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 84991
stable-diffusion-inpainting
booksforcharlie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 ↗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 ↗Qwen3.5-2B-GGUF
Boollm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 · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Qwen3.5-4B-GGUF
Boollm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 · Image→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗PORNHUBAI
Boombaaa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 Image→ Output Video
Price not verifiedCheck multimodal and channel pricing separately
View details ↗dasllama-tts
borisbat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 Audio
Price not verifiedCheck multimodal and channel pricing separately
View details ↗finki-gpt-140M
Borjan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 ↗my_awesome_eli5_clm-model
bornil20005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。
Input Not verified→ Output Not verified
Price not verifiedCheck multimodal and channel pricing separately
View details ↗e5-sk-large
borsimnet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 Embedding
Price not verifiedCheck multimodal and channel pricing separately
View details ↗bitnet_b1_58-xl_q8_0_gguf
BoscoTheDog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 ↗Danube_3-500M_Chat_GGUF
BoscoTheDog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 ↗h2o-danube3-500m-chat_chunked
BoscoTheDog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 ↗phi_3_mini_128k_it_russian_Q4_K_M_chunked
BoscoTheDog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 ↗higgs-audio-v2-tokenizer
bosonaiCheck our open-source repository https://github.com/boson-ai/higgs-audio for more details! > [!TIP] > For **licensing** inquiries (e.g., commercial use) or **collaboration** opportunities, please reach out to us at contact@boson.ai. We introduce a new discretized audio tokenizer that runs at just **25 frames per second** while keeping—or even improving—audio quality compared to tokenizers with twice the bitrate. Our model is the first to train on **24 kHz data** covering speech, music, and sound events in one unified system. It also uses a simple non-diffusion encoder/decoder for fast, batch inference.
Input Text→ Output Embedding
Price not verifiedCheck multimodal and channel pricing separately
View details ↗higgs-audio-v3-8b-stt
bosonai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 Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗higgs-audio-v3-8b-stt-v2
bosonaiA speech-to-text model combining a Whisper-Large-v3 encoder with a Qwen3-8B decoder (8.91B total parameters), fine-tuned with LoRA on diverse ASR benchmarks.
Input Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗higgs-audio-v3-stt
bosonai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 Audio→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗Higgs-Llama-3-70B
bosonaiHiggs-Llama-3-70B is post-trained from meta-llama/Meta-Llama-3-70B, specially tuned for role-playing while being competitive in general-domain instruction-following and reasoning. We perform supervised fine-tuning with our in-house instruction-following and chat datasets. Afterwards, we construct preference pairs with a semi-automated pipeline that relies on both human-labelers and our private LLMs. We conduct iterative preference optimization to align the model. During alignment, we adopted a special strategy to align the model’s behavior with the system message. Compared with other instruct models, Higgs models follow their roles more closely. All benchmarks lead to eventual overfitting, including those for LLMs. Training on data, particularly beneficial for benchmarks typically does not improve (or even worsen) role-playing performance. We worked to exclude benchmark data, including their training examples, from our fine-tuning data.
Input Text→ Output Text
Price not verifiedCheck multimodal and channel pricing separately
View details ↗higgs-tts-2-3b-base
bosonaiCheck our open-source repository https://github.com/boson-ai/higgs-audio for more details! > **Rename note:** Higgs Audio V2 and Higgs Audio V2 Generation have been renamed to Higgs TTS 2. We are open-sourcing Higgs TTS 2, a powerful audio foundation model pretrained on over 10 million hours of audio data and a diverse set of text data. Despite having no post-training or fine-tuning, Higgs TTS 2 excels in expressive audio generation, thanks to its deep language and acoustic understanding.
Input Text→ Output Audio
Price not verifiedCheck multimodal and channel pricing separately
View details ↗higgs-tts-3-4b
bosonaiHiggs TTS 3 is built for voice chat: it **speaks, not just reads**. It turns model responses into expressive conversational speech across **100+ languages**, with **zero-shot voice cloning** and **inline control** over emotion, style, prosody, pauses, and sound effects. > [!TIP] > Released for research and non-commercial use under the **Boson Higgs TTS 3 Research and Non-Commercial License**. Production, hosted APIs, embedding in a product/service, or reselling the model requires a separate commercial license. Prohibited: voice cloning without consent, impersonation, fraud, election deception, biometric surveillance, or any unlawful use. > [!TIP] > **Free for digital creators — including monetized content.** Under the license's **Creator Use Grant**, creators may use Higgs TTS 3 to make and monetize podcasts, videos, and social posts for free. The one requirement is to credit *Boson AI's Higgs Audio* — either in the audio or prominently in the accompanying text (e.g., the video description or show notes). Suggested credit: *"This audio was created with Boson AI's Higgs Audio — https://www.boson.ai/higgs-audio"*. See the Creator Use section below.
Input Text→ Output Audio
Price not verifiedCheck multimodal and channel pricing separately
View details ↗hubert_base
bosonaiA general-purpose HuBERT-Base checkpoint released by Boson AI, used inside the Higgs Audio Tokenizer as the semantic teacher. - Standard HuBERT-Base architecture (12 transformer layers, hidden size 768, ~95M params) - 16 kHz audio input - Loadable via `AutoModel` with `trust_remote_code=True` - Outputs 768-dim per-layer hidden states (`output_hidden_states=True`) The Higgs Audio Tokenizer distills semantic features from this HuBERT into its semantic branch. From `boson_multimodal/audio_processing/higgs_audio_tokenizer.py` (`semantic_techer="hubert_base_general"`):
Input Text→ Output Embedding
Price not verifiedCheck multimodal and channel pricing separately
View details ↗transcendent-logic-model
BosonicJustin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 ↗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.