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Intel forecast more than $500 million in accelerator revenue in the second half of 2024, with Gaudi products expected to build momentum into 2025. That was a forecast—not reported sales. On its October 2024 earnings call, Intel said it would miss its $500 million Gaudi revenue target for 2024. Intel has not provided a verified Gaudi 3 revenue figure in the cited sources.
What Intel forecast—and what it later said
On its April 25, 2024 earnings call, Intel expected to generate over $500 million in accelerator revenue in the second half of 2024. Intel described increasing momentum into 2025; the figure was a forward-looking target, not a tally of Gaudi 3 sales. Intel’s Q1 2024 earnings-call comments provide the original forecast.
By its October 31, 2024 Q3 call, Intel said it would not achieve its $500 million Gaudi revenue target for the year. That update means the original headline’s “this year” referred to 2024, and the target was subsequently missed. The cited official statements do not establish how much Gaudi 3 revenue Intel actually earned. Intel’s Q3 2024 earnings-call transcript records the update.
What Gaudi 3 is and how it is sold
Gaudi 3 is Intel data-center accelerator hardware for AI model training and inference. Intel introduced it in April 2024, saying OEM availability would begin in the second quarter in Universal Baseboard and open accelerator module configurations. Intel announced its commercial launch in September 2024. Its current product page also lists a PCIe Gen5 card, model HL-338, and a 32-node cluster reference design. See Intel’s April 2024 introduction and the Gaudi product page.
#1 Best Overall
- Professional AI & Creator Workstation: AMD Radeon AI PRO R9700 GPU with 32GB GDDR6 is engineered for AI development, professional content creation, and compute-intensive workloads.
- Massive 32GB Memory Capacity: 32GB of GDDR6 memory on a 256-bit bus provides ample bandwidth for large AI models, 8K video editing, and complex 3D rendering.
- Advanced RDNA 4 with AI Accelerators: 64 Compute Units with 3rd Gen Ray Tracing and dedicated 2nd Gen AI Accelerators for groundbreaking AI performance and visual computing.
- Professional Blower Cooling: Efficient single blower design exhausts heat directly out of the chassis, ideal for multi-GPU workstation and server configurations.
- Enterprise-Grade Thermal Solution: Vapor chamber heatsink with industrial Honeywell PTM7950 thermal interface material ensures reliable cooling under sustained professional loads.
This is enterprise equipment, not a typical consumer add-on: buyers generally need a compatible server or complete system. Intel named Dell Technologies, Hewlett Packard Enterprise, Lenovo, and Supermicro as OEMs. In May 2025, Intel said Gaudi 3 was available through Dell AI Factory. These announcements do not establish current inventory or availability for every configuration. Intel’s May 2025 Dell AI Factory announcement describes that route.
Intel’s product page describes standard Ethernet networking, open software resources, PyTorch integration, and use cases such as large language models, multimodal models, and enterprise retrieval-augmented generation. It lists IBM Cloud and Denvr Dataworks as cloud options, but that listing alone does not confirm a specific Gaudi 3 instance or its availability in a particular region. Check with the provider for current offerings.
Rank #2
- NVIDIA Volta GV100 Architecture — 4,608 CUDA Cores, 640 1st-Gen Tensor Cores delivering 14 TFLOPS FP32 and 112 TFLOPS deep learning performance for AI training, inference, HPC, and scientific computing workloads
- 32GB HBM2 ECC Memory — 900 GB/s Bandwidth — High-bandwidth memory on a 4096-bit bus with ECC error correction provides the memory capacity and throughput required for the largest AI models, simulations, and datasets
- PCIe 3.0 x16 Interface — 250W TDP — Standard PCIe Gen3 connectivity with passive cooling designed for enterprise rack server deployment in HPE ProLiant, Dell PowerEdge, and Supermicro platforms with adequate chassis airflow
- NVLink — Scale to 96GB Unified Memory — Connect two V100 GPUs via NVLink at 300 GB/s bi-directional bandwidth to scale GPU memory from 32GB to 96GB for larger AI training and HPC workloads
- Multi-Precision Computing — Supports FP64 (7 TFLOPS), FP32 (14 TFLOPS), FP16 (112 TFLOPS) and INT8 precision modes for flexible deployment across training, inference, and scientific simulation workloads
How to interpret Intel’s performance comparisons
Intel’s April 2024 launch announcement claimed Gaudi 3 provides four times Gaudi 2’s BF16 AI compute, 1.5 times its memory bandwidth, and twice its networking bandwidth. These are Intel’s product claims, not independent measurements established by the cited sources. The April announcement is the source for those comparisons.
Do these 3 things before closing this tab:
1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsIn September 2024, Intel also claimed up to 20% more throughput and twice the price/performance of Nvidia H100 for Llama 2 70B inference. The claim is specific to Intel’s stated workload and comparison; it should not be read as a general result across AI models or deployments. Intel’s September 2024 launch announcement gives the claim, but the cited materials do not provide a neutral, apples-to-apples comparison across systems.
Rank #3
- Built for Running LLMs Locally: RDNA 4, 128 AI Accelerators, up to 1,531 TOPS (INT4) for fast inference and fine-tuning
- 32GB GDDR6 VRAM for Large AI Models: 256-bit, up to 640GB/s bandwidth, run large language and multi-modal AI models without offloading
- Multi-GPU Scaling for Local AI Clusters: PCIe 5.0 and 2-slot design support dense multi-GPU builds for local AI training and inference clusters
- Diecast Shroud and Backplate: Wave-pattern design cuts memory temperature by up to 16%, keeping clocks steady during long AI training runs
- Phase-Change GPU Thermal Pad: Delivers superior thermal conductivity for consistent performance and longevity under heavy AI loads
For a purchasing decision, compare results for the model and precision you plan to run, and account for the full deployment rather than a single headline metric:
- Performance at the relevant precision and workload, using comparable system configurations and batch sizes.
- Memory capacity and bandwidth, plus the interconnect and network topology needed to scale.
- Power, cooling, system availability, and total cost of ownership.
- Software support and the effort required to migrate or maintain your workloads.
What the forecast says about Gaudi 3 sales
The $500 million figure shows what Intel expected from its accelerator business for the second half of 2024; it does not show Gaudi 3 revenue achieved. Intel later said it would miss its $500 million Gaudi target for the full year, and the cited official material does not report a verified realized-sales amount or a Gaudi 3-specific market statistic. For a current evaluation, treat product claims as vendor claims and confirm system or cloud availability directly with the seller or provider.
Quick Recap
Rank #4
- 24GB GDDR7 ECC Memory: handles large AI, 3D and rendering files smoothly
- Powerful CUDA Compute - 8,960 CUDA cores for fast graphics and computing power
- AI & Ray Tracing Boost - Tensor of the 5th generation and RT cores of the 4th generation
- PCIe 5.0 x16 interface - fast data connection with modern systems
- 4 × DisplayPort 2.1 - Multi-monitor support for professional workflows
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
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