docs: cross-link base<->v2, add known limitations, fix stale benchmark promise, enrich v2 metadata

README.md

@@ -4,12 +4,18 @@ language:
   - en
 library_name: transformers
 pipeline_tag: audio-text-to-text
-base_model: Qwen/Qwen3.6-27B
+base_model:
+  - Qwen/Qwen3.6-27B
+  - openai/whisper-large-v3-turbo
 tags:
-  - ultravox
+  - audio
   - speech
+  - speech-language-model
+  - ultravox
+  - qwen
   - telephony
   - voice-agent
+  - automatic-speech-recognition
 ---
 
 # ultravox-qwen3.6-27b-v2
@@ -21,7 +27,9 @@ directly through a Whisper-large-v3-turbo encoder + projection adapter (LoRA r=1
 encoder; knowledge-distillation training against the text LLM as teacher).
 
 Trained by **QuantumDesk** for receptionist/sales phone agents: heavy real-telephony and
-entity-dense data rather than multilingual benchmark balance.
+entity-dense data rather than multilingual benchmark balance. This is the **production
+successor** to [ultravox-qwen3.6-27b-base](https://huggingface.co/QuantumDesk-AI/ultravox-qwen3.6-27b-base)
+(the early English-only research checkpoint) — use this one for real voice-agent work.
 
 ## Benchmarks (native inference, greedy, n=100 per set)
 
@@ -73,4 +81,17 @@ currently loses some accuracy under vLLM relative to native transformers inferen
 maximum quality use HF transformers, or vLLM with `--no-enable-chunked-prefill` and
 default (fp32) mamba cache dtypes.
 
+## Known limitations
+
+- **Short utterances degrade sharply.** The benchmarks above are sentence-length inputs.
+  On isolated sub-second turns — "Yes", "Hello", "Okay", single-word backchannels — the
+  model frequently mistranscribes or hallucinates (observed in live deployment; the
+  training mix is dominated by sentence-length corpora). If you use this in a live
+  agent, buffer very short VAD segments with surrounding context, or route turns under
+  ~1.5 s through a fallback. A v3 addressing this with short-turn training data is in
+  progress.
+- **English only** — degraded quality on other languages and heavily accented English.
+- **Response style is trained to the prompt shape** shown above; deviating from it
+  (especially for conversational use) reduces quality.
+
 Apache 2.0. Built with the Ultravox training framework by Fixie.ai.