- IBM offers an optimized version of Mixtral-8x7B that showed
potential to cut latency by up to 75%
- Adds to growing catalogue of IBM, third-party and
open-source models to give clients choice and flexibility
- Latest open-source model available on watsonx AI and data
platform with enterprise-ready AI studio, data store and governance
capabilities
ARMONK,
N.Y., Feb. 29, 2024 /CNW/ -- IBM (NYSE:
IBM) today announced the availability of the popular open-source
Mixtral-8x7B large language model (LLM), developed by Mistral AI,
on its watsonx AI and data platform, as it continues to expand
capabilities to help clients innovate with IBM's own foundation
models and those from a range of open-source providers.
IBM offers an optimized version of Mixtral-8x7B that, in
internal testing, was able to increase throughput — or the amount
of data that can be processed in a given time period — by 50
percent when compared to the regular model.1 This could
potentially cut latency by 35-75 percent, depending on batch size —
speeding time to insights. This is achieved through a process
called quantization, which reduces model size and memory
requirements for LLMs and, in turn, can speed up processing to help
lower costs and energy consumption.
The addition of Mixtral-8x7B expands IBM's open, multi-model
strategy to meet clients where they are and give them choice and
flexibility to scale enterprise AI solutions across their
businesses. Through decades-long AI research and development, open
collaboration with Meta and Hugging Face, and partnerships
with model leaders, IBM is expanding its watsonx.ai model
catalog and bringing in new capabilities, languages, and
modalities.
IBM's enterprise-ready foundation model choices and its watsonx
AI and data platform can empower clients to use generative AI
to gain new insights and efficiencies, and create new business
models based on principles of trust. IBM enables clients to
select the right model for the right use cases and
price-performance goals for targeted business domains like
finance.
Mixtral-8x7B was built using a combination of Sparse modeling —
an innovative technique that finds and uses only the most essential
parts of data to create more efficient models — and the
Mixture-of-Experts technique, which combines different models
("experts") that specialize in and solve different parts of a
problem. The Mixtral-8x7B model is widely known for its ability to
rapidly process and analyze vast amounts of data to provide
context-relevant insights.
"Clients are asking for choice and flexibility to deploy models
that best suit their unique use cases and business requirements,"
said Kareem Yusuf, Ph.D, Senior Vice
President, Product Management & Growth, IBM Software. "By
offering Mixtral-8x7B and other models on watsonx, we're not only
giving them optionality in how they deploy AI — we're empowering a
robust ecosystem of AI builders and business leaders with tools and
technologies to drive innovation across diverse industries and
domains."
This week, IBM also announced the availability of
ELYZA-japanese-Llama-2-7b, a Japanese
LLM model open-sourced by ELYZA Corporation, on watsonx. IBM also
offers Meta's open-source models Llama-2-13B-chat and Llama-2-70B-chat and other third-party models on watsonx,
with more to come in the next few months.
Statements regarding IBM's future direction and intent are
subject to change or withdrawal without notice and represent goals
and objectives only.
Media Contact:
Amy Angelini
alangeli@us.ibm.com
1 Based on IBM testing over two days using internal
workloads captured on an instance of watsonx for IBM use.
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SOURCE IBM