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@@ -20,7 +20,7 @@ training_regime: bf16 mixed precision
 
 <p align="center">
 🤗 <a href="https://kko.kakao.com/kananallm">1.5 HF Models</a> &nbsp |
-&nbsp 📕 <a href="https://tech.kakao.com/posts/707">1.5 Blog Post</a> &nbsp |
+&nbsp 📕 <a href="https://tech.kakao.com/posts/707">1.5 Blog</a> &nbsp |
 &nbsp 📜 <a href="https://arxiv.org/abs/2502.18934">Technical Report</a>
 
 
@@ -44,8 +44,7 @@ training_regime: bf16 mixed precision
         - [Instruct Model Evaluation](#instruct-model-evaluation)
         - [Long Context](#long-context)
     - [Processing 32K+ Length](#processing-32k-length)
-    - [Contributors](#contributors)
-- [Kanana 1.0](#kanana-10)
+- [Contributors](#contributors)
 - [Citation](#citation)
 - [Contact](#contact)
 
@@ -77,7 +76,7 @@ training_regime: bf16 mixed precision
         <th>GSM8K</th>
     </tr>
     <tr>
-        <td><strong>Kanana-Flag-1.5-32.5B</strong></td>
+        <td>Kanana-Flag-1.5-32.5B</td>
         <td align="center">76.76</td>
         <td align="center">61.90</td>
         <td align="center">89.18</td>
@@ -86,7 +85,7 @@ training_regime: bf16 mixed precision
         <td align="center">81.50</td>
     </tr>
     <tr>
-        <td><strong>Kanana-Flag-32.5B</strong></td>
+        <td>Kanana-Flag-32.5B</td>
         <td align="center">77.68</td>
         <td align="center">62.10</td>
         <td align="center">90.47</td>
@@ -95,7 +94,7 @@ training_regime: bf16 mixed precision
         <td align="center">70.05</td>
     </tr>
     <tr>
-        <td><strong>Kanana-Essence-1.5-9.8B</strong></td>
+        <td>Kanana-Essence-1.5-9.8B</td>
         <td align="center">68.27</td>
         <td align="center">52.78</td>
         <td align="center">86.34</td>
@@ -104,7 +103,7 @@ training_regime: bf16 mixed precision
         <td align="center">71.57</td>
     </tr>
     <tr>
-        <td><strong>Kanana-Essence-9.8B</strong></td>
+        <td>Kanana-Essence-9.8B</td>
         <td align="center">67.61</td>
         <td align="center">50.57</td>
         <td align="center">84.97</td>
@@ -113,7 +112,7 @@ training_regime: bf16 mixed precision
         <td align="center">63.61</td>
     </tr>
     <tr>
-        <td><strong>Kanana-1.5-8B</strong></td>
+        <td>Kanana-1.5-8B</td>
         <td align="center">64.24</td>
         <td align="center">48.94</td>
         <td align="center">82.77</td>
@@ -122,7 +121,7 @@ training_regime: bf16 mixed precision
         <td align="center">63.53</td>
     </tr>
     <tr>
-        <td><strong>Kanana-8B</strong></td>
+        <td>Kanana-8B</td>
         <td align="center">64.22</td>
         <td align="center">48.30</td>
         <td align="center">83.41</td>
@@ -131,7 +130,7 @@ training_regime: bf16 mixed precision
         <td align="center">57.09</td>
     </tr>
     <tr>
-        <td><strong>Kanana-Nano-1.5-3B</strong></td>
+        <td>Kanana-Nano-1.5-3B</td>
         <td align="center">59.23</td>
         <td align="center">47.30</td>
         <td align="center">78.00</td>
@@ -149,7 +148,7 @@ training_regime: bf16 mixed precision
         <td align="center">55.95</td>
     </tr>
     <tr>
-        <td><strong>Kanana-Nano-2.1B</strong></td>
+        <td>Kanana-Nano-2.1B</td>
         <td align="center">54.83</td>
         <td align="center">44.80</td>
         <td align="center">77.09</td>
@@ -177,7 +176,7 @@ training_regime: bf16 mixed precision
         <th>FunctionChatBench</th>
     </tr>
     <tr>
-        <td><strong>Kanana-Flag-1.5-32.5B</strong></td>
+        <td>Kanana-Flag-1.5-32.5B</td>
         <td align="center">8.13</td>
         <td align="center">8.12</td>
         <td align="center">82.70</td>
@@ -190,7 +189,7 @@ training_regime: bf16 mixed precision
         <td align="center">67.17</td>
     </tr>
     <tr>
-        <td><strong>Kanana-Flag-32.5B</strong></td>
+        <td>Kanana-Flag-32.5B</td>
         <td align="center">8.33</td>
         <td align="center">8.03</td>
         <td align="center">84.59</td>
@@ -203,7 +202,7 @@ training_regime: bf16 mixed precision
         <td align="center">65.67</td>
     </tr>
     <tr>
-        <td><strong>Kanana-Essence-1.5-9.8B</strong></td>
+        <td>Kanana-Essence-1.5-9.8B</td>
         <td align="center">7.88</td>
         <td align="center">7.35</td>
         <td align="center">76.34</td>
@@ -216,7 +215,7 @@ training_regime: bf16 mixed precision
         <td align="center">51.43</td>
     </tr>
     <tr>
-        <td><strong>Kanana-Essence-9.8B</strong></td>
+        <td>Kanana-Essence-9.8B</td>
         <td align="center">7.81</td>
         <td align="center">7.65</td>
         <td align="center">80.20</td>
@@ -229,7 +228,7 @@ training_regime: bf16 mixed precision
         <td align="center">26.77</td>
     </tr>
     <tr>
-        <td><strong>Kanana-1.5-8B*</strong></td>
+        <td>Kanana-1.5-8B</td>
         <td align="center">7.76</td>
         <td align="center">7.63</td>
         <td align="center">80.11</td>
@@ -242,7 +241,7 @@ training_regime: bf16 mixed precision
         <td align="center">58.00</td>
     </tr>
     <tr>
-        <td><strong>Kanana-8B</strong></td>
+        <td>Kanana-8B</td>
         <td align="center">7.13</td>
         <td align="center">6.92</td>
         <td align="center">76.91</td>
@@ -255,7 +254,7 @@ training_regime: bf16 mixed precision
         <td align="center">17.37</td>
     </tr>
     <tr>
-        <td><strong>Kanana-Nano-1.5-3B</strong></td>
+        <td>Kanana-Nano-1.5-3B</td>
         <td align="center">7.01</td>
         <td align="center">6.52</td>
         <td align="center">70.08</td>
@@ -268,7 +267,7 @@ training_regime: bf16 mixed precision
         <td align="center">55.37</td>
     </tr>
     <tr>
-        <td><strong>Kanana-1.5-2.1B*</strong></td>
+        <td>Kanana-1.5-2.1B</td>
         <td align="center">7.01</td>
         <td align="center">6.54</td>
         <td align="center">68.61</td>
@@ -281,7 +280,7 @@ training_regime: bf16 mixed precision
         <td align="center">53.70</td>
     </tr>
     <tr>
-        <td><strong>Kanana-Nano-2.1B</strong></td>
+        <td>Kanana-Nano-2.1B</td>
         <td align="center">6.40</td>
         <td align="center">5.90</td>
         <td align="center">71.97</td>
@@ -296,7 +295,7 @@ training_regime: bf16 mixed precision
 </table>
 
 > [!Note]
-> \* Models released under the Apache 2.0 license have been trained on more recent data compared to other models.
+> \* Models released under Apache 2.0 are trained on the latest versions compared to other models.
 
 <br>
 
@@ -344,634 +343,6 @@ Currently, the `config.json` uploaded to HuggingFace is configured for token len
 
 <br>
 
-# Kanana 1.0
-<details>
-<summary>View the details about Kanana 1.0</summary>
-
-<br>
-
-We introduce Kanana, a series of bilingual language models (developed by [Kakao](https://github.com/kakao)) that demonstrate exceeding performance in Korean and competitive performance in English. The computational cost of Kanana is significantly lower than that of state-of-the-art models of similar size. The report details the techniques employed during pre-training to achieve compute-efficient yet competitive models, including high-quality data filtering, staged pre-training, depth up-scaling, and pruning and distillation. Furthermore, the report outlines the methodologies utilized during the post-training of the Kanana models, encompassing supervised fine-tuning and preference optimization, aimed at enhancing their capability for seamless interaction with users. Lastly, the report elaborates on plausible approaches used for language model adaptation to specific scenarios, such as embedding, function calling, and Retrieval Augmented Generation (RAG). The Kanana model series spans from 2.1B to 32.5B parameters with 2.1B models (base, instruct, embedding, function call, and RAG) publicly released to promote research on Korean language models.
-
-> Neither the pre-training nor the post-training data includes Kakao user data.
-
-<p align="center">
-<picture>
-    <img src="assets/performance/flops-vs-mmlu.jpg", width="700" style="margin: 40px auto;">
-</picture>
-
-## Performance
-
-Below are partial report on the performance of the `Kanana` model series. Please refer to the [Technical Report](https://arxiv.org/abs/2502.18934) for the full results.
-
-### Base Model Evaluation
-
-<table>
-    <tr>
-        <th>Models</th>
-        <th>MMLU</th>
-        <th>KMMLU</th>
-        <th>HAERAE</th>
-        <th>HumanEval</th>
-        <th>MBPP</th>
-        <th>GSM8K</th>
-    </tr>
-    <tr>
-        <th colspan="8" height="30px">27b+ scale</th>
-    </tr>
-    <tr>
-        <td>Kanana-Flag-32.5b</td>
-        <td align="center">77.68</td>
-        <td align="center">62.10</td>
-        <td align="center"><strong>90.47</strong></td>
-        <td align="center"><strong>51.22</strong></td>
-        <td align="center">63.40</td>
-        <td align="center">70.05</td>
-    </tr>
-    <tr>
-        <td>Qwen2.5-32b</td>
-        <td align="center"><strong>83.10</strong></td>
-        <td align="center"><strong>63.15</strong></td>
-        <td align="center">75.16</td>
-        <td align="center">50.00</td>
-        <td align="center">73.40</td>
-        <td align="center"><strong>82.41</strong></td>
-    </tr>
-    <tr>
-        <td>Gemma-2-27b</td>
-        <td align="center">75.45</td>
-        <td align="center">51.16</td>
-        <td align="center">69.11</td>
-        <td align="center"><strong>51.22</strong></td>
-        <td align="center">64.60</td>
-        <td align="center">74.37</td>
-    </tr>
-    <tr>
-        <td>EXAONE-3.5-32b</td>
-        <td align="center">72.68</td>
-        <td align="center">46.36</td>
-        <td align="center">82.22</td>
-        <td align="center">-</td>
-        <td align="center">-</td>
-        <td align="center">-</td>
-    </tr>
-    <tr>
-        <td>Aya-Expanse-32b</td>
-        <td align="center">74.52</td>
-        <td align="center">49.57</td>
-        <td align="center">80.66</td>
-        <td align="center">-</td>
-        <td align="center">-</td>
-        <td align="center">-</td>
-    </tr>
-    <tr>
-        <th colspan="8" height="30px">7b+ scale</th>
-    </tr>
-    <tr>
-        <td>Kanana-Essence-9.8b</td>
-        <td align="center">67.61</td>
-        <td align="center">50.57</td>
-        <td align="center"><strong>84.98</strong></td>
-        <td align="center">40.24</td>
-        <td align="center">53.60</td>
-        <td align="center">63.61</td>
-    </tr>
-    <tr>
-        <td>Llama-3.1-8b</td>
-        <td align="center">65.18</td>
-        <td align="center">41.02</td>
-        <td align="center">61.78</td>
-        <td align="center">35.37</td>
-        <td align="center">48.60</td>
-        <td align="center">50.87</td>
-    </tr>
-    <tr>
-        <td>Qwen2.5-7b</td>
-        <td align="center"><strong>74.19</strong></td>
-        <td align="center"><strong>51.68</strong></td>
-        <td align="center">67.46</td>
-        <td align="center"><strong>56.71</strong></td>
-        <td align="center"><strong>63.20</strong></td>
-        <td align="center"><strong>83.85</strong></td>
-    </tr>
-    <tr>
-        <td>Gemma-2-9b</td>
-        <td align="center">70.34</td>
-        <td align="center">48.18</td>
-        <td align="center">66.18</td>
-        <td align="center">37.20</td>
-        <td align="center">53.60</td>
-        <td align="center">68.16</td>
-    </tr>
-    <tr>
-        <td>EXAONE-3.5-7.8b</td>
-        <td align="center">65.36</td>
-        <td align="center">45.30</td>
-        <td align="center">77.54</td>
-        <td align="center">-</td>
-        <td align="center">-</td>
-        <td align="center">-</td>
-    </tr>
-    <tr>
-        <td>Aya-Expanse-8b</td>
-        <td align="center">62.52</td>
-        <td align="center">40.11</td>
-        <td align="center">71.95</td>
-        <td align="center">-</td>
-        <td align="center">-</td>
-        <td align="center">-</td>
-    </tr>
-    <tr>
-        <th colspan="8" height="30px">2b+ scale</th>
-    </tr>
-    <tr>
-        <td>Kanana-Nano-2.1b</td>
-        <td align="center">54.83</td>
-        <td align="center">44.80</td>
-        <td align="center"><strong>77.09</strong></td>
-        <td align="center">31.10</td>
-        <td align="center">46.20</td>
-        <td align="center">46.32</td>
-    </tr>
-    <tr>
-        <td>Llama-3.2-3b</td>
-        <td align="center">56.40</td>
-        <td align="center">35.57</td>
-        <td align="center">47.66</td>
-        <td align="center">25.61</td>
-        <td align="center">39.00</td>
-        <td align="center">27.37</td>
-    </tr>
-    <tr>
-        <td>Qwen2.5-3b</td>
-        <td align="center"><strong>65.57</strong></td>
-        <td align="center"><strong>45.28</strong></td>
-        <td align="center">61.32</td>
-        <td align="center"><strong>37.80</strong></td>
-        <td align="center"><strong>55.60</strong></td>
-        <td align="center"><strong>69.07</strong></td>
-    </tr>
-    <tr>
-        <td>Gemma-2-2b</td>
-        <td align="center">52.89</td>
-        <td align="center">30.67</td>
-        <td align="center">45.55</td>
-        <td align="center">20.12</td>
-        <td align="center">28.20</td>
-        <td align="center">24.72</td>
-    </tr>
-    <tr>
-        <td>EXAONE-3.5-2.4b</td>
-        <td align="center">59.27</td>
-        <td align="center">43.58</td>
-        <td align="center">69.65</td>
-        <td align="center">-</td>
-        <td align="center">-</td>
-        <td align="center">-</td>
-    </tr>
-    <tr>
-        <th colspan="8" height="30px">70b+ scale</th>
-    </tr>
-    <tr>
-        <td>Llama-3.1-70b</td>
-        <td align="center">78.93</td>
-        <td align="center">53.00</td>
-        <td align="center">76.35</td>
-        <td align="center">57.32</td>
-        <td align="center">66.60</td>
-        <td align="center">81.73</td>
-    </tr>
-    <tr>
-        <td>Qwen2.5-72b</td>
-        <td align="center">86.12</td>
-        <td align="center">68.57</td>
-        <td align="center">80.84</td>
-        <td align="center">55.49</td>
-        <td align="center">76.40</td>
-        <td align="center">92.04</td>
-    </tr>
-</table>
-
-<br>
-
-
-### Instruct Model Evaluation
-
-#### Instruction-following Benchmarks
-<table>
-    <tr>
-        <th>Models</th>
-        <th>MT-Bench</th>
-        <th>LogicKor</th>
-        <th>KoMT-Bench</th>
-        <th>WildBench</th>
-        <th>IFEval</th>
-    </tr>
-    <tr>
-        <th colspan="8" height="30px">27b+ scale</th>
-    </tr>
-    <tr>
-        <td>Kanana-Flag-32.5b</td>
-        <td align="center">8.356</td>
-        <td align="center"><strong>9.524</strong></td>
-        <td align="center"><strong>8.058</strong></td>
-        <td align="center">54.14</td>
-        <td align="center"><strong>0.856</strong></td>
-    </tr>
-    <tr>
-        <td>Qwen2.5-32b</td>
-        <td align="center">8.331</td>
-        <td align="center">8.988</td>
-        <td align="center">7.847</td>
-        <td align="center">51.13</td>
-        <td align="center">0.822</td>
-    </tr>
-    <tr>
-        <td>Gemma-2-27b</td>
-        <td align="center">8.088</td>
-        <td align="center">8.869</td>
-        <td align="center">7.373</td>
-        <td align="center">46.46</td>
-        <td align="center">0.817</td>
-    </tr>
-    <tr>
-        <td>EXAONE-3.5-32b</td>
-        <td align="center"><strong>8.375</strong></td>
-        <td align="center">9.202</td>
-        <td align="center">7.907</td>
-        <td align="center"><strong>54.30</strong></td>
-        <td align="center">0.845</td>
-    </tr>
-    <tr>
-        <td>Aya-Expanse-32b</td>
-        <td align="center">7.788</td>
-        <td align="center">8.941</td>
-        <td align="center">7.626</td>
-        <td align="center">48.36</td>
-        <td align="center">0.735</td>
-    </tr>
-    <tr>
-        <th colspan="8" height="30px">7b+ scale</th>
-    </tr>
-    <tr>
-        <td>Kanana-Essence-9.8b</td>
-        <td align="center">7.769</td>
-        <td align="center">8.964</td>
-        <td align="center">7.706</td>
-        <td align="center">47.27</td>
-        <td align="center">0.799</td>
-    </tr>
-    <tr>
-        <td>Llama-3.1-8b</td>
-        <td align="center">7.500</td>
-        <td align="center">6.512</td>
-        <td align="center">5.336</td>
-        <td align="center">33.20</td>
-        <td align="center">0.772</td>
-    </tr>
-    <tr>
-        <td>Qwen2.5-7b</td>
-        <td align="center">7.625</td>
-        <td align="center">7.952</td>
-        <td align="center">6.808</td>
-        <td align="center">41.31</td>
-        <td align="center">0.760</td>
-    </tr>
-    <tr>
-        <td>Gemma-2-9b</td>
-        <td align="center">7.633</td>
-        <td align="center">8.643</td>
-        <td align="center">7.029</td>
-        <td align="center">40.92</td>
-        <td align="center">0.750</td>
-    </tr>
-    <tr>
-        <td>EXAONE-3.5-7.8b</td>
-        <td align="center"><strong>8.213</strong></td>
-        <td align="center"><strong>9.357</strong></td>
-        <td align="center"><strong>8.013</strong></td>
-        <td align="center"><strong>50.98</strong></td>
-        <td align="center"><strong>0.826</strong></td>
-    </tr>
-    <tr>
-        <td>Aya-Expanse-8b</td>
-        <td align="center">7.131</td>
-        <td align="center">8.357</td>
-        <td align="center">7.006</td>
-        <td align="center">38.50</td>
-        <td align="center">0.645</td>
-    </tr>
-    <tr>
-        <th colspan="8" height="30px">2b+ scale</th>
-    </tr>
-    <tr>
-        <td>Kanana-Nano-2.1b</td>
-        <td align="center">6.400</td>
-        <td align="center">7.964</td>
-        <td align="center">5.857</td>
-        <td align="center">25.41</td>
-        <td align="center">0.720</td>
-    </tr>
-    <tr>
-        <td>Llama-3.2-3b</td>
-        <td align="center">7.050</td>
-        <td align="center">4.452</td>
-        <td align="center">3.967</td>
-        <td align="center">21.91</td>
-        <td align="center">0.767</td>
-    </tr>
-    <tr>
-        <td>Qwen2.5-3b</td>
-        <td align="center">6.969</td>
-        <td align="center">6.488</td>
-        <td align="center">5.274</td>
-        <td align="center">25.76</td>
-        <td align="center">0.355</td>
-    </tr>
-    <tr>
-        <td>Gemma-2-2b</td>
-        <td align="center">7.225</td>
-        <td align="center">5.917</td>
-        <td align="center">4.835</td>
-        <td align="center">28.71</td>
-        <td align="center">0.428</td>
-    </tr>
-    <tr>
-        <td>EXAONE-3.5-2.4b</td>
-        <td align="center"><strong>7.919</strong></td>
-        <td align="center"><strong>8.941</strong></td>
-        <td align="center"><strong>7.223</strong></td>
-        <td align="center"><strong>41.68</strong></td>
-        <td align="center"><strong>0.790</strong></td>
-    </tr>
-    <tr>
-        <th colspan="8" height="30px">70b+ scale</th>
-    </tr>
-    <tr>
-        <td>Llama-3.1-70b</td>
-        <td align="center">8.275</td>
-        <td align="center">8.250</td>
-        <td align="center">6.970</td>
-        <td align="center">46.50</td>
-        <td align="center">0.875</td>
-    </tr>
-    <tr>
-        <td>Qwen2.5-72b</td>
-        <td align="center">8.619</td>
-        <td align="center">9.214</td>
-        <td align="center">8.281</td>
-        <td align="center">55.25</td>
-        <td align="center">0.861</td>
-    </tr>
-</table>
-
-<br>
-
-#### General Benchmarks
-
-<table>
-    <tr>
-        <th>Models</th>
-        <th>MMLU</th>
-        <th>KMMLU</th>
-        <th>HAE-RAE</th>
-        <th>HumanEval+</th>
-        <th>MBPP+</th>
-        <th>GSM8K</th>
-        <th>MATH</th>
-    </tr>
-    <tr>
-        <th colspan="8" height="30px">27b+ scale</th>
-    </tr>
-    <tr>
-        <td>Kanana-Flag-32.5b</td>
-        <td align="center">81.08</td>
-        <td align="center"><strong>64.19</strong></td>
-        <td align="center"><strong>68.18</strong></td>
-        <td align="center">77.44</td>
-        <td align="center">69.84</td>
-        <td align="center">90.83</td>
-        <td align="center">57.82</td>
-    </tr>
-    <tr>
-        <td>Qwen2.5-32b</td>
-        <td align="center"><strong>84.40</strong></td>
-        <td align="center">59.37</td>
-        <td align="center">48.30</td>
-        <td align="center"><strong>82.32</strong></td>
-        <td align="center"><strong>71.96</strong></td>
-        <td align="center"><strong>95.30</strong></td>
-        <td align="center"><strong>81.90</strong></td>
-    </tr>
-    <tr>
-        <td>Gemma-2-27b</td>
-        <td align="center">78.01</td>
-        <td align="center">49.98</td>
-        <td align="center">46.02</td>
-        <td align="center">70.12</td>
-        <td align="center">70.90</td>
-        <td align="center">91.05</td>
-        <td align="center">53.80</td>
-    </tr>
-    <tr>
-        <td>EXAONE-3.5-32b</td>
-        <td align="center">78.30</td>
-        <td align="center">55.44</td>
-        <td align="center">52.27</td>
-        <td align="center">78.66</td>
-        <td align="center">70.90</td>
-        <td align="center">93.56</td>
-        <td align="center">76.80</td>
-    </tr>
-    <tr>
-        <td>Aya-Expanse-32b</td>
-        <td align="center">74.49</td>
-        <td align="center">42.35</td>
-        <td align="center">51.14</td>
-        <td align="center">64.63</td>
-        <td align="center">65.61</td>
-        <td align="center">75.06</td>
-        <td align="center">42.82</td>
-    </tr>
-    <tr>
-        <th colspan="8" height="30px">7b+ scale</th>
-    </tr>
-    <tr>
-        <td>Kanana-Essence-9.8b</td>
-        <td align="center">70.64</td>
-        <td align="center">50.76</td>
-        <td align="center"><strong>47.16</strong></td>
-        <td align="center">72.56</td>
-        <td align="center">69.05</td>
-        <td align="center">84.91</td>
-        <td align="center">42.24</td>
-    </tr>
-    <tr>
-        <td>Llama-3.1-8b</td>
-        <td align="center">71.18</td>
-        <td align="center">39.24</td>
-        <td align="center">40.91</td>
-        <td align="center">60.98</td>
-        <td align="center">57.67</td>
-        <td align="center">82.71</td>
-        <td align="center">49.86</td>
-    </tr>
-    <tr>
-        <td>Qwen2.5-7b</td>
-        <td align="center"><strong>77.23</strong></td>
-        <td align="center">46.87</td>
-        <td align="center">37.50</td>
-        <td align="center">73.78</td>
-        <td align="center"><strong>70.63</strong></td>
-        <td align="center"><strong>91.58</strong></td>
-        <td align="center"><strong>75.22</strong></td>
-    </tr>
-    <tr>
-        <td>Gemma-2-9b</td>
-        <td align="center">73.47</td>
-        <td align="center">44.47</td>
-        <td align="center">39.77</td>
-        <td align="center">59.76</td>
-        <td align="center">64.55</td>
-        <td align="center">87.72</td>
-        <td align="center">48.10</td>
-    </tr>
-    <tr>
-        <td>EXAONE-3.5-7.8b</td>
-        <td align="center">72.62</td>
-        <td align="center"><strong>52.09</strong></td>
-        <td align="center">46.02</td>
-        <td align="center"><strong>79.27</strong></td>
-        <td align="center">66.67</td>
-        <td align="center">89.99</td>
-        <td align="center">73.50</td>
-    </tr>
-    <tr>
-        <td>Aya-Expanse-8b</td>
-        <td align="center">61.23</td>
-        <td align="center">35.78</td>
-        <td align="center">39.20</td>
-        <td align="center">42.68</td>
-        <td align="center">56.88</td>
-        <td align="center">78.85</td>
-        <td align="center">30.80</td>
-    </tr>
-    <tr>
-        <th colspan="8" height="30px">2b+ scale</th>
-    </tr>
-    <tr>
-        <td>Kanana-Nano-2.1b</td>
-        <td align="center">52.48</td>
-        <td align="center"><strong>38.51</strong></td>
-        <td align="center"><strong>33.52</strong></td>
-        <td align="center">63.41</td>
-        <td align="center">62.43</td>
-        <td align="center">72.32</td>
-        <td align="center">29.26</td>
-    </tr>
-    <tr>
-        <td>Llama-3.2-3b</td>
-        <td align="center">56.09</td>
-        <td align="center">3.07</td>
-        <td align="center">17.05</td>
-        <td align="center">56.71</td>
-        <td align="center">50.26</td>
-        <td align="center">66.57</td>
-        <td align="center">38.18</td>
-    </tr>
-    <tr>
-        <td>Qwen2.5-3b</td>
-        <td align="center"><strong>69.18</strong></td>
-        <td align="center">38.33</td>
-        <td align="center">32.39</td>
-        <td align="center">67.68</td>
-        <td align="center"><strong>64.02</strong></td>
-        <td align="center"><strong>84.00</strong></td>
-        <td align="center"><strong>65.72</strong></td>
-    </tr>
-    <tr>
-        <td>Gemma-2-2b</td>
-        <td align="center">57.69</td>
-        <td align="center">6.99</td>
-        <td align="center">7.95</td>
-        <td align="center">35.37</td>
-        <td align="center">45.24</td>
-        <td align="center">49.81</td>
-        <td align="center">21.68</td>
-    </tr>
-    <tr>
-        <td>EXAONE-3.5-2.4b</td>
-        <td align="center">63.19</td>
-        <td align="center">14.27</td>
-        <td align="center">14.20</td>
-        <td align="center"><strong>70.73</strong></td>
-        <td align="center">59.79</td>
-        <td align="center">83.78</td>
-        <td align="center">64.04</td>
-    </tr>
-    <tr>
-        <th colspan="8" height="30px">70b+ scale</th>
-    </tr>
-    <tr>
-        <td>Llama-3.1-70b</td>
-        <td align="center">83.48</td>
-        <td align="center">39.08</td>
-        <td align="center">53.41</td>
-        <td align="center">75.61</td>
-        <td align="center">66.40</td>
-        <td align="center">91.66</td>
-        <td align="center">63.98</td>
-    </tr>
-    <tr>
-        <td>Qwen2.5-72b</td>
-        <td align="center">87.14</td>
-        <td align="center">65.78</td>
-        <td align="center">60.80</td>
-        <td align="center">81.10</td>
-        <td align="center">75.66</td>
-        <td align="center">95.45</td>
-        <td align="center">82.60</td>
-    </tr>
-</table>
-
-<br>
-
-### Embedding Model Performance
-<table>
-    <tr>
-        <td align="center">Backbone</td>
-        <td align="center">Kanana-Nano-2.1b</td>
-        <td align="center">Llama-3.2-3b</td>
-        <td align="center">Qwen2.5-3b</td>
-        <td align="center">Llama-3.2-1b</td>
-        <td align="center">Qwen-2.5-1.5b</td>
-    </tr>
-    <tr>
-        <td align="center">English</td>
-        <td align="center">51.56</td>
-        <td align="center">53.28</td>
-        <td align="center"><strong>54.00</strong></td>
-        <td align="center">48.77</td>
-        <td align="center">50.60</td>
-    </tr>
-    <tr>
-        <td align="center">Korean</td>
-        <td align="center"><strong>65.00</strong></td>
-        <td align="center">59.43</td>
-        <td align="center">62.10</td>
-        <td align="center">54.68</td>
-        <td align="center">54.60</td>
-    </tr>
-    <tr>
-        <td align="center">Avg.</td>
-        <td align="center"><strong>58.28</strong></td>
-        <td align="center">56.35</td>
-        <td align="center">58.05</td>
-        <td align="center">51.73</td>
-        <td align="center">52.60</td>
-    </tr>
-</table>
-
-<br>
 
 ## Contributors