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nousresearchListed Jul 29
Nous: Hermes 3 70B Instruct
Hermes 3 is a generalist language model with many improvements over Hermes 2, including advanced agentic capabilities, much better roleplaying, reasoning, multi-turn conversation, long context coherence,…
131.1K context70BStructured outputOpen weightsNo reported score
No reported score
meta-llamaListed Jul 23
Meta: Llama 3.1 70B Instruct
Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 70B instruct-tuned version is optimized for high quality dialogue usecases. It has demonstrated strong...
131.1K context70BTool callingStructured outputNo reported score
No reported score
$0.40in$0.40out/ 1M tokens · USDDeepInfra · via OpenRouter · 3 endpointsdeepinfra/turbo · quantization=fp8
meta-llamaListed Jul 23
Meta: Llama 3.1 8B Instruct
Meta's latest class of model (Llama 3.1) launched with a variety of sizes & flavors. This 8B instruct-tuned version is fast and efficient. It has demonstrated strong performance compared to...
131.1K context8BTool callingStructured outputNo reported score
No reported score
$0.02in$0.04out/ 1M tokens · USDDeepInfra · via OpenRouter · 6 endpointsdeepinfra/fp8 · quantization=fp8
mistralaiListed Jul 19
Mistral: Mistral Nemo
A 12B parameter model with a 128k token context length built by Mistral in collaboration with NVIDIA. The model is multilingual, supporting English, French, German, Spanish, Italian, Portuguese, Chinese,…
131.1K contextTool callingStructured outputNo reported score
No reported score
$0.0166in$0.0216out/ 1M tokens · USDIo Net · via OpenRouter · 7 endpointsio-net/fp16 · quantization=fp16
meta-llamaListed Jul 18
Llama-3.1-8B-Instruct
131.1K context8BOpen weightsTool callingNo reported score
No reported score
openaiListed Jul 17
whisper-large-v3
Whisper is a general-purpose speech recognition model. It is trained on a large dataset of diverse audio and is also a multi-task model that can perform multilingual speech recognition as well as speech…
Audio inputOpen weights
googleListed Jul 13
Google: Gemma 2 27B
Gemma 2 27B by Google is an open model built from the same research and technology used to create the Gemini models. Gemma models are well-suited for a variety of...
8.2K context27BStructured outputOpen weightsNo reported score
No reported score
$0.65in$0.65out/ 1M tokens · USDNextBit · via OpenRouter · 2 endpointsnextbit/int4 · quantization=int4
No reported score
intfloatListed Jun 4
Intfloat: Multilingual-E5-Large
The multilingual-e5-large embedding model encodes sentences, paragraphs, and documents across over 90 languages into a 1024-dimensional dense vector space, delivering robust semantic embeddings optimized…
512 contextOpen weightsNo reported score
No reported score
BAAIListed May 27
bge-m3
BGE-M3 is a versatile text embedding model that supports multi-functionality, multi-linguality, and multi-granularity, allowing it to perform dense retrieval, multi-vector retrieval, and sparse retrieval in…
8.2K contextOpen weightsNo reported score
No reported score
mistralaiListed Apr 17
Mistral: Mixtral 8x22B Instruct
Mistral's official instruct fine-tuned version of Mixtral 8x22B. It uses 39B active parameters out of 141B, offering unparalleled cost efficiency for its size. Its strengths include: - strong math, coding,...
65.5K contextTool callingStructured outputNo reported score
No reported score
No reported score
Price not listed
Price not listed
intfloatListed Nov 22
Intfloat: E5-Base-v2
The e5-base-v2 embedding model encodes English sentences and paragraphs into a 768-dimensional dense vector space, producing efficient and high-quality semantic embeddings optimized for tasks such as…
512 contextOpen weightsNo reported score
No reported score
thenlperListed Nov 22
gte-base
The GTE models are trained by Alibaba DAMO Academy. They are mainly based on the BERT framework and currently offer three different sizes of models, including GTE-large, GTE-base, and GTE-small. The GTE…
512 contextOpen weightsNo reported score
No reported score
intfloatListed Nov 22
Intfloat: E5-Large-v2
The e5-large-v2 embedding model maps English sentences, paragraphs, and documents into a 1024-dimensional dense vector space, delivering high-accuracy semantic embeddings optimized for retrieval, semantic…
512 contextOpen weightsNo reported score
No reported score
thenlperListed Nov 22
gte-large
The GTE models are trained by Alibaba DAMO Academy. They are mainly based on the BERT framework and currently offer three different sizes of models, including GTE-large, GTE-base, and GTE-small. The GTE…
512 contextOpen weightsNo reported score
No reported score
BAAIListed Nov 22
bge-base-en-v1.5
BGE embedding is a general Embedding Model. It is pre-trained using retromae and trained on large-scale pair data using contrastive learning. Note that the goal of pre-training is to reconstruct the text,…
512 contextOpen weightsNo reported score
No reported score
BAAIListed Nov 22
bge-large-en-v1.5
BGE embedding is a general Embedding Model. It is pre-trained using retromae and trained on large-scale pair data using contrastive learning. Note that the goal of pre-training is to reconstruct the text,…
512 contextOpen weightsNo reported score
No reported score
Price not listed
undi95Listed Jul 22
ReMM SLERP 13B
A recreation trial of the original MythoMax-L2-B13 but with updated models. #merge
6.1K context13BStructured outputOpen weightsNo reported score
No reported score
$0.35in$0.65out/ 1M tokens · USDMancer 2 · via OpenRouter · 2 endpointsmancer/fp8 · quantization=fp8