
 
-    // note: can mutate `cparams`
     // TODO: move this to new llm_arch_model_i interface
-    llama_memory_i * create_memory(const llama_memory_params & params, llama_cparams & cparams) const;
+    llama_memory_i * create_memory(const llama_memory_params & params, const llama_cparams & cparams) const;
 
     // TODO: move this to new llm_arch_model_i interface
     ggml_cgraph * build_graph(const llm_graph_params & params) const;