Merge branch 'master' of https://github.com/yacy/yacy_search_server.git

1 files changed, 14 insertions, 14 deletions

diff --git a/htroot/LLMSelection_p.html b/htroot/LLMSelection_p.html
index c94e4e85b..baebcd342 100644
--- a/htroot/LLMSelection_p.html
+++ b/htroot/LLMSelection_p.html
@@ -61,20 +61,20 @@
       let cachedVisionTestImagePromise = null;
 
       const RECOMMENDED_MODELS = [
-        ["hf.co/tiiuae/Falcon-H1-0.5B-Instruct-GGUF:Q4_K_M",                                     "0.50", "0.5GB", "english-only minimalistic model for small devices", "Technology Innovation Institute, Dubai", "falcon-llm-license"],
-        ["llama3.2:1b-instruct-q4_K_M",                                                          "0.10", "1.5GB", "A good 1B model", "Meta", "llama3.2"],
-        ["llama3.2:3b-instruct-q4_K_M",                                                          "0.66",   "3GB", "A good 3B model", "Meta", "llama3.2"],
-        ["qwen3-vl:2b-instruct-q4_K_M",                                                          "0.73",   "3GB", "A very small vision-model, can understand what is sees in images"],
-        ["qwen3:4b-instruct-2507-q4_K_M",                                                        "7.70",   "3GB", "Exceptional good 4B model", "Alibaba", "apache-2.0"],
-        ["hf.co/mradermacher/Josiefied-Qwen3-4B-Instruct-2507-abliterated-v1-GGUF:Q4_K_M",       "4.41",   "3GB", "Uncensored version of qwen3:4b", "huggingface.co/Goekdeniz-Guelmez", "apache-2.0"],
-        ["hf.co/unsloth/medgemma-4b-it-GGUF:Q4_K_M",                                             "0.60",   "4GB", "Medical Knowledge and Vision", "Google", "health-ai-developer-foundations"],
-        ["olmo-3:7b-instruct-q4_K_M",                                                            "2.22",   "4GB", "open and accessible training data, open-source training code", "allenai.org", "apache-2.0"],
-        ["hf.co/bartowski/AGI-0_Art-0-8B-GGUF:Q4_K_M",                                           "11.9",   "6GB", "Exceptional good 8B model, ranking above ChatGPT-3.5", "AGI-0.com and Alibaba", "apache-2.0"],
-        ["phi4:14b-q4_K_M",                                                                      "5.24",  "10GB", "Very strong, made with synthetic data", "Microsoft", "mit"],
-        ["hf.co/mistralai/Magistral-Small-2509-GGUF:Q4_K_M",                                     "5.18",  "16GB", "European flagship model, strong multilangual, reasoning", "mistral.ai", "apache-2.0"],
-        ["hf.co/bartowski/cognitivecomputations_Dolphin-Mistral-24B-Venice-Edition-GGUF:Q4_K_M", "3.43",  "16GB", "Uncensored multilingual european Mistral-24B for role playing", "mistral.ai and dphn.ai", "apache-2.0"],
-        ["gemma3:27b-it-q4_K_M",                                                                 "4.81",  "20GB", "Strong content safety, multilingual support in over 140 languages", "google.com", "gemma"],
-        ["qwen3-vl:30b-a3b-instruct-q4_K_M",                                                     "17.33", "22GB", "Very fast, exceptional good 30B model, ranking above GPT-4-turbo, GPT-4.1-nano, GPT-o1, GPT-4o-mini", "Alibaba", "apache-2.0"]
+        //["hf.co/tiiuae/Falcon-H1-0.5B-Instruct-GGUF:Q4_K_M",  " 0.50","0.5GB", "english-only minimalistic model for small devices", "Technology Innovation Institute, Dubai", "falcon-llm-license"],
+        //["llama3.2:1b-instruct-q4_K_M",                       " 0.10",  "2GB", "A good 1B model", "Meta", "llama3.2"],
+        ["qwen2.5:1.5b-instruct-q4_K_M",                      " 0.88",  "2GB", "Good small model for 1GB RAM", "Alibaba", "apache-2.0"],
+        ["llama3.2:3b-instruct-q4_K_M",                       " 0.66",  "3GB", "A good 3B model", "Meta", "llama3.2"],
+        //["qwen3-vl:2b-instruct-q4_K_M",                       " 0.73",  "3GB", "A very small vision-model, can understand what is sees in images"],
+        ["qwen3:4b-instruct-2507-q4_K_M",                     " 7.70",  "3GB", "Exceptional good 4B model", "Alibaba", "apache-2.0"],
+        ["hf.co/unsloth/medgemma-4b-it-GGUF:Q4_K_M",          " 0.60",  "4GB", "Medical Knowledge and Vision", "Google", "health-ai-developer-foundations"],
+        ["olmo-3:7b-instruct-q4_K_M",                         " 2.22",  "4GB", "open and accessible training data, open-source training code", "allenai.org", "apache-2.0"],
+        //["phi4:14b-q4_K_M",                                   " 5.24", "10GB", "Strong, made with synthetic data", "Microsoft", "mit"],
+        ["hf.co/mradermacher/Ling-mini-2.0-GGUF:Q4_K_M",      "20.00", "14GB", "very fast MoE model with 1.4B activated parameters per expert", "InclusionAI", "mit"],
+        //["magistral:24b-small-2506-q4_K_M",                   " 2.37", "16GB", "European flagship model, strong multilangual, reasoning", "mistral.ai", "apache-2.0"],
+        //["gemma3:27b-it-q4_K_M",                              " 4.81", "20GB", "Strong content safety, multilingual support in over 140 languages", "google.com", "gemma"],
+        //["qwen3-vl:30b-a3b-instruct-q4_K_M",                  "17.33", "22GB", "Very fast, exceptional good 30B model, ranking above GPT-4-turbo, GPT-4.1-nano, GPT-o1, GPT-4o-mini", "Alibaba", "apache-2.0"],
+        ["qwen3.5:35b-a3b-q4_K_M",                            "44.63", "25GB", "Very fast MoE, exceptional good 35B model with vision, ranking above GPT-4-turbo, GPT-4.1-nano, GPT-o1, GPT-4o-mini", "Alibaba", "apache-2.0"]
       ];
 
       const MODEL_TABLE_HEADERS = ["Model", "Ranking", "Size", "Description", "Provider", "License", "Actions"];