Add new containers in main index

docs/index.md

@@ -119,23 +119,27 @@ NeMo Evaluator Launcher provides pre-built evaluation containers for different e
 
 | Container | Description | NGC Catalog | Latest Tag | Supported benchmarks |
 |-----------|-------------|-------------|------------| ------------|
-| **agentic_eval** | Agentic AI evaluation framework | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/agentic_eval) | `25.08.1` | Agentic Eval Topic Adherence, Agentic Eval Tool Call, Agentic Eval Goal and Answer Accuracy |
-| **bfcl** | Function calling | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/bfcl) | `25.08.1` | BFCL v2 and v3 |
-| **bigcode-evaluation-harness** | Code generation evaluation | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/bigcode-evaluation-harness) | `25.08.1` | MBPP, MBPP-Plus, HumanEval, HumanEval+, Multiple (cpp, cs, d, go, java, jl, js, lua, php, pl, py, r, rb, rkt, rs, scala, sh, swift, ts) |
-| **garak** | Safety and vulnerability testing | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/garak) | `25.08.1` | Garak |
-| **helm** | Holistic evaluation framework | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/helm) | `25.08.1` | MedHelm |
-| **hle** | Academic knowledge and problem solving | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/hle) | `25.08.1` | HLE |
-| **ifbench** | Instruction following | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/ifbench) | `25.08.1` | IFBench |
-| **livecodebench** | Coding | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/livecodebench) | `25.08.1` | LiveCodeBench (v1-v6, 0724_0125, 0824_0225) |
-| **lm-evaluation-harness** | Language model benchmarks | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/lm-evaluation-harness) | `25.08.1` | ARC Challenge (also multilingual), GSM8K, HumanEval, HumanEval+, MBPP, MINERVA MMMLU-Pro, RACE, TruthfulQA, AGIEval, BBH, BBQ, CSQA, Frames, Global MMMLU, GPQA-D, HellaSwag (also multilingual), IFEval, MGSM, MMMLU, MMMLU-Pro, MMMLU-ProX (de, es, fr, it, ja), MMLU-Redux, MUSR, OpenbookQA, Piqa, Social IQa, TruthfulQA, WikiLingua, WinoGrande|
-| **mmath** | Multilingual math reasoning | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/mmath) | `25.08.1` | EN, ZH, AR, ES, FR, JA, KO, PT, TH, VI |
-| **mtbench** | Multi-turn conversation evaluation | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/mtbench) | `25.08.1` | MT-Bench |
-| **rag_retriever_eval** | RAG system evaluation | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/rag_retriever_eval) | `25.08.1` | RAG, Retriever |
-| **safety-harness** | Safety and bias evaluation | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/safety-harness) | `25.08.1` | Aegis v2, BBQ, WildGuard |
-| **scicode** | Coding for scientific research | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/scicode) | `25.08.1` | SciCode |
-| **simple-evals** | Common evaluation tasks | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/simple-evals) | `25.08.1` | GPQA-D, MATH-500, AIME 24 & 25, HumanEval, MGSM, MMMLU, MMMLU-Pro, MMMLU-lite (AR, BN, DE, EN, ES, FR, HI, ID, IT, JA, KO, MY, PT, SW, YO, ZH), SimpleQA |
-| **tooltalk** | Tool usage evaluation | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/tooltalk) | `25.08.1` | ToolTalk |
-| **vlmevalkit** | Vision-language model evaluation | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/vlmevalkit) | `25.08.1` | AI2D, ChartQA, OCRBench, SlideVQA |
+| **agentic_eval** | Agentic AI evaluation framework | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/agentic_eval) | `25.09` | Agentic Eval Topic Adherence, Agentic Eval Tool Call, Agentic Eval Goal and Answer Accuracy |
+| **bfcl** | Function calling | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/bfcl) | `25.09` | BFCL v2 and v3 |
+| **bigcode-evaluation-harness** | Code generation evaluation | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/bigcode-evaluation-harness) | `25.09` | MBPP, MBPP-Plus, HumanEval, HumanEval+, Multiple (cpp, cs, d, go, java, jl, js, lua, php, pl, py, r, rb, rkt, rs, scala, sh, swift, ts) |
+| **compute-eval** | CUDA code evaluation | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/compute-eval) | `25.09` | CCCL, Combined Problems, CUDA |
+| **garak** | Safety and vulnerability testing | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/garak) | `25.09` | Garak |
+| **genai-perf** | GenAI performance benchmarking | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/genai-perf) | `25.09` | GenAI Perf Generation & Summarization |
+| **helm** | Holistic evaluation framework | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/helm) | `25.09` | MedHelm |
+| **hle** | Academic knowledge and problem solving | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/hle) | `25.09` | HLE |
+| **ifbench** | Instruction following | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/ifbench) | `25.09` | IFBench |
+| **livecodebench** | Coding | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/livecodebench) | `25.09` | LiveCodeBench (v1-v6, 0724_0125, 0824_0225) |
+| **lm-evaluation-harness** | Language model benchmarks | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/lm-evaluation-harness) | `25.09` | ARC Challenge (also multilingual), GSM8K, HumanEval, HumanEval+, MBPP, MINERVA MMMLU-Pro, RACE, TruthfulQA, AGIEval, BBH, BBQ, CSQA, Frames, Global MMMLU, GPQA-D, HellaSwag (also multilingual), IFEval, MGSM, MMMLU, MMMLU-Pro, MMMLU-ProX (de, es, fr, it, ja), MMLU-Redux, MUSR, OpenbookQA, Piqa, Social IQa, TruthfulQA, WikiLingua, WinoGrande|
+| **mmath** | Multilingual math reasoning | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/mmath) | `25.09` | EN, ZH, AR, ES, FR, JA, KO, PT, TH, VI |
+| **mtbench** | Multi-turn conversation evaluation | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/mtbench) | `25.09` | MT-Bench |
+| **nemo-skills** | Language model benchmarks (science, math, agentic)  | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/nemo_skills) | `25.09` | AIME 24 & 25, BFCL_v3, GPQA, HLE, LiveCodeBench, MMLU, MMLU-Pro |
+| **mtbench** | Multi-turn conversation evaluation | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/mtbench) | `25.09` | MT-Bench |
+| **rag_retriever_eval** | RAG system evaluation | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/rag_retriever_eval) | `25.09` | RAG, Retriever |
+| **safety-harness** | Safety and bias evaluation | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/safety-harness) | `25.09` | Aegis v2, BBQ, WildGuard |
+| **scicode** | Coding for scientific research | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/scicode) | `25.09` | SciCode |
+| **simple-evals** | Common evaluation tasks | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/simple-evals) | `25.09` | GPQA-D, MATH-500, AIME 24 & 25, HumanEval, MGSM, MMMLU, MMMLU-Pro, MMMLU-lite (AR, BN, DE, EN, ES, FR, HI, ID, IT, JA, KO, MY, PT, SW, YO, ZH), SimpleQA |
+| **tooltalk** | Tool usage evaluation | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/tooltalk) | `25.09` | ToolTalk |
+| **vlmevalkit** | Vision-language model evaluation | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/vlmevalkit) | `25.09` | AI2D, ChartQA, OCRBench, SlideVQA |
 
 ## Contribution Guide
 

docs/nemo-evaluator/index.md

@@ -100,20 +100,20 @@ NeMo Evaluator provides pre-built evaluation containers through the NVIDIA NGC c
 | **agentic_eval** | Agentic AI evaluation framework | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/agentic_eval) | `25.09` | agentic_eval_answer_accuracy, agentic_eval_goal_accuracy_with_reference, agentic_eval_goal_accuracy_without_reference, agentic_eval_topic_adherence, agentic_eval_tool_call_accuracy |
 | **bfcl** | Function calling | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/bfcl) | `25.09` | bfclv2, bfclv2_ast, bfclv2_ast_prompting, bfclv3, bfclv3_ast, bfclv3_ast_prompting |
 | **bigcode-evaluation-harness** | Code generation evaluation | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/bigcode-evaluation-harness) | `25.09` | humaneval, humaneval_instruct, humanevalplus, mbpp, mbppplus, mbppplus_nemo, multiple-cpp, multiple-cs, multiple-d, multiple-go, multiple-java, multiple-jl, multiple-js, multiple-lua, multiple-php, multiple-pl, multiple-py, multiple-r, multiple-rb, multiple-rkt, multiple-rs, multiple-scala, multiple-sh, multiple-swift, multiple-ts |
-| **compute-eval** | CUDA code evaluation | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/compute-eval) | `25.09` | compute-eval |
+| **compute-eval** | CUDA code evaluation | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/compute-eval) | `25.09` | cccl_problems, combined_problems, cuda_problems |
 | **garak** | Safety and vulnerability testing | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/garak) | `25.09` | garak |
-| **genai-perf** | GenAI performance benchmarking | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/genai-perf) | `25.09` | genai-perf |
+| **genai-perf** | GenAI performance benchmarking | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/genai-perf) | `25.09` | genai_perf_generation, genai_perf_summarization |
 | **helm** | Holistic evaluation framework | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/helm) | `25.09` | ci_bench, ehr_sql, head_qa, med_dialog_healthcaremagic, med_dialog_icliniq, medbullets, medcalc_bench, medec, medhallu, medi_qa, medication_qa, mtsamples_procedures, mtsamples_replicate, pubmed_qa, race_based_med |
 | **hle** | Academic knowledge and problem solving | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/hle) | `25.09` | hle |
 | **ifbench** | Instruction following | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/ifbench) | `25.09` | ifbench |
 | **livecodebench** | Coding | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/livecodebench) | `25.09` | AA_codegeneration, codeexecution_v2, codeexecution_v2_cot, codegeneration_notfast, codegeneration_release_latest, codegeneration_release_v1, codegeneration_release_v2, codegeneration_release_v3, codegeneration_release_v4, codegeneration_release_v5, codegeneration_release_v6, livecodebench_0724_0125, livecodebench_0824_0225 |
 | **lm-evaluation-harness** | Language model benchmarks | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/lm-evaluation-harness) | `25.09` | adlr_arc_challenge_llama, adlr_gsm8k_fewshot_cot, adlr_humaneval_greedy, adlr_humanevalplus_greedy, adlr_mbpp_sanitized_3shot_greedy, adlr_mbppplus_greedy_sanitized, adlr_minerva_math_nemo, adlr_mmlu_pro_5_shot_base, adlr_race, adlr_truthfulqa_mc2, agieval, arc_challenge, arc_challenge_chat, arc_multilingual, bbh, bbh_instruct, bbq, commonsense_qa, frames_naive, frames_naive_with_links, frames_oracle, global_mmlu, global_mmlu_ar, global_mmlu_bn, global_mmlu_de, global_mmlu_en, global_mmlu_es, global_mmlu_fr, global_mmlu_full, global_mmlu_full_am, global_mmlu_full_ar, global_mmlu_full_bn, global_mmlu_full_cs, global_mmlu_full_de, global_mmlu_full_el, global_mmlu_full_en, global_mmlu_full_es, global_mmlu_full_fa, global_mmlu_full_fil, global_mmlu_full_fr, global_mmlu_full_ha, global_mmlu_full_he, global_mmlu_full_hi, global_mmlu_full_id, global_mmlu_full_ig, global_mmlu_full_it, global_mmlu_full_ja, global_mmlu_full_ko, global_mmlu_full_ky, global_mmlu_full_lt, global_mmlu_full_mg, global_mmlu_full_ms, global_mmlu_full_ne, global_mmlu_full_nl, global_mmlu_full_ny, global_mmlu_full_pl, global_mmlu_full_pt, global_mmlu_full_ro, global_mmlu_full_ru, global_mmlu_full_si, global_mmlu_full_sn, global_mmlu_full_so, global_mmlu_full_sr, global_mmlu_full_sv, global_mmlu_full_sw, global_mmlu_full_te, global_mmlu_full_tr, global_mmlu_full_uk, global_mmlu_full_vi, global_mmlu_full_yo, global_mmlu_full_zh, global_mmlu_hi, global_mmlu_id, global_mmlu_it, global_mmlu_ja, global_mmlu_ko, global_mmlu_pt, global_mmlu_sw, global_mmlu_yo, global_mmlu_zh, gpqa, gpqa_diamond_cot, gpqa_diamond_cot_5_shot, gsm8k, gsm8k_cot_instruct, gsm8k_cot_llama, gsm8k_cot_zeroshot, gsm8k_cot_zeroshot_llama, hellaswag, hellaswag_multilingual, humaneval_instruct, ifeval, m_mmlu_id_str, mbpp_plus, mgsm, mgsm_cot, mmlu, mmlu_cot_0_shot_chat, mmlu_instruct, mmlu_logits, mmlu_pro, mmlu_pro_instruct, mmlu_prox, mmlu_prox_de, mmlu_prox_es, mmlu_prox_fr, mmlu_prox_it, mmlu_prox_ja, mmlu_redux, mmlu_redux_instruct, musr, openbookqa, piqa, social_iqa, truthfulqa, wikilingua, winogrande |
 | **mmath** | Multilingual math reasoning | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/mmath) | `25.09` | mmath_ar, mmath_en, mmath_es, mmath_fr, mmath_ja, mmath_ko, mmath_pt, mmath_th, mmath_vi, mmath_zh |
 | **mtbench** | Multi-turn conversation evaluation | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/mtbench) | `25.09` | mtbench, mtbench-cor1 |
-| **nemo-skills** | NeMo Skills - a project to improve skills of LLMs - packaged by NVIDIA Eval Factory | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/nemo_skills) | `25.09` | nemo_skills |
+| **nemo-skills** | NeMo Skills - a project to improve skills of LLMs - packaged by NVIDIA Eval Factory | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/nemo_skills) | `25.09` | ns_aime2024, ns_aime2025, ns_aime2025_ef, ns_bfcl_v3, ns_gpqa, ns_gpqa_ef, ns_hle, ns_livecodebench, ns_mmlu, ns_mmlu_pro |
 | **rag_retriever_eval** | RAG system evaluation | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/rag_retriever_eval) | `25.09` | RAG, Retriever |
 | **safety-harness** | Safety and bias evaluation | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/safety-harness) | `25.09` | aegis_v2, aegis_v2_ar, aegis_v2_de, aegis_v2_es, aegis_v2_fr, aegis_v2_hi, aegis_v2_ja, aegis_v2_reasoning, aegis_v2_th, aegis_v2_zh-CN, bbq_full, bbq_small, wildguard |
-| **scicode** | Coding for scientific research | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/scicode) | aa_scicode, scicode, scicode_background |
+| **scicode** | Coding for scientific research | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/scicode) | `25.09`| aa_scicode, scicode, scicode_background |
 | **simple-evals** | Common evaluation tasks | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/simple-evals) | `25.09` | AA_AIME_2024, AA_math_test_500, AIME_2024, AIME_2025, aime_2024_nemo, aime_2025_nemo, gpqa_diamond, gpqa_diamond_aa_v2, gpqa_diamond_aa_v2_llama_4, gpqa_diamond_nemo, gpqa_extended, gpqa_main, humaneval, humanevalplus, math_test_500, math_test_500_nemo, mgsm, mmlu, mmlu_am, mmlu_ar, mmlu_ar-lite, mmlu_bn, mmlu_bn-lite, mmlu_cs, mmlu_de, mmlu_de-lite, mmlu_el, mmlu_en, mmlu_en-lite, mmlu_es, mmlu_es-lite, mmlu_fa, mmlu_fil, mmlu_fr, mmlu_fr-lite, mmlu_ha, mmlu_he, mmlu_hi, mmlu_hi-lite, mmlu_id, mmlu_id-lite, mmlu_ig, mmlu_it, mmlu_it-lite, mmlu_ja, mmlu_ja-lite, mmlu_ko, mmlu_ko-lite, mmlu_ky, mmlu_llama_4, mmlu_lt, mmlu_mg, mmlu_ms, mmlu_my-lite, mmlu_ne, mmlu_nl, mmlu_ny, mmlu_pl, mmlu_pro, mmlu_pro_llama_4, mmlu_pt, mmlu_pt-lite, mmlu_ro, mmlu_ru, mmlu_si, mmlu_sn, mmlu_so, mmlu_sr, mmlu_sv, mmlu_sw, mmlu_sw-lite, mmlu_te, mmlu_tr, mmlu_uk, mmlu_vi, mmlu_yo, mmlu_yo-lite, mmlu_zh-lite, simpleqa |
 | **tooltalk** | Tool usage evaluation | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/tooltalk) | `25.09` | tooltalk |
 | **vlmevalkit** | Vision-language model evaluation | [Link](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/eval-factory/containers/vlmevalkit) | `25.09` | ai2d_judge, chartqa, ocrbench, slidevqa |