Browse AI Models

DeepSeek

We present DeepSeek-V3, a strong Mixture-of-Experts (MoE) language model with 671B total parameters with 37B activated for each token. To achieve efficient inference and cost-effective training, DeepSeek-V3 adopts Multi-head Latent Attention (MLA) and DeepSeekMoE architectures, which were thoroughly validated in DeepSeek-V2. Furthermore, DeepSeek-V3 pioneers an auxiliary-loss-free strategy for load balancing and sets a multi-token prediction training objective for stronger performance.

Cohere

Command A is Cohere's latest flagship model with 111B parameters, designed for agentic enterprise applications. Features advanced tool use, multi-step reasoning, and retrieval-augmented generation.

DeepSeek

We present DeepSeek-Coder-V2, an open-source Mixture-of-Experts (MoE) code language model that achieves performance comparable to GPT4-Turbo in code-specific tasks. Specifically, DeepSeek-Coder-V2 is further pre-trained from an intermediate checkpoint of DeepSeek-V2 with additional 6 trillion tokens. Through this continued pre-training, DeepSeek-Coder-V2 substantially enhances the coding and mathematical reasoning capabilities of DeepSeek-V2, while maintaining comparable performance in general language tasks.

DeepSeek

DeepSeek-V2.5 is an upgraded version that combines DeepSeek-V2-Chat and DeepSeek-Coder-V2-Instruct. The new model integrates the general and coding abilities of the two previous versions. For model details, please visit DeepSeek-V2 page for more information.

Mistral AI

from mistral_common.tokens.tokenizers.mistral import MistralTokenizer from mistral_common.protocol.instruct.messages import UserMessage from mistral_common.protocol.instruct.request import ChatCompletionRequest

OpenAI

GPT-OSS 20B is OpenAI's first open-weight model, a 21B-parameter mixture-of-experts model with 3.6B active parameters per token. Features configurable reasoning effort (low/medium/high), full chain-of-thought visibility, and agentic capabilities including function calling. Runs on devices with 16GB of memory using MXFP4 quantization.

DeepSeek

We present DeepSeek-Coder-V2, an open-source Mixture-of-Experts (MoE) code language model that achieves performance comparable to GPT4-Turbo in code-specific tasks. Specifically, DeepSeek-Coder-V2 is further pre-trained from an intermediate checkpoint of DeepSeek-V2 with additional 6 trillion tokens. Through this continued pre-training, DeepSeek-Coder-V2 substantially enhances the coding and mathematical reasoning capabilities of DeepSeek-V2, while maintaining comparable performance in general language tasks.

DeepSeek

DeepSeek R1 Distill Qwen 7B is a 7B-parameter reasoning model distilled from the larger DeepSeek-R1. Based on Qwen2.5-Math-7B and fine-tuned on 800K samples from DeepSeek-R1, it delivers strong reasoning with 92.8% on MATH-500 and 49.1 on GPQA Diamond while being far more efficient than the full 671B model.

IBM

Granite-20B-Code-Instruct-8K is a 20B parameter model fine tuned from *Granite-20B-Code-Base-8K* on a combination of permissively licensed instruction data to enhance instruction following capabilities including logical reasoning and problem-solving skills.

NVIDIA

Nemotron Nano 8B is NVIDIA's reasoning model derived from Llama 3.1 8B Instruct, post-trained for switchable reasoning with on/off modes. Achieves 95.4% on MATH-500 and 54.1% on GPQA Diamond with reasoning enabled. Fits on a single RTX GPU for local deployment.

Defog

The model weights were updated at 7 AM UTC on Feb 7, 2024. The new model weights lead to a much more performant model – particularly for joins.

Tsinghua/Zhipu

We introduce CodeGeeX4-ALL-9B, the open-source version of the latest CodeGeeX4 model series. It is a multilingual code generation model continually trained on the GLM-4-9B, significantly enhancing its code generation capabilities. Using a single CodeGeeX4-ALL-9B model, it can support comprehensive functions such as code completion and generation, code interpreter, web search, function call, repository-level code Q&A, covering various scenarios of software development. CodeGeeX4-ALL-9B has achieved highly competitive performance on public benchmarks, such as BigCodeBench and NaturalCodeBench.

01.AI

🐙 GitHub • 👾 Discord • 🐤 Twitter • 💬 WeChat

Mistral AI

Codestral Mamba is an open code model based on the Mamba2 architecture. It performs on par with state-of-the-art Transformer-based code models. \ You can read more in the official blog post.

IBM

Granite-8B-Code-Instruct-4K is a 8B parameter model fine tuned from *Granite-8B-Code-Base-4K* on a combination of permissively licensed instruction data to enhance instruction following capabilities including logical reasoning and problem-solving skills.

DeepSeek

DeepSeek R1 Distill Qwen 1.5B is a compact reasoning model distilled from DeepSeek-R1, based on Qwen2.5-Math-1.5B. Fine-tuned on 800K curated samples, it achieves 83.9% on MATH-500 and supports chain-of-thought reasoning on resource-constrained devices.

Alibaba

Qwen 2.5 Coder 1.5B is Alibaba's compact code-specific language model from the Qwen2.5 Coder series. Trained on 5.5T tokens including source code, text-code grounding, and synthetic data. Features improvements in code generation, reasoning, and fixing while maintaining general and math capabilities.