diff --git a/main/modules/LlamaModels.qml b/main/modules/LlamaModels.qml
index d07295b..7dd99bd 100644
--- a/main/modules/LlamaModels.qml
+++ b/main/modules/LlamaModels.qml
@@ -67,7 +67,7 @@ ClippingRectangle {
 
         let state = generationSamples[model.id];
         if (!state || state.generationId !== model.generationId)
-            state = { generationId: model.generationId, samples: [], phase: "" };
+            state = { generationId: model.generationId, samples: [], phase: "prompt" };
 
         const sample = {
             timestamp: now,
@@ -89,12 +89,10 @@ ClippingRectangle {
         const generatedTokens = Math.max(0, sample.generated - first.generated);
         if (generatedTokens > 0)
             state.phase = "generation";
-        else if (promptTokens > 0 || (state.phase.length === 0 && sample.prompt > 0))
-            state.phase = "prompt";
 
         const tokens = state.phase === "prompt" ? promptTokens : generatedTokens;
         model.tokensPerSecond = elapsed > 0 ? Math.max(0, tokens) * 1000 / elapsed : 0;
-        model.ratePhase = state.phase || "generation";
+        model.ratePhase = state.phase;
     }
 
     function rateText(value) {
@@ -131,26 +129,25 @@ ClippingRectangle {
 
     function paramsText(value) {
         const params = Number(value || 0);
-        return params > 0 ? `${(params / 1000000000).toFixed(1)}B params` : "";
+        return params > 0 ? `${(params / 1000000000).toFixed(1)}B param` : "";
     }
 
-    function sizeText(value) {
-        const size = Number(value || 0);
-        return size > 0 ? `${(size / 1073741824).toFixed(1)} GiB` : "";
+    function contextText(value) {
+        const context = Number(value || 0);
+        return context > 0 ? `${Math.round(context / 1024)}k ctx` : "";
     }
 
-    function modelDetails(model) {
+    function modelSpec(model) {
         const details = [];
+        const vram = Number(model.vramBytes || 0);
         const params = paramsText(model.params);
-        const size = sizeText(model.size);
+        const context = contextText(model.contextSize);
+        if (vram > 0)
+            details.push(`${(vram / 1073741824).toFixed(1)} GiB VRAM`);
         if (params.length > 0)
             details.push(params);
-        if (size.length > 0)
-            details.push(size);
-        if (Number(model.contextSize || 0) > 0)
-            details.push(`${Number(model.contextSize).toLocaleString()} ctx`);
-        if (Array.isArray(model.modalities) && model.modalities.length > 0)
-            details.push(model.modalities.join(" + "));
+        if (context.length > 0)
+            details.push(context);
         return details.join(" · ");
     }
 
@@ -304,9 +301,10 @@ ClippingRectangle {
 
                                 Row {
                                     width: parent.width
+                                    spacing: 8
 
                                     Text {
-                                        width: parent.width - stateLabel.width
+                                        width: parent.width - stateLabel.width - parent.spacing
                                         color: theme.text
                                         elide: Text.ElideMiddle
                                         font.family: theme.fontFamily
@@ -329,11 +327,11 @@ ClippingRectangle {
                                     width: parent.width
                                     visible: text.length > 0
                                     color: theme.subtext0
-                                    elide: Text.ElideRight
                                     font.family: theme.fontFamily
                                     font.pixelSize: theme.tooltipFontPixelSize - 1
-                                    text: root.modelDetails(modelRow.modelData)
+                                    text: root.modelSpec(modelRow.modelData)
                                 }
+
                             }
                         }
                     }
diff --git a/main/scripts/llama_models.py b/main/scripts/llama_models.py
index 79b1fb3..5a50421 100755
--- a/main/scripts/llama_models.py
+++ b/main/scripts/llama_models.py
@@ -1,6 +1,8 @@
 #!/usr/bin/env python3
 
 import json
+import os
+import subprocess
 import urllib.error
 import urllib.parse
 import urllib.request
@@ -60,6 +62,56 @@ def decoded_tokens(slot):
     return int(next_token[0].get("n_decoded", 0))
 
 
+def model_pids(ports):
+    pids = {}
+    for entry in os.scandir("/proc"):
+        if not entry.name.isdigit():
+            continue
+        try:
+            with open(f"{entry.path}/cmdline", "rb") as cmdline_file:
+                args = [
+                    part.decode(errors="replace")
+                    for part in cmdline_file.read().split(b"\0")
+                    if part
+                ]
+            port = model_port(args)
+            if port in ports:
+                pids[port] = int(entry.name)
+        except OSError:
+            continue
+    return pids
+
+
+def gpu_memory_by_pid(pids):
+    if not pids:
+        return {}
+    try:
+        result = subprocess.run(
+            [
+                "/usr/bin/nvidia-smi",
+                "--query-compute-apps=pid,used_gpu_memory",
+                "--format=csv,noheader,nounits",
+            ],
+            capture_output=True,
+            check=True,
+            text=True,
+            timeout=1,
+        )
+    except (OSError, subprocess.SubprocessError):
+        return {}
+
+    memory = {}
+    for line in result.stdout.splitlines():
+        try:
+            pid_text, mib_text = line.split(",", 1)
+            pid = int(pid_text.strip())
+            if pid in pids:
+                memory[pid] = memory.get(pid, 0) + int(mib_text.strip()) * 1048576
+        except ValueError:
+            continue
+    return memory
+
+
 def main():
     try:
         catalog = json.loads(fetch("/v1/models")).get("data", [])
@@ -67,16 +119,22 @@ def main():
         print(json.dumps({"models": [], "error": str(error)}))
         return
 
-    active_ports = connected_ports()
-    models = []
+    running_items = []
     for item in catalog:
         status_info = item.get("status", {})
         status = str(status_info.get("value", "unloaded"))
         if status not in ("loaded", "loading"):
             continue
+        running_items.append(
+            (item, status_info, status, model_port(status_info.get("args", [])))
+        )
 
+    pids = model_pids({port for _, _, _, port in running_items if port > 0})
+    gpu_memory = gpu_memory_by_pid(set(pids.values()))
+    active_ports = connected_ports()
+    models = []
+    for item, status_info, status, port in running_items:
         meta = item.get("meta", {})
-        port = model_port(status_info.get("args", []))
         has_active_request = status == "loaded" and port in active_ports
         model = {
             "id": str(item.get("id", "Unknown model")),
@@ -87,8 +145,7 @@ def main():
             "promptTokens": 0,
             "contextSize": int(meta.get("n_ctx", 0)),
             "params": float(meta.get("n_params", 0)),
-            "size": float(meta.get("size", 0)),
-            "modalities": item.get("architecture", {}).get("input_modalities", []),
+            "vramBytes": int(gpu_memory.get(pids.get(port), 0)),
         }
 
         if has_active_request: