Together Inference excels in providing a full-stack AI platform with its various features like GPU clusters and batch inference API, supported by significant funding of $533.5M in Series B. Meanwhile, ExLlamaV2, with $7.9B in other funding, focuses on local infrastructure for running large language models efficiently on consumer GPUs and offers extensive integration capabilities. Both tools cater to advanced AI application development but serve distinct community preferences and infrastructure needs.
Best for
Together Inference is the better choice when your team requires scalable AI solutions with real-time inference capabilities and extensive model support, particularly for data-driven decision support systems and personalized recommendation engines.
Best for
ExLlamaV2 is the better choice when the focus is on running large language models locally without reliance on cloud services, ideal for research and experimentation, or when seeking efficient integration with existing machine learning workflows.
Key Differences
Verdict
Together Inference is suited for companies seeking a robust, scalable AI platform with cloud integration for real-time applications. It offers a cost-effective solution with its open-source base and tiered subscription model. ExLlamaV2 is ideal for teams emphasizing local infrastructure and integration for machine learning workflows, with its strong financial backing and extensive employee base providing key community and support advantages. Choose based on the need for cloud reliance or local deployment capabilities.
Together Inference
Build what's next on the AI Native Cloud. Full-stack AI platform for inference, fine-tuning, and GPU clusters — powered by cutting-edge research.
Together Inference has been praised for its performance improvements and adaptability, specifically with its Aurora model, which offers faster decoding and continuously enhances itself over time. Users appreciate the open-source nature and contributions welcomed from the community, as well as expanding model support and improved efficiency. However, there are concerns about static draft models becoming less efficient with shifting traffic patterns, requiring frequent updates. Pricing sentiment isn't explicitly indicated, but the open-source aspect suggests positive reception in terms of cost-effectiveness. Overall, Together Inference holds a solid reputation for innovation and performance, especially in AI and coding spaces.
ExLlamaV2
A fast inference library for running LLMs locally on modern consumer-class GPUs - turboderp-org/exllamav2
While "ExLlamaV2" is not explicitly mentioned in the provided social mentions and reviews, the context around software development and tools highlights the strengths of integration with platforms like GitHub Copilot for efficient coding and workflow enhancements. Users generally appreciate tools that streamline processes and incorporate advanced features for complex tasks. The evolving nature of billing models, like the move to usage-based pricing for GitHub Copilot, indicates mixed feelings about pricing, with some users potentially wary of increased costs. Overall, software tools that improve developer productivity and offer seamless integration tend to have a positive reputation, though concerns around pricing changes can impact user sentiment.
Together Inference
-50% vs last weekExLlamaV2
-86% vs last weekTogether Inference
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Together Inference
Pricing found: $1.40, $4.40, $0.30, $0.06, $1.20
ExLlamaV2
Together Inference (6)
ExLlamaV2 (8)
Only in Together Inference (8)
Only in ExLlamaV2 (10)
Only in Together Inference (13)
Only in ExLlamaV2 (15)
Together Inference
ExLlamaV2
Together Inference
ExLlamaV2
Together Inference
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Together Inference
Introducing Mamba-3 🐍 Inference speeds are more i
Introducing Mamba-3 🐍 Inference speeds are more important than ever, driven by the rise in agents and inference-heavy RL rollouts. Linear models are
ExLlamaV2
Cooking up something new 🧑🍳 Join the waitlist for early access to technical preview of the GitHub Copilot app 👇 https://t.co/ODODKdvzOA https://t.co/1h7AJPAhiH
Cooking up something new 🧑🍳 Join the waitlist for early access to technical preview of the GitHub Copilot app 👇 https://t.co/ODODKdvzOA https://t.co/1h7AJPAhiH
Shared (3)
Only in ExLlamaV2 (2)
Together Inference is better for real-time processing tasks due to its real-time inference capabilities and cloud-integrated infrastructure.
Together Inference uses a subscription-based model with tiered options starting at $0.06, making it potentially more predictable, whereas ExLlamaV2 uses a tiered pricing model with concerns over usage-based pricing impacts.
ExLlamaV2 likely has better community support due to its larger company size (~6200 employees) and broader integration capabilities with developer tools.
While there is no direct integration mentioned, developers can potentially use each tool's strengths in complementary capacities within a broader AI infrastructure strategy.
ExLlamaV2 may be easier to get started with for developers interested in local infrastructure and seamless integration with developer tools such as FastAPI and Streamlit.
