diff --git a/server.py b/server.py
index 96fe546..19fba22 100644
--- a/server.py
+++ b/server.py
@@ -1820,7 +1820,7 @@ _STT_BACKEND_METRICS: dict[str, dict] = {
     "faster_whisper": {"speed": "~70× RT · GPU",    "latency": "0.5–2 s",     "quality": "large-v3",       "ram": "1.5 GB VRAM"},
     "whisper_cpp":    {"speed": "~8–15× RT · CPU",  "latency": "1–5 s",       "quality": "large-v3 Q5",    "ram": "~1 GB RAM"},
     "groq_whisper":   {"speed": "fastest cloud",    "latency": "0.5–1 s",     "quality": "Whisper Turbo",  "ram": "cloud · 0"},
-    "nvidia_parakeet":{"speed": "~200× RT · GPU",   "latency": "<0.3 s",      "quality": "Parakeet-TDT",   "ram": "2 GB VRAM"},
+    "nvidia_parakeet":{"speed": "~200× RT · GPU",   "latency": "<0.3 s",      "quality": "Parakeet-TDT",   "ram": "~1 GB"},
     "nvidia_router":  {"speed": "GPU routed",       "latency": "~0.5 s",      "quality": "varies",         "ram": "varies"},
 }
 
@@ -3213,7 +3213,7 @@ def _backend_capabilities(backend: str) -> dict:
             "style": "Weak per-request style; instruct may be ignored.",
             "best_for": "Known voices, multilingual cloning, benchmarks, and reliable speaker identity.",
             "uses_wav": True, "style_aware": False, "true_streaming": False,
-            "speed": "~0.3× GPU", "latency": "1–3 s", "quality": "Premium clone", "ram": "6–8 GB VRAM",
+            "speed": "~0.3× GPU", "latency": "1–3 s", "quality": "Premium clone", "ram": "~5 GB",
         },
         "voice_design": {
             "purpose": "Create or reuse prompt-designed voices from natural-language descriptions.",
@@ -3221,7 +3221,7 @@ def _backend_capabilities(backend: str) -> dict:
             "style": "Strong style and emotion control through instruct text.",
             "best_for": "New characters, personas, dialogue, and designing reference WAVs to clone later.",
             "uses_wav": False, "style_aware": True, "true_streaming": False,
-            "speed": "~0.4× GPU", "latency": "1–3 s", "quality": "Premium", "ram": "6–8 GB VRAM",
+            "speed": "~0.4× GPU", "latency": "1–3 s", "quality": "Premium", "ram": "~5 GB",
         },
         "customvoice": {
             "purpose": "Generate speech with the CustomVoice model voices.",
@@ -3229,7 +3229,7 @@ def _backend_capabilities(backend: str) -> dict:
             "style": "Good per-request style and emotion control.",
             "best_for": "Controlled style with configured CustomVoice speakers.",
             "uses_wav": False, "style_aware": True, "true_streaming": False,
-            "speed": "~0.3× GPU", "latency": "1–3 s", "quality": "Premium", "ram": "6–8 GB VRAM",
+            "speed": "~0.3× GPU", "latency": "1–3 s", "quality": "Premium", "ram": "~5 GB",
         },
         "streaming": {
             "purpose": "Low-latency playback from saved WAV/reference voices.",
@@ -3237,7 +3237,7 @@ def _backend_capabilities(backend: str) -> dict:
             "style": "Weak per-request style in the current streaming server.",
             "best_for": "Long text, assistants, Open WebUI/SillyTavern playback that can start before completion.",
             "uses_wav": True, "style_aware": False, "true_streaming": True,
-            "speed": "~0.1× GPU", "latency": "0.5–1 s", "quality": "Premium", "ram": "6–8 GB VRAM",
+            "speed": "~0.1× GPU", "latency": "0.5–1 s", "quality": "Premium", "ram": "~5 GB",
         },
         "nvidia_magpie": {
             "purpose": "Generate speech with NVIDIA Magpie fixed speaker voices.",
@@ -3245,7 +3245,7 @@ def _backend_capabilities(backend: str) -> dict:
             "style": "Language and speaker are controlled by the backend voice config; per-request style text is usually ignored.",
             "best_for": "Fast local NVIDIA TTS voices and OpenAI-compatible assistant playback.",
             "uses_wav": False, "style_aware": False, "true_streaming": False,
-            "speed": "~0.05× GPU", "latency": "0.3–0.8 s", "quality": "High", "ram": "4–6 GB VRAM",
+            "speed": "~0.05× GPU", "latency": "0.3–0.8 s", "quality": "High", "ram": "~1 GB",
         },
         "nvidia_zeroshot": {
             "purpose": "Clone a saved library voice through NVIDIA Magpie TTS Zeroshot NIM.",
@@ -3253,7 +3253,7 @@ def _backend_capabilities(backend: str) -> dict:
             "style": "Best with a clear 3-10 second prompt. Optional quality params can be configured in Settings.",
             "best_for": "Fast NVIDIA reference-audio cloning, streaming-class use cases, live agents, and games.",
             "uses_wav": True, "style_aware": False, "true_streaming": False,
-            "speed": "~0.1× GPU", "latency": "0.5–1 s", "quality": "High clone", "ram": "4–6 GB VRAM",
+            "speed": "~0.1× GPU", "latency": "0.5–1 s", "quality": "High clone", "ram": "~1 GB",
         },
         "nvidia_flow": {
             "purpose": "Clone a saved library voice through NVIDIA Magpie TTS Flow NIM.",
@@ -3261,7 +3261,7 @@ def _backend_capabilities(backend: str) -> dict:
             "style": "Offline high-fidelity clone path; prompt transcript must match the reference audio.",
             "best_for": "Studio-style dubbing, narration, and podcast-quality offline generation.",
             "uses_wav": True, "style_aware": False, "true_streaming": False,
-            "speed": "~0.2× GPU", "latency": "1–2 s", "quality": "Studio", "ram": "4–6 GB VRAM",
+            "speed": "~0.2× GPU", "latency": "1–2 s", "quality": "Studio", "ram": "~1 GB",
         },
         "kokoro": {
             "purpose": "High-quality English TTS with Kokoro 82M model. OpenAI-compatible endpoint.",
@@ -3285,7 +3285,7 @@ def _backend_capabilities(backend: str) -> dict:
             "style": "Speaker selected by voice ID. Style instruction not supported.",
             "best_for": "Local multi-speaker TTS with XTTS v2 model. Coqui/daswer123 docker setup.",
             "uses_wav": False, "style_aware": False, "true_streaming": False,
-            "speed": "~0.3× GPU", "latency": "1–3 s", "quality": "High", "ram": "4–6 GB VRAM",
+            "speed": "~0.3× GPU", "latency": "1–3 s", "quality": "High", "ram": "3–4 GB",
         },
     }
     return caps.get(_clean_preview_backend(backend), {})