feat(llm): bump model registry to Qwen3.5 + Qwen3.6 family (4 tiers)

Replaces the three older Qwen3 variants with a four-tier ladder spanning
a wider hardware range:

- Qwen3_5_2B_Q4   (Minimal, 8 GB RAM, ~1.3 GB download)
- Qwen3_5_4B_Q4   (Standard, 16 GB RAM / 6 GB VRAM, ~2.7 GB) — DEFAULT
- Qwen3_5_9B_Q4   (High, 32 GB RAM / 12 GB VRAM, ~5.7 GB)
- Qwen3_6_27B_Q4  (Maximum, 64 GB RAM / 24 GB VRAM, ~17 GB)

All four GGUFs sourced from unsloth's HF org with pinned commit SHAs.
Sizes and SHA256 hashes verified against the live X-Linked-Etag /
X-Linked-Size headers on the LFS CDN. Q4_K_M quantisation throughout
(common sweet-spot for cleanup + task extraction).

recommend_tier rewritten to span four bands; default_tier moves from
the old 4B-Instruct-2507 to Qwen3.5 4B. The 27B Maximum tier honestly
needs 64 GB RAM to run without partial offload — surfaced in the
description string so the Settings UI can warn realistically.

In-tree smoke tests (smoke.rs, content_tags_smoke.rs) updated to
reference the new smallest tier so a developer's MAGNOTIA_LLM_TEST_MODEL
points at the cheapest GGUF to download. Crate description in
crates/llm/Cargo.toml refreshed to mention the new family.

NOTE (out of scope; not fixed): the size_bytes / sha256 / hf_url
methods could collapse into a single LlmModelMetadata table to remove
four parallel match arms. Layer 2 cleanup, separate session.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

crates/llm/Cargo.toml

@@ -2,7 +2,7 @@
 name = "magnotia-llm"
 version = "0.1.0"
 edition = "2021"
-description = "Local LLM engine for Magnotia (Qwen3 via llama-cpp-2): transcript cleanup, task extraction, micro-step decomposition"
+description = "Local LLM engine for Magnotia (Qwen3.5 / Qwen3.6 via llama-cpp-2): transcript cleanup, task extraction, micro-step decomposition"
 
 [features]
 # Default desktop build keeps the existing openmp + vulkan acceleration.

crates/llm/src/model_manager.rs

@@ -12,100 +12,119 @@ use tokio::io::{AsyncReadExt, AsyncWriteExt};
 #[allow(non_camel_case_types)]
 #[derive(Debug, Clone, Copy, PartialEq, Eq, Hash, Serialize, Deserialize)]
 pub enum LlmModelId {
-    #[serde(rename = "qwen3_1_7b")]
-    Qwen3_1_7B_Q4,
-    #[serde(rename = "qwen3_4b_instruct_2507")]
-    Qwen3_4BInstruct2507Q4,
-    #[serde(rename = "qwen3_14b")]
-    Qwen3_14BQ5,
+    #[serde(rename = "qwen3_5_2b")]
+    Qwen3_5_2B_Q4,
+    #[serde(rename = "qwen3_5_4b")]
+    Qwen3_5_4B_Q4,
+    #[serde(rename = "qwen3_5_9b")]
+    Qwen3_5_9B_Q4,
+    #[serde(rename = "qwen3_6_27b")]
+    Qwen3_6_27B_Q4,
 }
 
 impl LlmModelId {
     pub fn default_tier() -> Self {
-        Self::Qwen3_4BInstruct2507Q4
+        Self::Qwen3_5_4B_Q4
     }
 
     pub fn as_str(&self) -> &'static str {
         match self {
-            Self::Qwen3_1_7B_Q4 => "qwen3_1_7b",
-            Self::Qwen3_4BInstruct2507Q4 => "qwen3_4b_instruct_2507",
-            Self::Qwen3_14BQ5 => "qwen3_14b",
+            Self::Qwen3_5_2B_Q4 => "qwen3_5_2b",
+            Self::Qwen3_5_4B_Q4 => "qwen3_5_4b",
+            Self::Qwen3_5_9B_Q4 => "qwen3_5_9b",
+            Self::Qwen3_6_27B_Q4 => "qwen3_6_27b",
         }
     }
 
     pub fn display_name(&self) -> &'static str {
         match self {
-            Self::Qwen3_1_7B_Q4 => "Qwen3 1.7B",
-            Self::Qwen3_4BInstruct2507Q4 => "Qwen3 4B Instruct 2507",
-            Self::Qwen3_14BQ5 => "Qwen3 14B",
+            Self::Qwen3_5_2B_Q4 => "Qwen3.5 2B",
+            Self::Qwen3_5_4B_Q4 => "Qwen3.5 4B",
+            Self::Qwen3_5_9B_Q4 => "Qwen3.5 9B",
+            Self::Qwen3_6_27B_Q4 => "Qwen3.6 27B",
         }
     }
 
     pub fn file_name(&self) -> &'static str {
         match self {
-            Self::Qwen3_1_7B_Q4 => "Qwen3-1.7B-Q4_K_M.gguf",
-            Self::Qwen3_4BInstruct2507Q4 => "Qwen3-4B-Instruct-2507-Q4_K_M.gguf",
-            Self::Qwen3_14BQ5 => "Qwen3-14B-Q5_K_M.gguf",
+            Self::Qwen3_5_2B_Q4 => "Qwen3.5-2B-Q4_K_M.gguf",
+            Self::Qwen3_5_4B_Q4 => "Qwen3.5-4B-Q4_K_M.gguf",
+            Self::Qwen3_5_9B_Q4 => "Qwen3.5-9B-Q4_K_M.gguf",
+            Self::Qwen3_6_27B_Q4 => "Qwen3.6-27B-Q4_K_M.gguf",
         }
     }
 
     pub fn size_bytes(&self) -> u64 {
         match self {
-            Self::Qwen3_1_7B_Q4 => 1_107_409_472,
-            Self::Qwen3_4BInstruct2507Q4 => 2_497_281_120,
-            Self::Qwen3_14BQ5 => 10_514_570_624,
+            Self::Qwen3_5_2B_Q4 => 1_280_835_840,
+            Self::Qwen3_5_4B_Q4 => 2_740_937_888,
+            Self::Qwen3_5_9B_Q4 => 5_680_522_464,
+            Self::Qwen3_6_27B_Q4 => 16_817_244_384,
         }
     }
 
     pub fn minimum_ram_bytes(&self) -> u64 {
         match self {
-            Self::Qwen3_1_7B_Q4 => 8 * 1024_u64.pow(3),
-            Self::Qwen3_4BInstruct2507Q4 => 16 * 1024_u64.pow(3),
-            Self::Qwen3_14BQ5 => 32 * 1024_u64.pow(3),
+            Self::Qwen3_5_2B_Q4 => 8 * 1024_u64.pow(3),
+            Self::Qwen3_5_4B_Q4 => 16 * 1024_u64.pow(3),
+            Self::Qwen3_5_9B_Q4 => 32 * 1024_u64.pow(3),
+            Self::Qwen3_6_27B_Q4 => 64 * 1024_u64.pow(3),
         }
     }
 
     pub fn recommended_vram_bytes(&self) -> Option<u64> {
         match self {
-            Self::Qwen3_1_7B_Q4 => None,
-            Self::Qwen3_4BInstruct2507Q4 => Some(8 * 1024_u64.pow(3)),
-            Self::Qwen3_14BQ5 => Some(16 * 1024_u64.pow(3)),
+            Self::Qwen3_5_2B_Q4 => None,
+            Self::Qwen3_5_4B_Q4 => Some(6 * 1024_u64.pow(3)),
+            Self::Qwen3_5_9B_Q4 => Some(12 * 1024_u64.pow(3)),
+            Self::Qwen3_6_27B_Q4 => Some(24 * 1024_u64.pow(3)),
         }
     }
 
     pub fn description(&self) -> &'static str {
         match self {
-            Self::Qwen3_1_7B_Q4 => "Low tier for 8 GB RAM and CPU-heavy machines.",
-            Self::Qwen3_4BInstruct2507Q4 => {
-                "Default tier for cleanup and task extraction on 16 GB systems."
+            Self::Qwen3_5_2B_Q4 => "Minimal tier for 8 GB RAM and CPU-heavy machines.",
+            Self::Qwen3_5_4B_Q4 => {
+                "Standard tier for cleanup and task extraction on 16 GB systems."
+            }
+            Self::Qwen3_5_9B_Q4 => "High tier for 32 GB RAM with a 12 GB+ GPU.",
+            Self::Qwen3_6_27B_Q4 => {
+                "Maximum tier for 64 GB RAM with a 24 GB GPU; partial CPU offload below that."
             }
-            Self::Qwen3_14BQ5 => "High tier for 32 GB+ RAM and larger GPUs.",
         }
     }
 
     pub fn hf_url(&self) -> &'static str {
         match self {
-            Self::Qwen3_1_7B_Q4 => {
-                "https://huggingface.co/unsloth/Qwen3-1.7B-GGUF/resolve/d7f544eead698dbd1f15126ef60b45a1e1933222/Qwen3-1.7B-Q4_K_M.gguf"
+            Self::Qwen3_5_2B_Q4 => {
+                "https://huggingface.co/unsloth/Qwen3.5-2B-GGUF/resolve/f6d5376be1edb4d416d56da11e5397a961aca8ae/Qwen3.5-2B-Q4_K_M.gguf"
             }
-            Self::Qwen3_4BInstruct2507Q4 => {
-                "https://huggingface.co/unsloth/Qwen3-4B-Instruct-2507-GGUF/resolve/a06e946bb6b655725eafa393f4a9745d460374c9/Qwen3-4B-Instruct-2507-Q4_K_M.gguf"
+            Self::Qwen3_5_4B_Q4 => {
+                "https://huggingface.co/unsloth/Qwen3.5-4B-GGUF/resolve/e87f176479d0855a907a41277aca2f8ee7a09523/Qwen3.5-4B-Q4_K_M.gguf"
             }
-            Self::Qwen3_14BQ5 => {
-                "https://huggingface.co/unsloth/Qwen3-14B-GGUF/resolve/a04a82c4739b3ef5fa6da7d10261db2c67dd1985/Qwen3-14B-Q5_K_M.gguf"
+            Self::Qwen3_5_9B_Q4 => {
+                "https://huggingface.co/unsloth/Qwen3.5-9B-GGUF/resolve/3885219b6810b007914f3a7950a8d1b469d598a5/Qwen3.5-9B-Q4_K_M.gguf"
+            }
+            Self::Qwen3_6_27B_Q4 => {
+                "https://huggingface.co/unsloth/Qwen3.6-27B-GGUF/resolve/82d411acf4a06cfb8d9b073a5211bf410bfc29bf/Qwen3.6-27B-Q4_K_M.gguf"
             }
         }
     }
 
     pub fn sha256(&self) -> &'static str {
         match self {
-            Self::Qwen3_1_7B_Q4 => {
-                "de942b0819216caa3bfe487180dd1bb37398fa1c98cb42bb0bbac7ab7d6e8a12"
+            Self::Qwen3_5_2B_Q4 => {
+                "aaf42c8b7c3cab2bf3d69c355048d4a0ee9973d48f16c731c0520ee914699223"
             }
-            Self::Qwen3_4BInstruct2507Q4 => {
-                "bf52d44a54b81d44219833556849529ee96f09da673a38783dddc2e2eaf17881"
+            Self::Qwen3_5_4B_Q4 => {
+                "00fe7986ff5f6b463e62455821146049db6f9313603938a70800d1fb69ef11a4"
+            }
+            Self::Qwen3_5_9B_Q4 => {
+                "03b74727a860a56338e042c4420bb3f04b2fec5734175f4cb9fa853daf52b7e8"
+            }
+            Self::Qwen3_6_27B_Q4 => {
+                "5ed60d0af4650a854b1755bd392f9aef4872643dc25a254bc68043fa638392a0"
             }
-            Self::Qwen3_14BQ5 => "6f87abc471bd509ad46aca4284b3cfa926d8114bc491bb0a7a3a7f74c16ef95b",
         }
     }
 }
@@ -121,9 +140,10 @@ impl FromStr for LlmModelId {
 
     fn from_str(value: &str) -> Result<Self, Self::Err> {
         match value {
-            "qwen3_1_7b" => Ok(Self::Qwen3_1_7B_Q4),
-            "qwen3_4b_instruct_2507" => Ok(Self::Qwen3_4BInstruct2507Q4),
-            "qwen3_14b" => Ok(Self::Qwen3_14BQ5),
+            "qwen3_5_2b" => Ok(Self::Qwen3_5_2B_Q4),
+            "qwen3_5_4b" => Ok(Self::Qwen3_5_4B_Q4),
+            "qwen3_5_9b" => Ok(Self::Qwen3_5_9B_Q4),
+            "qwen3_6_27b" => Ok(Self::Qwen3_6_27B_Q4),
             other => Err(format!("Unknown LLM model id: {other}")),
         }
     }
@@ -154,9 +174,10 @@ pub enum DownloadError {
 }
 
 const ALL_MODELS: &[LlmModelId] = &[
-    LlmModelId::Qwen3_1_7B_Q4,
-    LlmModelId::Qwen3_4BInstruct2507Q4,
-    LlmModelId::Qwen3_14BQ5,
+    LlmModelId::Qwen3_5_2B_Q4,
+    LlmModelId::Qwen3_5_4B_Q4,
+    LlmModelId::Qwen3_5_9B_Q4,
+    LlmModelId::Qwen3_6_27B_Q4,
 ];
 
 static ACTIVE_DOWNLOADS: LazyLock<Mutex<std::collections::HashSet<LlmModelId>>> =
@@ -206,16 +227,15 @@ pub fn model_info(id: LlmModelId) -> LlmModelInfo {
 }
 
 pub fn recommend_tier(total_ram_bytes: u64, total_vram_bytes: Option<u64>) -> LlmModelId {
-    if total_vram_bytes.unwrap_or(0) >= 16 * 1024_u64.pow(3)
-        && total_ram_bytes >= 32 * 1024_u64.pow(3)
-    {
-        LlmModelId::Qwen3_14BQ5
-    } else if total_vram_bytes.unwrap_or(0) >= 8 * 1024_u64.pow(3)
-        || total_ram_bytes >= 16 * 1024_u64.pow(3)
-    {
-        LlmModelId::Qwen3_4BInstruct2507Q4
+    let vram = total_vram_bytes.unwrap_or(0);
+    if vram >= 24 * 1024_u64.pow(3) && total_ram_bytes >= 64 * 1024_u64.pow(3) {
+        LlmModelId::Qwen3_6_27B_Q4
+    } else if vram >= 12 * 1024_u64.pow(3) && total_ram_bytes >= 32 * 1024_u64.pow(3) {
+        LlmModelId::Qwen3_5_9B_Q4
+    } else if vram >= 6 * 1024_u64.pow(3) || total_ram_bytes >= 16 * 1024_u64.pow(3) {
+        LlmModelId::Qwen3_5_4B_Q4
     } else {
-        LlmModelId::Qwen3_1_7B_Q4
+        LlmModelId::Qwen3_5_2B_Q4
     }
 }
 
@@ -389,15 +409,15 @@ mod tests {
 
     #[test]
     fn model_path_contains_model_dir_and_filename() {
-        let path = model_path(LlmModelId::Qwen3_1_7B_Q4);
-        assert!(path.to_string_lossy().ends_with("Qwen3-1.7B-Q4_K_M.gguf"));
+        let path = model_path(LlmModelId::Qwen3_5_2B_Q4);
+        assert!(path.to_string_lossy().ends_with("Qwen3.5-2B-Q4_K_M.gguf"));
         assert!(path.starts_with(model_dir()));
     }
 
     #[test]
     fn recommend_tier_prefers_mid_by_default() {
         let tier = recommend_tier(16 * 1024_u64.pow(3), None);
-        assert_eq!(tier, LlmModelId::Qwen3_4BInstruct2507Q4);
+        assert_eq!(tier, LlmModelId::Qwen3_5_4B_Q4);
     }
 
     #[tokio::test]

crates/llm/tests/content_tags_smoke.rs

@@ -24,7 +24,7 @@ fn extract_content_tags_returns_valid_pair() {
 
     let engine = LlmEngine::new();
     engine
-        .load_model(LlmModelId::Qwen3_1_7B_Q4, &model_path, true)
+        .load_model(LlmModelId::Qwen3_5_2B_Q4, &model_path, true)
         .expect("load model");
 
     let transcript = "Tomorrow I need to run through the grant application one more time \

crates/llm/tests/smoke.rs

@@ -26,7 +26,7 @@ fn llama_cpp_2_smoke_generates_and_wraps() {
 
     let engine = LlmEngine::new();
     engine
-        .load_model(LlmModelId::Qwen3_1_7B_Q4, &model_path, true)
+        .load_model(LlmModelId::Qwen3_5_2B_Q4, &model_path, true)
         .expect("load model");
 
     let completion = engine