6 Best 7B Local LLM Model

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image 37 - 6 Best 7B Local LLM Model

Language is a gateway to understanding, and in AI, the power of language models is boundless. Today, we unveil the top three 7B LLM (Large Language Model) models that have made remarkable strides in revolutionizing natural language processing.

These models have demonstrated extraordinary capabilities in comprehending and generating human-like text, pushing the boundaries of AI communication. Let’s dive into the highlights of these exceptional models:

Contact me if you think some other model should be on the list.


WizardLM-2 7B packs a punch, achieving performance comparable to models ten times its size. This makes it ideal for users with limited computational resources. While smaller than its counterparts, WizardLM-2 7B outshines Qwen1.5-14B-Chat and Starling-LM-7B-beta, and holds its own against the mighty Qwen1.5-32B-Chat.

Important Note: WizardLM-2 7B is heavily censored and may not be suitable for all tasks.


Another contender in the local LLM ring is FuseChat-7B-VaRM, and this one’s a beast! It mashes together three super strong chat LLMs (NH2-Mixtral-8x7B, NH2-Solar-10.7B, and OpenChat-3.5-7B) to create a real conversation champion.

Here’s what makes FuseChat-7B-VaRM stand out from the crowd:

  • Blows the Doors Off Benchmarks: FuseChat-7B-VaRM scored a whopping 8.22 on the MT-Bench test, leaving other 7B and even some 34B models like Starling-7B and Yi-34B-Chat in the dust. It even crushes popular choices like GPT-3.5 (March) and Claude-2.1, and comes really close to the mighty Mixtral-8x7B-Instruct.
  • Fusion with Flair: This LLM isn’t just one trick pony. It combines different strengths from various architectures and scales to become a well-rounded pro at all things conversation.
  • Less Censorship, More Fun: FuseChat-7B-VaRM isn’t afraid to let loose a bit. Compared to other local LLMs, it has fewer restrictions, which can make for more interesting and open chats.


Looking for an AI that can code, chat, and explain complex topics? Look no further than Dolphin-2.8-Mistral-7b-v02! This innovative model combines the power of the unreleased Mistral-7b-v02 base model with the fine-tuned capabilities of Dolphin-2.8.

Key Features:

  • Conversational Coding: Write scripts, debug code, and get coding help – all through natural conversation.
  • Clear Instructions: Need help fixing something? Dolphin can explain complex tasks in a way that’s easy to understand.
  • Uncensored and Aligned: The dataset is filtered to remove bias while maintaining informative content.
  • 32k Context Window: Keeps track of a significant conversation history for a more natural flow of interaction.

Mistral-7B Instruct-v0.2

The Mistral-7B Instruct-v0.2 Large Language Model (LLM) is a powerful tool for natural language processing tasks, fine-tuned from the Mistral-7B-v0.2 generative text model. This variant was trained on a diverse range of publicly available conversation datasets, enabling it to generate human-like responses to given prompts. With its ability to understand context and respond appropriately, the Mistral-7B Instruct model is ideal for applications such as chatbots, virtual assistants, and language translation software.

One of the key advantages of the Mistral-7B Instruct model is its ease of use. Despite its impressive capabilities, it does not require extensive training or expertise to operate effectively. In fact, the model’s creators demonstrate its potential with a simple, straightforward fine-tuning process.

Gemma 1.1 7B

Gemma 1.1 7B (IT) builds upon the original instruction-tuned Gemma release, offering significant advancements in several key areas. Here’s a breakdown of its strengths:

  • Enhanced Quality and Factuality: Trained using a novel RLHF method, Gemma 1.1 delivers more accurate and reliable outputs, making it ideal for tasks requiring factual grounding.
  • Stronger Instruction Following: This iteration excels at understanding and adhering to specific instructions, ensuring your prompts are executed precisely.
  • Improved Multi-Turn Conversation: A previous bug in multi-turn conversations has been fixed, leading to smoother and more coherent interactions.
  • Varied Response Openings: The repetitive “Sure,” response at the beginning of responses is no longer a constant, offering a more natural flow in communication.

Important Caveat: It’s essential to acknowledge that Gemma 1.1 prioritizes safety by employing a strong content filter. This filtering can be quite strict, sometimes hindering the model’s ability to address creative tasks effectively. In certain instances, this filtering might render the model almost unusable for tasks requiring unrestricted creative freedom.

OpenChat 3.5B Gemma

OpenChat 3.5B Gemma stands out as the most capable Gemma model available, achieving performance that rivals the Mistral-based OpenChat and surpassing both Gemma-7b and Gemma-7b-it. This powerful generalist model is trained with OpenChat’s C-RLFT on the openchat-3.5-06 dataset.

  • Exceptional performance: OpenChat 3.5B Gemma delivers unmatched capabilities among Gemma models.
  • Generalist expertise: Handles a wide range of tasks with proficiency.
  • Coding prowess: Proven ability to assist with coding tasks.
  • Reasoning skills: Offers decent reasoning abilities to tackle various problems.
  • Versatile assistant: Can be a competent assistant for a multitude of tasks.
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