longformer-action-ro
LibrAI基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗DISCOVER & COMPARE
Explore AI models 85001
longformer-harmful-ro
LibrAI基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗L3.3-70B-Euryale-v2.3-AWQ
libraos基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Qwen3-14b-MLX-Q5
LibraxisAI基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗qwen3-tts-GGUF
librellama**No Tag :** means that the model belongs to the *base* model family **CustomVoice :** means that the model belongs to the *CustomVoice* model family **VoiceDesign :** means that the model belongs to the *VoiceDesign* model family **0.6b :** means that the model has 0.6 billion parameters **1.7b :** means that the model has 1.7 billion parameters **f16 :** means that the model has no quantization applied to it ( full precision ) **q8_0 :** means that the model has been quantized to 8 bits.
Input Text→ Output Audio
Price not verifiedCheck multimodal and channel pricing separately
View details ↗gemma3
libretranslate基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Gemma-4-31B-it-abliterated-GGUF
LiconStudio基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗LTX-2.3-Multiple-Subject-Reference
LiconStudioThis model implements a novel approach to multi-reference video generation using **Multiple Subject Reference (MSR)**. Instead of introducing additional encoder branches or fusion modules, we transform multiple static reference images into a pseudo-video sequence that shares the same representation space as the target video. This LoRA requires the **ComfyUI-Licon-MSR** plugin for ComfyUI. A sample workflow is included in the model files for easy testing and experimentation. Beyond identity preservation, the model can compose references according to textual relationship descriptions:
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗LTX-2.5-Multiple-Subject-Reference
LiconStudioV2 improves visual consistency, character motion, and camera behavior, and adds audio reference support. Environmental sound generation currently requires **background music in the voice-reference audio**. Without it, environmental sounds may not be generated correctly. **Licon MSR V2** is a multi-reference LoRA trained for **LTX-2.5**, with support for both visual and audio references.
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Ltx2.3-VBVR-lora-I2V
LiconStudio**To ensure training quality, we preprocessed the full 1,000,000 videos from the official dataset and randomly sample during training to maintain data diversity. We adopt the official parameters with batch_size=16 and rank=32 to prevent catastrophic forgetting caused by excessively large rank.** The VBVR dataset contains 100 reasoning task categories, with ~10,000 variants per task, totaling ~1M videos. Main task types include: This model is trained on the VBVR (Video Benchmark for Video Reasoning) dataset from video-reason.com.
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Minimax-H3-VBVR
LiconStudio**Licon VBVR** is an image-to-video LoRA for **MiniMax-H3**, trained on VBVR data rebuilt and reprocessed specifically for H3. It improves object consistency and character action logic, reducing unintended object duplication, clipping, and interpenetration during motion and interactions. I rebuilt the VBVR training data around H3's characteristics, adapting data preparation and preprocessing to its training pipeline. The goal is to transfer structured motion and interaction patterns into practical video generation, with a focus on object consistency, spatial relationships, and action logic.
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Qwen3.5-27B-abliterated-GGUF
LiconStudio基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗VBVR-wan2.2-comfy-bf16
LiconStudio基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗flux_controlnet
licyk基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗flux-model
licyk基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗sd-extensions-model
licyk基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗MergeStove2.5D
LieDeath基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Image
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Lightweight-2-5D-LUNA16
Lien-Feng基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Image→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗xiaobu-embedding-v2
lier007基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Basic profile indexed · More details to follow
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Qwen3-VL-Embedding-2B-AWQ-4bit
LifetimeMistake基础档案已收录，详细介绍后续补充。可先查看厂商、分类与来源。
Input Text→ Output Embedding
Price not verifiedCheck multimodal and channel pricing separately
View details ↗No matching models
Adjust provider, category or input/output filters. New models are added continuously.
COST EXPLORER
Great models. Clear costs.
Adjust monthly token usage to compare estimated API costs.
1 M = 1 million tokens · USD
Compares base text-token rates within the same channel
Compares base text-token rates within the same channel
Uses collected, comparable USD-per-million-token rates. Snapshots exclude cache discounts, tiers, extra reasoning output and taxes. Check current source prices.
MODEL HANDBOOK
Understand before you choose
How should API prices be compared?+
Separate input, output and cache rates, then estimate the same workload. Image, audio and video rates may use items, duration or resolution rather than tokens.
Do open weights mean free commercial use?+
Not necessarily. Check each version’s license, commercial restrictions and policies. Self-hosting also incurs compute and maintenance costs.
Is the top-ranked model the best for me?+
Rankings depend on tasks, versions and methods. Compare accuracy, latency, reliability and costs on your own workload.