diff --git a/API.md b/API.md
index 2cc189b..73a5d40 100644
--- a/API.md
+++ b/API.md
@@ -108,8 +108,8 @@ The following keys are available in context_settings:
 
 | Key                      | Type     | Meaning                                                          |
 | ------------------------ | -------- | ---------------------------------------------------------------- |
-| `context_size`           | `number` | Equivalent to n_ctx = N and n_batch = N.                         |
-| `n_ctx`                  | `number` | Text context length (tokens). `0` = from model.                  |
+| `context_size`           | `number` | Equivalent to `n_ctx = N` and `n_batch = N`. `0` = use the model's training window. |
+| `n_ctx`                  | `number` | Text context length (tokens). `0` = use the model's training window.               |
 | `n_batch`                | `number` | **Logical** max batch size submitted to `llama_decode`.          |
 | `n_ubatch`               | `number` | **Physical** max micro-batch size.                               |
 | `n_seq_max`              | `number` | Max concurrent sequences (parallel states for recurrent models). |
@@ -199,7 +199,10 @@ SELECT llm_context_create_embedding();
 **Description:**
 Creates a new inference context specifically set for chat conversation.
 
-It is equivalent to `SELECT llm_context_create('context_size=4096');`
+It applies no context settings of its own, so anything you do not pass is
+llama.cpp's default — in particular the context length defaults to the model's
+training window (`llm_model_n_ctx_train()`), not to a fixed size. Pass
+`context_size` to bound it, and use `llm_context_size()` to confirm what you got.
 
 Context must explicitly created before performing any AI operation!
 
@@ -220,7 +223,10 @@ SELECT llm_context_create_chat();
 **Description:**
 Creates a new inference context specifically set for text generation.
 
-It is equivalent to `SELECT llm_context_create('context_size=4096');`
+It applies no context settings of its own, so anything you do not pass is
+llama.cpp's default — in particular the context length defaults to the model's
+training window (`llm_model_n_ctx_train()`), not to a fixed size. Pass
+`context_size` to bound it, and use `llm_context_size()` to confirm what you got.
 
 Context must explicitly created before performing any AI operation!
 
diff --git a/src/sqlite-ai.c b/src/sqlite-ai.c
index a20e9b8..263f742 100644
--- a/src/sqlite-ai.c
+++ b/src/sqlite-ai.c
@@ -511,8 +511,8 @@ static bool llm_context_options_callback (void *ctx, void *xdata, const char *ke
     if (KEY_MATCHES(key, key_len, OPTION_KEY_CONTEXT_SIZE)) {
         int value = (int)strtol(buffer, NULL, 0);
         if (value >= 0) {
-            options->n_ctx = value;
-            options->n_batch = value;
+            options->n_ctx = value;                     // 0 = use the model's training window
+            if (value > 0) options->n_batch = value;    // never drive n_batch to 0
         }
         return true;
     }
@@ -2724,6 +2724,14 @@ static void llm_context_free (sqlite3_context *context, int argc, sqlite3_value
 
 static bool llm_context_create_with_options (sqlite3_context *context, ai_context *ai, const char *options1, const char *options2) {
     struct llama_context_params ctx_params = llama_context_default_params();
+
+    // n_ctx = 0 tells llama.cpp to use the model's training window. Start from it so
+    // that "the caller did not ask for a context size" is an explicit sentinel rather
+    // than something inferred after the fact from the value: llama's own default is
+    // 512, so an explicit context_size=512 used to be indistinguishable from unset and
+    // was silently replaced by n_ctx_train.
+    ctx_params.n_ctx = 0;
+
     if (parse_keyvalue_string(ai, options1, llm_context_options_callback, &ctx_params) == false) {
         sqlite_context_result_error(context, SQLITE_ERROR, "An error occurred while parsing options (%s)", options1);
         return false;
@@ -2742,13 +2750,6 @@ static bool llm_context_create_with_options (sqlite3_context *context, ai_contex
         return false;
     }
 
-    // auto-size n_ctx to the model's training window when no explicit context_size was set
-    // llama_context_default_params() sets n_ctx=512; setting n_ctx=0 tells llama.cpp to use n_ctx_train
-    struct llama_context_params defaults = llama_context_default_params();
-    if (ai->model && ctx_params.n_ctx == defaults.n_ctx) {
-        ctx_params.n_ctx = 0;
-    }
-
     // for embedding contexts, clamp n_ctx to n_ctx_train to avoid position overflow
     if (ctx_params.embeddings && ai->model) {
         int n_ctx_train = llama_model_n_ctx_train(ai->model);
diff --git a/src/sqlite-ai.h b/src/sqlite-ai.h
index a710ed5..713d066 100644
--- a/src/sqlite-ai.h
+++ b/src/sqlite-ai.h
@@ -24,7 +24,7 @@
 extern "C" {
 #endif
 
-#define SQLITE_AI_VERSION "1.0.5"
+#define SQLITE_AI_VERSION "1.0.6"
 
 SQLITE_AI_API int sqlite3_ai_init (sqlite3 *db, char **pzErrMsg, const sqlite3_api_routines *pApi);
 
diff --git a/tests/c/unittest.c b/tests/c/unittest.c
index 8868a35..963959b 100644
--- a/tests/c/unittest.c
+++ b/tests/c/unittest.c
@@ -607,6 +607,81 @@ static int test_llm_context_size_errors(const test_env *env) {
     return 1;
 }
 
+// Regression: an explicit context_size=512 collided with the value
+// llama_context_default_params() uses for n_ctx, so it was read as "the caller did
+// not ask" and silently replaced by the model's training window - 32768 for the test
+// model, 64x what was requested.
+static int test_context_size_is_honoured(const test_env *env) {
+    sqlite3 *db = NULL;
+    if (open_db_and_load(env, &db) != SQLITE_OK) return 1;
+
+    const char *model = env->model_path ? env->model_path : DEFAULT_MODEL_PATH;
+    char sqlbuf[512];
+    snprintf(sqlbuf, sizeof(sqlbuf), "SELECT llm_model_load('%s');", model);
+    if (exec_expect_ok(env, db, sqlbuf) != 0) goto fail;
+
+    int n_ctx_train = 0;
+    if (select_single_int(env, db, "SELECT llm_model_n_ctx_train();", &n_ctx_train) != 0) goto fail;
+    if (n_ctx_train <= 1024) {
+        fprintf(stderr, "[context_size_is_honoured] model trains at %d, too small to tell a "
+                        "honoured context_size from an auto-sized one\n", n_ctx_train);
+        goto fail;
+    }
+
+    // llama pads n_ctx up to a multiple of 256, so only exact multiples compare equal.
+    // 512 is the regression; the others guard against over-correcting.
+    const int sizes[] = {256, 512, 1024};
+    for (size_t i = 0; i < sizeof(sizes) / sizeof(sizes[0]); ++i) {
+        snprintf(sqlbuf, sizeof(sqlbuf), "SELECT llm_context_create_chat('context_size=%d');", sizes[i]);
+        if (exec_expect_ok(env, db, sqlbuf) != 0) goto fail;
+        int n_ctx = 0;
+        if (select_single_int(env, db, "SELECT llm_context_size();", &n_ctx) != 0) goto fail;
+        if (env->verbose) printf("[context_size_is_honoured] asked %d, got %d\n", sizes[i], n_ctx);
+        if (n_ctx != sizes[i]) {
+            fprintf(stderr, "[context_size_is_honoured] context_size=%d produced n_ctx=%d\n", sizes[i], n_ctx);
+            goto fail;
+        }
+        if (exec_expect_ok(env, db, "SELECT llm_context_free();") != 0) goto fail;
+    }
+
+    // n_ctx= is the other spelling of the same thing and hit the same collision
+    if (exec_expect_ok(env, db, "SELECT llm_context_create_chat('n_ctx=512');") != 0) goto fail;
+    int n_ctx = 0;
+    if (select_single_int(env, db, "SELECT llm_context_size();", &n_ctx) != 0) goto fail;
+    if (n_ctx != 512) {
+        fprintf(stderr, "[context_size_is_honoured] n_ctx=512 produced n_ctx=%d\n", n_ctx);
+        goto fail;
+    }
+    if (exec_expect_ok(env, db, "SELECT llm_context_free();") != 0) goto fail;
+
+    // omitting it still auto-sizes to the model's training window
+    if (exec_expect_ok(env, db, "SELECT llm_context_create_chat();") != 0) goto fail;
+    if (select_single_int(env, db, "SELECT llm_context_size();", &n_ctx) != 0) goto fail;
+    if (n_ctx != n_ctx_train) {
+        fprintf(stderr, "[context_size_is_honoured] no context_size produced n_ctx=%d, expected %d\n", n_ctx, n_ctx_train);
+        goto fail;
+    }
+    if (exec_expect_ok(env, db, "SELECT llm_context_free();") != 0) goto fail;
+
+    // and context_size=0 asks for that explicitly
+    if (exec_expect_ok(env, db, "SELECT llm_context_create_chat('context_size=0');") != 0) goto fail;
+    if (select_single_int(env, db, "SELECT llm_context_size();", &n_ctx) != 0) goto fail;
+    if (n_ctx != n_ctx_train) {
+        fprintf(stderr, "[context_size_is_honoured] context_size=0 produced n_ctx=%d, expected %d\n", n_ctx, n_ctx_train);
+        goto fail;
+    }
+    if (exec_expect_ok(env, db, "SELECT llm_context_free();") != 0) goto fail;
+
+    if (exec_expect_ok(env, db, "SELECT llm_model_free();") != 0) goto fail;
+
+    sqlite3_close_v2(db);
+    return assert_sqlite_memory_clean("context_size_is_honoured", env);
+
+fail:
+    if (db) sqlite3_close_v2(db);
+    return 1;
+}
+
 static int test_document_ingestion_flow(const test_env *env) {
     sqlite3 *db = NULL;
     if (open_db_and_load(env, &db) != SQLITE_OK) {
@@ -2093,6 +2168,7 @@ static const test_case TESTS[] = {
     {"llm_embed_generate_basic", test_llm_embed_generate_basic},
     {"llm_embedding_then_chat", test_llm_embedding_then_chat},
     {"llm_context_size_errors", test_llm_context_size_errors},
+    {"context_size_is_honoured", test_context_size_is_honoured},
     {"document_ingestion_flow", test_document_ingestion_flow},
     {"llm_sampler_roundtrip", test_llm_sampler_roundtrip},
     {"chat_default_sampler_autocreate", test_chat_default_sampler_autocreate},