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While everyone is crying, Zuck has gone all in on $AMD. Llama runs inferences exclusively on $AMD MI300X. This deal shows $AMD has an edge in inference over $NVDA, which will be a much larger market than training.

Antonio Linares

133,603 subscribers

170,180 просмотров • 1 год назад •via X (Twitter)

Финансы Наука и технологии Новости и политика

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Комментарии: 10

Фото профиля Rob

Rob1 год назад

‘All in’ is extremely misleading. He’s using the chips for part of his business. I’m quite heavily invested too so I want it to perform but this is just not right.

Фото профиля Antonio Linares

Antonio Linares1 год назад

You think that using a chip exclusively for inference across all the apps is a small feat I see...

Фото профиля Welcoming Wealth

Welcoming Wealth1 год назад

The $META and $AMD "partnership" is just another reason to be bullish on the company. Lisa and Zuck are hell of a duo.

Фото профиля STONKS

STONKS1 год назад

Dude, just stop, please stop.

Фото профиля Steff Peeters

Steff Peeters1 год назад

Investing in AI is great, let’s just hope that $META and co finds enough added revenue to pay for these investments.

Фото профиля Antonio Linares

Antonio Linares1 год назад

It's literally skyrocketing the engagement on the apps

Фото профиля Don Merrifield Jr. 🇨🇦🇺🇦

Don Merrifield Jr. 🇨🇦🇺🇦1 год назад

$NVDA $AMD

Фото профиля Royal Tesla

Royal Tesla1 год назад

$NVDA chips are quite expensive. Hyperscalers trying to find a way to reduce costs and have more efficiency. $AMD offers a perfect alternative

Фото профиля DROCK STOCKS

DROCK STOCKS1 год назад

$AMD to $500-1000 by 2030.

Фото профиля JHKim

JHKim1 год назад

Can't NVDA chips be used for inferencing as well? and if inferencing market is going to be larger, I'm sure Jensen already knows that, don't you think? Don't you think NVDA already has something prepared or preparing for inferencing market?

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$AMD is down more than 40% from its ATH. Meanwhile, who’s all in on $AMD? Mark Zuckerberg. Llama 405B runs inferences exclusively on the $AMD MI300X chip.

$AMD is down more than 40% from its ATH. Meanwhile, who’s all in on $AMD? Mark Zuckerberg. Llama 405B runs inferences exclusively on the $AMD MI300X chip.

Antonio Linares

150,656 просмотров • 1 год назад

1/ $AMD is a 10x opportunity everybody ignores. Lisa Su believes that inference will be a bigger market than training. Training is the cost center of AI workload while inference is where you make money. $AMD has an advantage here. Let me explain why: 🧵

1/ $AMD is a 10x opportunity everybody ignores. Lisa Su believes that inference will be a bigger market than training. Training is the cost center of AI workload while inference is where you make money. $AMD has an advantage here. Let me explain why: 🧵

Oguz Erkan

413,014 просмотров • 1 год назад

$NVDA CEO: “Demand for inference will go up by a billion times.” $AMD will be one of the biggest winners as it has the upper hand in inference thanks to larger memory bandwith and capacity of its chips. Stock is still at 22x 2027 earnings. How can’t you be bullish on $AMD?

$NVDA CEO: “Demand for inference will go up by a billion times.” $AMD will be one of the biggest winners as it has the upper hand in inference thanks to larger memory bandwith and capacity of its chips. Stock is still at 22x 2027 earnings. How can’t you be bullish on $AMD?

Oguz Erkan

282,229 просмотров • 4 месяцев назад

$META is betting on $AMD for AI inference. As AI models become more commoditized, total cost of ownership for token generation matters more than ever. $AMD GPUs are far more cost-efficient than $NVDA for inference. With 3.5B daily users ready to use its AI models, $META is going all-in on $AMD

$META is betting on $AMD for AI inference. As AI models become more commoditized, total cost of ownership for token generation matters more than ever. $AMD GPUs are far more cost-efficient than $NVDA for inference. With 3.5B daily users ready to use its AI models, $META is going all-in on $AMD

Daniel

20,558 просмотров • 7 месяцев назад

The $100B deal wirth Zuck shows you one thing: $AMD can personalise compute at scale and a marginal cost. This positions $AMD to become the number 1 AI chip company in the next 5 years, overtaking $NVDA.

The $100B deal wirth Zuck shows you one thing: $AMD can personalise compute at scale and a marginal cost. This positions $AMD to become the number 1 AI chip company in the next 5 years, overtaking $NVDA.

Antonio Linares

34,366 просмотров • 6 месяцев назад

$$AMD has dropped a bomb on the AI arms race. The new MI355X beats $NVDA B200 across the board. It’s expected to undercut Nvidia on price. If $AMD grabs even a fraction of the AI inference market: You’re going to wish you loaded up earlier$

$AMD has dropped a bomb on the AI arms race. The new MI355X beats $NVDA B200 across the board. It’s expected to undercut Nvidia on price. If $AMD grabs even a fraction of the AI inference market: You’re going to wish you loaded up earlier

BeanWealth Research

89,112 просмотров • 1 год назад

The Market is on Verge of once in a Generation type move‼️ Investor will LOSE their MIND! $QQQ $AMD $SNDK $NVDA

The Market is on Verge of once in a Generation type move‼️ Investor will LOSE their MIND! $QQQ $AMD $SNDK $NVDA

Jeremy Lefebvre

33,466 просмотров • 3 месяцев назад

The market no longer sees $AMD as a second option It’s realized $AMD is a big deal in its own way But let me tell you something. Only 5% of the $AMD thesis has become visible What’s coming is way, way bigger

The market no longer sees $AMD as a second option It’s realized $AMD is a big deal in its own way But let me tell you something. Only 5% of the $AMD thesis has become visible What’s coming is way, way bigger

Antonio Linares

132,211 просмотров • 3 месяцев назад

BREAKING $AMD Dr. Lisa Su Fresh Interview 🚀🚀 Note: This was after CES AMD ANALysts concluded OpenAI has no money, but $40B Cash and Raising $100B where they already secured $22B from SoftBank. This morning they also concluded Saudi has $0 money backing and LumaAI for 2GW AMD chips deployment. HUMAIN is extremely well-funded and is a subsidiary of Saudi Arabia's PIF, which manages nearly $1 trillion in assets🤣! So far, ANALysts are concluding whoever buying Chips from AMD are broke. Oh $ORCL too. They also said $META(AMD MI300X largest customer) is broke. They will soon conclude $MSFT and $AMZN are extremely poor too. AMD ANALysts can continue to be SEXIST. Dr. Lisa Su will continue to execute. Fundamental matters more than Opinions. Source: CNBC

BREAKING $AMD Dr. Lisa Su Fresh Interview 🚀🚀 Note: This was after CES AMD ANALysts concluded OpenAI has no money, but $40B Cash and Raising $100B where they already secured $22B from SoftBank. This morning they also concluded Saudi has $0 money backing and LumaAI for 2GW AMD chips deployment. HUMAIN is extremely well-funded and is a subsidiary of Saudi Arabia's PIF, which manages nearly $1 trillion in assets🤣! So far, ANALysts are concluding whoever buying Chips from AMD are broke. Oh $ORCL too. They also said $META(AMD MI300X largest customer) is broke. They will soon conclude $MSFT and $AMZN are extremely poor too. AMD ANALysts can continue to be SEXIST. Dr. Lisa Su will continue to execute. Fundamental matters more than Opinions. Source: CNBC

Mike

35,337 просмотров • 7 месяцев назад

$AMD is providing receipts right now winning inference workloads from one of the best implementers of AI on the planet in $META And don’t @ me about the warrants. No one will care when AMD market cap goes above a trillion. 👏🏻🔥🚀

$AMD is providing receipts right now winning inference workloads from one of the best implementers of AI on the planet in $META And don’t @ me about the warrants. No one will care when AMD market cap goes above a trillion. 👏🏻🔥🚀

Daniel Newman

21,040 просмотров • 6 месяцев назад

$ASTS is on track to become the world's dominant personalised-spectrum provider. This positions $ASTS to be at least as important as chip provides like $NVDA and $AMD in the Physical AI market, which will soon be one of the largest markets on Earth.

$ASTS is on track to become the world's dominant personalised-spectrum provider. This positions $ASTS to be at least as important as chip provides like $NVDA and $AMD in the Physical AI market, which will soon be one of the largest markets on Earth.

Antonio Linares

45,540 просмотров • 8 месяцев назад

$AMD $620/share is too conservative for 2026 🧵 Some quick facts before I dive into this super long thread: $META allocated 42% GPUs to $AMD and 58% to $NVDA OpenAI allocated 6GW(38%) to $AMD and 10GW to $NVDA My $620 PT below by end of 2026 was only for 10-15% market share. I believe $AMD is going to have much much higher market share than I projected. The AI accelerator market is exploding, projected to reach $500 billion by 2028(is now heading $1Tril), driven by insatiable demand for training and inference compute in large language models (LLMs), recommendation systems, and autonomous systems. Nvidia ($NVDA) has long held a stranglehold, commanding over 90% market share through its CUDA ecosystem and superior rack-scale solutions. However, AMD is mounting a formidable challenge, leveraging cost advantages, open-source software momentum, and hyperscaler partnerships to erode Nvidia's moat. Recent deals—such as Meta's ($META) allocation of 42% of its GPU capacity to AMD and OpenAI's commitment to 6GW of AMD compute (versus 10GW for Nvidia)—signal a tipping point. At the forefront is AMD's Instinct MI450 series, a next-generation AI GPU slated for H2 2026 launch, which promises "no-excuses" leadership in training, inference, and distributed workloads. This analysis dissects how AMD will capture more market share and why hyperscalers like $Meta , xAI , Oracle , and others are poised to become voracious buyers of the MI450. AMD's AI GPU revenue has surged from negligible levels in 2022 to an estimated $4-5 billion in 2025, capturing ~6% of the data center GPU market. This growth stems from the Instinct MI300X, which offers 141GB of HBM3 memory and competitive FP8/FP16 performance at 20-30% lower cost than Nvidia's H100. Hyperscalers, facing NVIDIA 's overcharging, have turned to AMD for diversification. Meta, for instance, plans 600,000 H100-equivalent GPUs by end-2024, with ~42% (or 250,000+ units) sourced from AMD's MI300 series for inference tasks like image editing and AI assistants. Similarly, OpenAI's recent multi-year deal commits to 6GW of AMD compute—equivalent to ~300,000-400,000 MI450 GPUs—starting with 1GW in 2026, explicitly to counterbalance its 10GW Nvidia allocation. These aren't one-offs. Microsoft Azure, Amazon AWS, and Oracle Cloud Infrastructure (OCI) have integrated MI300X for AI workloads, with Oracle deploying 30,000 MI355X units in zettascale clusters. xAI, Elon Musk Musk's AI venture, ran 30% of Grok-1's production traffic on MI300X GPUs and has confirmed ongoing purchases. Collectively, these partners represent over $400 billion in projected AI infrastructure spend through 2028, with AMD targeting up to 40% market share. For those that subscribed, I wrote a specific thread on how AMD "secret weapon" is going to change the game in 2026 with an improved designs on all its products, yes AMD has patent on it. Software is the linchpin. AMD's ROCm platform, once derided as "half-baked," now supports day-zero integration for Llama-4, DeepSeek V3, and GPT-OSS models—closing the CUDA gap. Benchmarks show MI355X (MI450 precursor) outperforming Nvidia's B200 in inference by 1.5-2x on memory-bound tasks, at 25-35% lower TCO. For training, MI450's rack-scale IF128 configuration (128 GPUs, 1.4 PB/s intra-rack bandwidth) rivals Nvidia's VR200 NVL144, enabling clusters like xAI's Colossus (scaling to 1M GPUs). My below thread projected Etimated conservative FY 25 revenue: $34-$36B Estimated conservative FY 26 revenue: $55B-$62B Below is why $AMD is revenue is going to be much higher after OpenAI deal. 1. OpenAI 1GW in 2026. With high demand for MI355X at $30,000k+ per unit, with MI450 is likely to be sold in the $45k-$55k. We can safely calcuate 1GW would require roughly 400,000 MI450 GPUs. or Roughly ~$20B revenue in 2026 alone from OpenAI. That would mean $AMD would hit $56B just from one partnership(OpenAI) in 2026 2. $META, the biggest spender on AI Infrastructure right now, Daddy Zuckerberg bought 250,000+ MI300, and is buying MI355X for recommendation engines and Llama training. It is very unlikely for Daddy Zuck to slow down AMD Chips, due to its Inference superiority to NVDA Chips. Most likely we will see at least 300,000-400,000 MI355X ordered from now toward end of H1 2025. And another 300,000-500,000 MI450 by H2 2025. Or ~$20B from just Meta in H2 alone, excluded H1. 3. xAI : Musk confirmed "AMD GPUs work very well" for Grok's small/medium models, with 30% of Grok-1 on MI300X. xAI's Colossus (200K+ GPUs, targeting 1M) and Oracle partnership (via OCI's MI355X cluster) position it for MI450 trials in H1 2026. With $6B funding and Grok integration into Oracle services, xAI could allocate 10-20% ($10B-$15B) to MI450 for distributed inference. We haven't heard the detail from Daddy Elon Musk yet, but most likely not going to be spending less than OpenAI or Sam Altman 4. Oracle ($ORCL): A multi-billion-dollar MI355X deal powers OCI's AI superclusters, with $500B+ remaining performance obligations. Larry Ellison's zettascale ambitions and xAI/OpenAI integrations make Oracle a MI450 anchor tenant—projected 50-100k units ($15B+ spend) for enterprise AI platforms. $ORCL is likely to spend more on the new "secret weapon" due to its capability in AI inference and cost advantage for $500B backlog. 5. Others ( Microsoft , Amazon , Saudi+other countries): Microsoft (Azure MI300X for training) and Amazon ($148B 15-year spend) test MI450 via Stargate ($500B with Oracle/SoftBank). Emerging buyers like G42 (5GW UAE campus), Crusoe, and Hot Aisle add 5-10GW demand. These potentially would add $15B-$30B in 2026 alone. We also need to factor in $TSM supply constraint( $NVDA is TSMC favorite), so $AMD market cap/growth is being tamed by TSMC. So what are you saying Mike, well $AMD 2026 revenue could hit $90-$100B by end of 2026 or nearly 185% growth YoYo. So what does that mean for valuation? I have no idea how Mr. Market gonna value AMD in 2026 with 3 digits growth. My Conservative $620 was my best projection until today with OpenAI partnership. I'm telling you as one of the biggest AMD bull, that I will leave it to "smart money" and other investors to do the price discovery while I'm chilling and writing DDs daily. Lastly, AMD's MI450 isn't hype—it's a calibrated strike at Nvidia's vulnerabilities, amplified by hyperscaler bets like Meta's 42% allocation and OpenAI's 6GW lifeline. By prioritizing inference efficiency, rack-scale innovation, and open ecosystems, AMD will siphon 10-15% share in 2026, scaling to 20%+ as TCO trumps CUDA loyalty. Meta, xAI, Oracle et al. aren't passive; they're active co-designers, betting billions on MI450 to fuel AGI pursuits without Nvidia's premium. For investors, this is AMD's inflection Per Dr. Lisa Su Not Financial Advice!

$AMD $620/share is too conservative for 2026 🧵 Some quick facts before I dive into this super long thread: $META allocated 42% GPUs to $AMD and 58% to $NVDA OpenAI allocated 6GW(38%) to $AMD and 10GW to $NVDA My $620 PT below by end of 2026 was only for 10-15% market share. I believe $AMD is going to have much much higher market share than I projected. The AI accelerator market is exploding, projected to reach $500 billion by 2028(is now heading $1Tril), driven by insatiable demand for training and inference compute in large language models (LLMs), recommendation systems, and autonomous systems. Nvidia ($NVDA) has long held a stranglehold, commanding over 90% market share through its CUDA ecosystem and superior rack-scale solutions. However, AMD is mounting a formidable challenge, leveraging cost advantages, open-source software momentum, and hyperscaler partnerships to erode Nvidia's moat. Recent deals—such as Meta's ($META) allocation of 42% of its GPU capacity to AMD and OpenAI's commitment to 6GW of AMD compute (versus 10GW for Nvidia)—signal a tipping point. At the forefront is AMD's Instinct MI450 series, a next-generation AI GPU slated for H2 2026 launch, which promises "no-excuses" leadership in training, inference, and distributed workloads. This analysis dissects how AMD will capture more market share and why hyperscalers like $Meta , xAI , Oracle , and others are poised to become voracious buyers of the MI450. AMD's AI GPU revenue has surged from negligible levels in 2022 to an estimated $4-5 billion in 2025, capturing ~6% of the data center GPU market. This growth stems from the Instinct MI300X, which offers 141GB of HBM3 memory and competitive FP8/FP16 performance at 20-30% lower cost than Nvidia's H100. Hyperscalers, facing NVIDIA 's overcharging, have turned to AMD for diversification. Meta, for instance, plans 600,000 H100-equivalent GPUs by end-2024, with ~42% (or 250,000+ units) sourced from AMD's MI300 series for inference tasks like image editing and AI assistants. Similarly, OpenAI's recent multi-year deal commits to 6GW of AMD compute—equivalent to ~300,000-400,000 MI450 GPUs—starting with 1GW in 2026, explicitly to counterbalance its 10GW Nvidia allocation. These aren't one-offs. Microsoft Azure, Amazon AWS, and Oracle Cloud Infrastructure (OCI) have integrated MI300X for AI workloads, with Oracle deploying 30,000 MI355X units in zettascale clusters. xAI, Elon Musk Musk's AI venture, ran 30% of Grok-1's production traffic on MI300X GPUs and has confirmed ongoing purchases. Collectively, these partners represent over $400 billion in projected AI infrastructure spend through 2028, with AMD targeting up to 40% market share. For those that subscribed, I wrote a specific thread on how AMD "secret weapon" is going to change the game in 2026 with an improved designs on all its products, yes AMD has patent on it. Software is the linchpin. AMD's ROCm platform, once derided as "half-baked," now supports day-zero integration for Llama-4, DeepSeek V3, and GPT-OSS models—closing the CUDA gap. Benchmarks show MI355X (MI450 precursor) outperforming Nvidia's B200 in inference by 1.5-2x on memory-bound tasks, at 25-35% lower TCO. For training, MI450's rack-scale IF128 configuration (128 GPUs, 1.4 PB/s intra-rack bandwidth) rivals Nvidia's VR200 NVL144, enabling clusters like xAI's Colossus (scaling to 1M GPUs). My below thread projected Etimated conservative FY 25 revenue: $34-$36B Estimated conservative FY 26 revenue: $55B-$62B Below is why $AMD is revenue is going to be much higher after OpenAI deal. 1. OpenAI 1GW in 2026. With high demand for MI355X at $30,000k+ per unit, with MI450 is likely to be sold in the $45k-$55k. We can safely calcuate 1GW would require roughly 400,000 MI450 GPUs. or Roughly ~$20B revenue in 2026 alone from OpenAI. That would mean $AMD would hit $56B just from one partnership(OpenAI) in 2026 2. $META, the biggest spender on AI Infrastructure right now, Daddy Zuckerberg bought 250,000+ MI300, and is buying MI355X for recommendation engines and Llama training. It is very unlikely for Daddy Zuck to slow down AMD Chips, due to its Inference superiority to NVDA Chips. Most likely we will see at least 300,000-400,000 MI355X ordered from now toward end of H1 2025. And another 300,000-500,000 MI450 by H2 2025. Or ~$20B from just Meta in H2 alone, excluded H1. 3. xAI : Musk confirmed "AMD GPUs work very well" for Grok's small/medium models, with 30% of Grok-1 on MI300X. xAI's Colossus (200K+ GPUs, targeting 1M) and Oracle partnership (via OCI's MI355X cluster) position it for MI450 trials in H1 2026. With $6B funding and Grok integration into Oracle services, xAI could allocate 10-20% ($10B-$15B) to MI450 for distributed inference. We haven't heard the detail from Daddy Elon Musk yet, but most likely not going to be spending less than OpenAI or Sam Altman 4. Oracle ($ORCL): A multi-billion-dollar MI355X deal powers OCI's AI superclusters, with $500B+ remaining performance obligations. Larry Ellison's zettascale ambitions and xAI/OpenAI integrations make Oracle a MI450 anchor tenant—projected 50-100k units ($15B+ spend) for enterprise AI platforms. $ORCL is likely to spend more on the new "secret weapon" due to its capability in AI inference and cost advantage for $500B backlog. 5. Others ( Microsoft , Amazon , Saudi+other countries): Microsoft (Azure MI300X for training) and Amazon ($148B 15-year spend) test MI450 via Stargate ($500B with Oracle/SoftBank). Emerging buyers like G42 (5GW UAE campus), Crusoe, and Hot Aisle add 5-10GW demand. These potentially would add $15B-$30B in 2026 alone. We also need to factor in $TSM supply constraint( $NVDA is TSMC favorite), so $AMD market cap/growth is being tamed by TSMC. So what are you saying Mike, well $AMD 2026 revenue could hit $90-$100B by end of 2026 or nearly 185% growth YoYo. So what does that mean for valuation? I have no idea how Mr. Market gonna value AMD in 2026 with 3 digits growth. My Conservative $620 was my best projection until today with OpenAI partnership. I'm telling you as one of the biggest AMD bull, that I will leave it to "smart money" and other investors to do the price discovery while I'm chilling and writing DDs daily. Lastly, AMD's MI450 isn't hype—it's a calibrated strike at Nvidia's vulnerabilities, amplified by hyperscaler bets like Meta's 42% allocation and OpenAI's 6GW lifeline. By prioritizing inference efficiency, rack-scale innovation, and open ecosystems, AMD will siphon 10-15% share in 2026, scaling to 20%+ as TCO trumps CUDA loyalty. Meta, xAI, Oracle et al. aren't passive; they're active co-designers, betting billions on MI450 to fuel AGI pursuits without Nvidia's premium. For investors, this is AMD's inflection Per Dr. Lisa Su Not Financial Advice!

Mike

711,006 просмотров • 10 месяцев назад

The $NVDA CEO, Jensen Huang is literally telling you to buy semiconductors. Recently in an interview he’s said, “The semiconductor industry is going to be 10X larger than it is today.” Jensen is absolutely right as sales will exceed $1.6T in 2026 versus just $790M in 2025. Names like $NVDA, $AMD, $AVGO, $TSM, & $MU should be names your buying on pullbacks. Arguably the easiest dip-buy in history…

The $NVDA CEO, Jensen Huang is literally telling you to buy semiconductors. Recently in an interview he’s said, “The semiconductor industry is going to be 10X larger than it is today.” Jensen is absolutely right as sales will exceed $1.6T in 2026 versus just $790M in 2025. Names like $NVDA, $AMD, $AVGO, $TSM, & $MU should be names your buying on pullbacks. Arguably the easiest dip-buy in history…

Mike Investing

94,321 просмотров • 1 месяц назад

RealityScan 2.2 and that means full AMD GPU support has landed! Mix AMD and NVIDIA in the same machine and RealityScan will use both at once. More details on that and the latest bug fixes can be found here:

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Unreal Engine

21,782 просмотров • 2 месяцев назад

At Advancing AI 2026, AMD went after the humanoid "robot brain," directly challenging NVIDIA's Jetson Thor at the edge. Its new Kria AI Robotics Developer Platform is an open, turnkey system putting CPU, GPU, NPU and FPGA on one board. The X100 chip is the robot's "brain," while dedicated FPGAs control the joints, motion, and sensors in real time, something AMD has long done well. AMD claims the Kria/X100 robot module beats NVIDIA's Jetson Thor T5000 by up to 3.4× on real-time reaction, 2.3× on concurrent agents, and 1.6× on CPU (AMD's own numbers). Here's Lisa Su meeting Generative Bionics' humanoid. AMD is both an investor in and tech partner to the Italian startup.

At Advancing AI 2026, AMD went after the humanoid "robot brain," directly challenging NVIDIA's Jetson Thor at the edge. Its new Kria AI Robotics Developer Platform is an open, turnkey system putting CPU, GPU, NPU and FPGA on one board. The X100 chip is the robot's "brain," while dedicated FPGAs control the joints, motion, and sensors in real time, something AMD has long done well. AMD claims the Kria/X100 robot module beats NVIDIA's Jetson Thor T5000 by up to 3.4× on real-time reaction, 2.3× on concurrent agents, and 1.6× on CPU (AMD's own numbers). Here's Lisa Su meeting Generative Bionics' humanoid. AMD is both an investor in and tech partner to the Italian startup.

The Humanoid Hub

37,885 просмотров • 27 дней назад

THIS IS UGLY👇 $NVDA is in a Range, $AMD is trying to COLLAPSE OUT ITS RANGE The level breaks and SELLERS STEP IN, we are looking for $20-30 on downside.

THIS IS UGLY👇 $NVDA is in a Range, $AMD is trying to COLLAPSE OUT ITS RANGE The level breaks and SELLERS STEP IN, we are looking for $20-30 on downside.

JEFE TRADES 🔪

27,113 просмотров • 6 месяцев назад

$AMD $NVDA & the AMD Bear SemiAnalysis 🧵 Here are some facts: $META allocated 42% AI GPUs to $AMD OpenAI allocated 6GW(38%) to $AMD 1. Model-Specific Bias: Llama 3.3 70B graph favored NVIDIA due to TRT-LLM optimizations, highlighting throughput and latency where Blackwell excels. In contrast, the GPT-OSS 120B chart shifts focus to cost and interactivity, where MI355X shines. This selective model choice clearly suggests SemiAnalysis tailors benchmarks to reinforce narratives—NVIDIA’s dominance in speed (Llama 3.3) and AMD’s niche in cost (GPT-OSS). GPT-OSS 120B, with its sparse attention mechanisms (similar to DeepSeek-V3.2-Exp), shows AMD’s CDNA 4 architecture, while Llama 3.3’s dense attention favors NVIDIA’s Tensor Cores. SemiAnalysis’ decision to emphasize Llama 3.3 initially could reflect its AMD bear stance. 2. The way Data is presented The Llama 3.3 graph focused on raw performance metrics (throughput vs. latency), downplaying cost, where AMD holds an edge. This new chart, buried in follow-up posts, reveals AMD’s strength but receives less prominence, suggesting a curated narrative. Labeling variability (e.g., B200 with/without TRT) and the lack of uniform scaling across graphs indicate potential cherry-picking of configurations to favor NVIDIA’s optimized setups. 3. Historical Context: SemiAnalysis’ past critiques of AMD’s R&D and ROCm (web results from May 2025) align with a bearish outlook. Their own hype/brand around NVIDIA’s 15x ROI contrasts with muted coverage of AMD’s cost advantages, reinforcing bias. Despite AMD’s participation in InferenceMAX, the benchmark’s framing (e.g., prioritizing Blackwell’s ROI) reflect SemiAnalysis’ market predictions rather than balanced analysis. Lastly, AMD’s Instinct MI355X proves superior in inference and cost per million tokens for the GPT-OSS 120B model, offering a 25% cost advantage over NVIDIA’s H200 at moderate-to-high interactivity levels. This efficiency, driven by AMD’s memory bandwidth and FP4 support, makes it a better choice for cost-sensitive, multi-user deployments over a three-year horizon. However, SemiAnalysis’ sole focus(presentation graph) on Llama 3.3—where NVIDIA excels demonstrates a pattern of cherry-picking models and data to favor NVIDIA , consistent with its historical AMD bearish stance. This selective presentation risks misleading stakeholders by overshadowing AMD economic strengths. My personal take: I would trust Dr. Lisa Su, and Greg Brockman Sam Altman take on AMD and how they viewed and allocated 6GW for AMD over SemiAnalysis . At the end of the day, Large customers pay when it works. $Meta allocated 42% AI GPUs to $AMD for a reason. And the "secret weapon" will improve energy consumption by 20-50%, meaning at 6GW, OpenAI would be able to deploy 25-50% more MI450 at a much better cost advantage, higher memory bandwidth, and the queen of Inference! Oh and ROCm 8 is expected to be on par with CUDA in 2026.

Mike

104,194 просмотров • 10 месяцев назад

$NVDA says it has shipped its first Vera Rubin samples to customers and remains on track for production shipments in 2H. $AMD Helios vs. Vera Rubin is shaping up to be the compute Super Bowl of 2026.

$NVDA says it has shipped its first Vera Rubin samples to customers and remains on track for production shipments in 2H. $AMD Helios vs. Vera Rubin is shaping up to be the compute Super Bowl of 2026.

Shay Boloor

66,499 просмотров • 6 месяцев назад

$AMD CEO Lisa Su said Helios has industry-leading specs and is on track to launch this year. Built with $META, Helios targets large-scale AI training & inference aiming for up to 10x performance where performance per dollar matters.

$AMD CEO Lisa Su said Helios has industry-leading specs and is on track to launch this year. Built with $META, Helios targets large-scale AI training & inference aiming for up to 10x performance where performance per dollar matters.

Shay Boloor

118,072 просмотров • 7 месяцев назад