update teletables

README.md

@@ -14,7 +14,7 @@ license: apache-2.0
 - **Among open-source models**, TelecomGPT-R1 leads DeepSeek-V3-0324 (685B) by **+30.3**, LLaMA-3.3-70B by **+34.9**, and Qwen2.5-72B by **+35.6**, while operating at roughly **25× fewer active parameters than the next-best open entrant**.
 - **Among closed-source models**, TelecomGPT-R1 reaches SOTA performance across both the general-purpose frontier tier and the telecom-specialized tier, as detailed in the two bullets below.
 - **Among general-purpose frontier models**, TelecomGPT-R1 leads Gemini-3.1-Pro by **+14.0**, Claude-Opus-4.6 by **+16.3**, and GPT-5 by **+17.7**. These systems sit at the **trillion-parameter-class frontier** (active-parameter counts are not publicly disclosed but are widely reported as orders of magnitude larger than 27B), making the margin a parameter-efficiency result as much as an accuracy result.
-- **Among telecom-specialized models**, TelecomGPT-R1 is **on par with the leading closed operator-internal telecom model AT&T's OTel-LLM-8.3B-QnA**, and leads SoftBank LTM by **+16.0**, demonstrating that an open telecom reasoning model can reach SOTA performance alongside top operator-internal baselines on the GSMA Open Telco Leaderboard.
+- **Among telecom-specialized models**, TelecomGPT-R1 is **on par with the leading closed operator-internal telecom model AT&T's OTel-LLM-8.3B-QnA**, and leads SoftBank LTM by **+16.0**, demonstrating that an open telecom reasoning model can reach SOTA performance alongside top operator-internal baselines on the GSMA Open Telco Leaderboard. [^teletables]
 
 **In one line: TelecomGPT-R1 demonstrates that an open 27B telecom reasoning model can reach SOTA performance across the full breadth of the GSMA Open Telco Leaderboard.**