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U.S. chip-maker Intel Corporation is reportedly in early-stage talks to acquire AI-chip startup SambaNova Systems, according to sources cited by Bloomberg News. The potential acquisition would mark a strategic push for Intel into the growing artificial-intelligence hardware space, after previous efforts to roll out its own AI-GPU products lagged behind competitors.
SambaNova, which designs custom AI processors and systems, has been working with bankers to gauge interest from potential buyers. While the company achieved a valuation of around USD 5 billion in a 2021 funding round, any deal today would likely value it below that level. The discussions remain preliminary and there is no guarantee they will lead to a transaction.
Intel has longstanding ties to SambaNova: Intel’s venture arm, Intel Capital, is an investor in the startup, and former Intel executive and investor Lip‑Bu Tan serves as SambaNova’s executive chairman. Industry watchers view such a move as a way for Intel to accelerate its AI hardware roadmap and better compete in the data-centre and cloud-inference markets. The companies declined to comment on the report.
Does the new LBT Intel really need and see a path with yet another also-ran AI architecture ? SambaNova did some smart things (rack optimized architecture, system software), but are carrying around the burden of 3 year chips when the industry is on a yearly cadence. The whole 16 bit “accuracy” is actually a liability for most LLMs today, though maybe an asset for HPC.
“SambaNova’s RDU excels at running very large, specialized models with high efficiency, in part due to the three-tier memory architecture mentioned previously. Independent benchmarks from Artificial Analysis measured SambaNova’s performance on the DeepSeek-R1 671B model at 198-255 output TPS. Note that this is 16 RDU chips, while Nvidia generates 250 tokens per second with just eight GPUs. albeit using FP4. SambaNova emphasizes its ability to run the full, unquantized (16-bit) version of these massive models on a single system, a feat it claims competitors achieve only by using smaller, less accurate model versions or significantly more hardware.”
