Free tools Windows power users keep installed
One-click scans. No signup required.
Short answer: AMD did not overtake Nvidia in June 2024, but its annual Instinct roadmap made Intel’s AI-accelerator catch-up problem materially harder. Nvidia was already selling a fast, integrated platform cycle; AMD had a credible MI300X alternative and announced MI325X and MI350 on a yearly cadence. Intel’s Gaudi 3 therefore arrived between generations, asking customers to evaluate not only performance, but software, supply, systems, networking and total cost.
This is a historical analysis of the June 2024 inflection point. Later availability, market share and product results are outside its scope.
Nvidia’s “victory lap” was about a platform, not one GPU
Blackwell had already been announced at GTC on March 18, 2024. At Computex, Nvidia broadened the message into a complete data-center operating model: Blackwell GPUs paired with Grace CPUs, NVLink and networking, server systems, cloud instances, inference services, software and a long list of OEM and cloud partners. Nvidia’s announcement is documented at Nvidia’s Blackwell release and its investor-relations version at NVIDIA Investor Relations.
The strategic signal was continuity. The roadmap discussed in CRN’s June 17, 2024 analysis pointed to successor architectures in 2025, 2026 and 2027, formalizing an annual rhythm. Customers could plan around a recurring Nvidia platform refresh rather than a standalone accelerator purchase. That cadence, combined with CUDA, TensorRT-LLM, NVLink, networking, OEM qualification and cloud access, created switching costs even when another chip looked attractive on a specification sheet.
#1 Best Overall
- AI Performance: 767 AI TOPS
- OC mode: 2632 MHz (OC mode)/ 2602 MHz (Default mode)
- Powered by the NVIDIA Blackwell architecture and DLSS 4
- Axial-tech fan design features a smaller fan hub that facilitates longer blades and a barrier ring that increases downward air pressure
- A 2.5-slot design maximizes compatibility and cooling efficiency for superior performance in small chassis
“Dominance” needs precision here: Nvidia’s advantage meant installed base, software ecosystem, partner coverage and commercial scale—not an assertion that every workload was fastest or cheapest.
AMD turns a two-player problem into a three-way pressure problem
AMD’s MI300X was already shipping and had become a credible alternative to Nvidia’s H100 and H200 in selected deployments. On June 2, 2024, AMD announced an annual Instinct cadence: MI325X planned for the fourth quarter of 2024, followed by the MI350 series in 2025 using CDNA 4. The announcement is available from AMD and AMD Investor Relations.
AMD said MI325X would provide up to 288 GB of HBM3E and 6 TB/s of memory bandwidth. It also said the accelerator could reuse the MI300-series Universal Baseboard, potentially reducing server redesign and qualification work. That matters to OEMs, cloud providers and channel partners already supporting MI300 systems.
AMD executive Forrest Norrod told CRN that Nvidia accelerated its roadmap after recognizing MI300X as a serious competitor; that is an executive explanation, not an independently verified causal finding. The interview is at CRN.
Crashes, No Sound, or Screen Glitches?
Random freezes, missing sound and display glitches usually trace back to one bad driver. Find and replace yours safely.Free scan · under a minutePC Slower Than It Used to Be?
A free scan shows the junk files, broken settings and background clutter dragging Windows down - then fixes them in one click.Free scan · Windows 10 & 11Rank #2
- Powered by the NVIDIA Blackwell architecture and DLSS 4
- Powered by GeForce RTX 5060
- Integrated with 8GB GDDR7 128bit memory interface
- PCIe 5.0
- WINDFORCE cooling system
Product positions as of June 2024
The following status labels reflect what was shipping, announced or planned at that time. Memory figures are representative configurations or vendor-announced specifications, not a normalized benchmark.
| Product | Company | June 2024 status | Memory signal | Strategic role |
|---|---|---|---|---|
| H100 | Nvidia | Established Hopper accelerator | 80 GB HBM3 in a common SXM configuration; exact SKU matters | Installed base and benchmark reference |
| H200 | Nvidia | Newer Hopper product | 141 GB HBM3e in Nvidia’s announced specification; configuration matters | Bridge before Blackwell |
| Blackwell B100/B200/GB200 | Nvidia | Announced; availability expected later in 2024 | Varies by platform configuration | Maintains Nvidia’s platform and ecosystem lead |
| MI300X | AMD | Shipping and adopted by major partners | 192 GB HBM3 per accelerator in the 2024 comparison | First serious hyperscale challenger |
| MI325X | AMD | Planned for Q4 2024 | Up to 288 GB HBM3E and 6 TB/s, according to AMD’s June announcement | Annual refresh and large-memory strategy |
| Gaudi 3 | Intel | Planned 2024 launch | 128 GB HBM2e in Intel product material; platform specification should be confirmed | Lower-cost, Ethernet-oriented alternative |
| Falcon Shores | Intel | Expected in late 2025 in the period’s analysis | Not final at the time | Attempt to unify Xe and Gaudi roadmaps |
AMD’s June figure for MI325X is the relevant historical announcement. Later product pages may describe different configurations; those figures should not be mixed into this dated comparison.
Why HBM capacity became a strategic weapon
Large language models, long-context inference and larger batches can be limited by accelerator memory. More HBM may let weights, activations or a larger batch fit on fewer accelerators, reducing system count, networking complexity, power and operational overhead. That is why AMD emphasized MI325X’s memory capacity.
Capacity alone does not prove superiority. Results also depend on bandwidth, interconnects, kernels, framework support, quantization, utilization and workload. “MI325X is faster” is therefore not a general conclusion from the announced memory figures.
Quick wins for a faster PC:
Fix the driver behind crashes, sound loss and screen glitchesFind Drivers →Clear out junk files and repair common Windows errorsFree Scan →Rank #3
- Powered by the NVIDIA Blackwell architecture and DLSS 4. System Requirements: Minimum 850W PSU with 16-pin 12V-2x6 (12VHPWR) connector required. Verify before purchasing.
- Military-grade components deliver rock-solid power and longer lifespan for ultimate durability. Compatibility: 348mm (13.7") length, 3.6 slots, 4.3 lbs. Confirm case clearance and slot spacing. GPU bracket included.
- Protective PCB coating helps protect against short circuits caused by moisture, dust, or debris
- 3.6-slot design with massive fin array optimized for airflow from three Axial-tech fans
- Phase-change GPU thermal pad helps ensure optimal thermal performance and longevity, outlasting traditional thermal paste for graphics cards under heavy loads
Why Intel was more exposed than AMD
Intel faced four simultaneous gaps:
- Technical: Gaudi 3 had to catch current Nvidia products while Blackwell was moving the comparison forward.
- Timing: Intel’s next major successor, Falcon Shores, was not expected until late 2025 in the period’s reporting.
- Platform: Intel needed software, OEM, cloud, networking and support maturity, not merely a competitive die.
- Business: It had to scale Gaudi revenue while funding a broader manufacturing and corporate turnaround.
CRN reported Gaudi 3 air-cooled systems for the third quarter of 2024 and liquid-cooled versions for the fourth quarter. It also reported server support from Dell, HPE, Lenovo, Supermicro, Asus, Gigabyte and others. Those relationships improved reach, but announced support is not the same as volume availability or proven utilization.
Intel’s price-and-openness counterattack
Intel listed an eight-accelerator Gaudi 3 Universal Baseboard package at $125,000 and estimated that it was about two-thirds the cost of a comparable H100 platform. Those are Intel’s historical price and comparison claims, reported in its Computex announcement, not a neutral market quote.
A serious buyer would ask whether the figure covered only accelerators and the board or a deployable server, and whether the Nvidia comparison included host CPUs, memory, storage, networking, cooling, software and support. List-price savings can disappear through porting, tuning, underutilization and scarce engineering expertise.
Intel also promoted Ethernet-based scaling, open infrastructure, performance per watt and total cost of ownership. Ethernet and Ultra Ethernet can improve supplier choice and fit enterprise networks, but “open” does not automatically mean easier or cheaper: customers still need mature drivers, optimized libraries, monitoring, validated reference architectures and support contracts.
Rank #4
- Powered by the NVIDIA Blackwell architecture and DLSS 4
- Powered by GeForce RTX 5070 Ti
- Integrated with 16GB GDDR7 256bit memory interface
- PCIe 5.0
- WINDFORCE cooling system
The software and ecosystem contest
Nvidia
CUDA, TensorRT-LLM, NVLink, integrated networking, broad OEM coverage and cloud availability made Nvidia a complete platform. Its Blackwell partner list included AWS, Google Cloud, Microsoft Azure, Oracle Cloud Infrastructure and major server manufacturers.
AMD
AMD’s opportunity was hardware plus ROCm and a growing deployment base through Microsoft Azure, Meta, Dell, HPE, Lenovo and other partners. AMD’s MI300 information is at the MI300 product page. ROCm resources are at AMD ROCm, with model resources through AMD Infinity Hub.
Intel
Intel’s Gaudi opportunity was Ethernet scaling and enterprise relationships involving VMware, Red Hat, SAP and server vendors. Gaudi details are at Intel’s product page, with developer resources at Intel Habana Developer Site. The practical question was whether software support and model portability could reach the breadth customers already associated with CUDA.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Commercial scale showed the distance, but not market share
| Company and figure | Period and definition | What it indicates |
|---|---|---|
| Intel: more than $500 million | 2024 Gaudi revenue expectation | Early monetization target |
| AMD: $4 billion | 2024 data-center GPU revenue forecast | Much larger expected accelerator business |
| Nvidia: $19.4 billion | Fiscal first-quarter data-center compute revenue | Quarterly scale, including more than discrete AI GPUs |
These are not comparable accounting categories or periods, so they cannot produce a clean market-share ranking. They do show the commercial distance Intel had to close.
The Tool Desk
Outbyte PC Repair FREEClear out junk files and repair common Windows errorsFree Scan →Outbyte Driver Updater FREEFix the driver behind crashes, sound loss and screen glitchesFind Drivers →Best Value
- AI Performance: 1005 AI TOPS
- OC mode boosts clock 2587 MHz (OC mode) / 2557 MHz (Default mode)
- Powered by the NVIDIA Blackwell architecture and DLSS 4
- SFF-Ready enthusiast GeForce card compatible with small-form-factor builds
- Axial-tech fans feature a smaller fan hub that facilitates longer blades and a barrier ring that increases downward air pressure
Who was most threatened?
Intel: greatest immediate exposure
Intel was chasing both product performance and ecosystem maturity while Nvidia moved to Blackwell and AMD shortened its cadence. Its price, Ethernet and openness arguments could win specific deployments, but they did not erase timing or software risk.
AMD: credible challenger, unfinished conversion
AMD had a stronger hardware and memory story than Intel and a more credible installed base. It still had to turn ROCm adoption, supply and partner deployments into sustained customer preference rather than isolated wins.
Nvidia: dominant, but under execution pressure
Nvidia retained the broadest platform, yet an annual cycle raises its own obligations: supply, validation, power and cooling, software releases and customer willingness to refresh infrastructure repeatedly. AMD’s roadmap gave buyers a reason to negotiate and diversify.
How buyers should evaluate the three platforms
Hyperscalers
- Measure cost per token or inference request, not accelerator price alone.
- Model HBM capacity, bandwidth, interconnect scaling, rack power and cooling.
- Verify delivery volume and whether existing servers can be reused.
- Price software migration, engineering time, support and vendor-concentration risk.
Enterprises
- Confirm that the required model and libraries are optimized for the platform.
- Compare cloud instances with on-premises OEM systems, warranty and support.
- Account for CUDA, ROCm or Gaudi expertise and data-sovereignty requirements.
- Estimate utilization and the workload’s expected life before buying a rapidly refreshed platform.
Server vendors and channel partners
- Check reference-platform maturity, qualification effort and supply consistency.
- Design for power, cooling, inventory risk and software-service attach.
- Use AMD’s baseboard reuse where it genuinely reduces validation work; use Gaudi’s economics where customers value Ethernet and differentiation.
- Recognize Nvidia’s stronger customer pull and complete-platform coverage.
The practical conclusion
In the June 2024 market, AMD “doubled the trouble” for Intel by becoming a credible second source while Nvidia accelerated its own platform cycle. Intel’s challenge was therefore not simply that Gaudi 3 might trail a benchmark. It had to launch on time, secure supply, deliver a usable software stack, qualify systems and prove that lower acquisition cost survived deployment.
Do these 3 things before closing this tab:
1Fix the driver behind crashes, sound loss and screen glitches2Clear out junk files and repair common Windows errors3Scan for outdated or missing drivers - takes under a minuteFor uncertain or bursty workloads, renting cloud capacity can avoid hardware depreciation. Nvidia was the lower-risk choice when CUDA compatibility and deployment speed dominated. AMD warranted evaluation when memory capacity, price-performance and supplier diversification justified ROCm validation. Intel Gaudi warranted evaluation when Ethernet scaling and platform economics outweighed ecosystem breadth. In every case, compare the complete deployed cost: accelerators, servers, networking, power, cooling, support, software engineering and utilization.
Quick Recap
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.
