Market Cap 254.27M
Revenue (ttm) 20.52M
Net Income (ttm) -10.64M
EPS (ttm) N/A
PE Ratio 0.00
Forward PE N/A
Profit Margin -51.85%
Debt to Equity Ratio 0.00
Volume 1,310,609
Avg Vol 1,700,044
Day's Range N/A - N/A
Shares Out 35.24M
Stochastic %K 12%
Beta 1.46
Analysts Strong Buy
Price Target $8.00

Company Profile

GSI Technology, Inc. designs, develops, and markets semiconductor memory solutions for networking, industrial, test equipment, medical, aerospace, and military customers in the United States, China, Singapore, Germany, the Netherlands, and internationally. It offers associative processing unit products, which focuses on applications using similarity search in visual search queries for e-commerce, computer vision, drug discovery, cyber security, and service markets. The company also provides stat...

Industry: Semiconductors
Sector: Technology
Phone: 408 331 8800
Fax: 408 331 9795
Address:
1213 Elko Drive, Sunnyvale, United States
Seenalot
Seenalot Feb. 3 at 8:24 PM
$GSIT This is the reason the stock has continued to slide lower. Almost everybody (apparently not everybody) has realized the headline publication was just hype. The term Vaporware seems appropriate.
0 · Reply
OleStockHound
OleStockHound Feb. 3 at 8:23 PM
$GSIT Interesting read. Open AI looking for faster inference chips. It mentioned S-Ram, something GSIT does as well. $NVDA AI dominance might be feeling the pressure soon: Competing products such as Anthropic’s Claude and Google’s Gemini benefit from deployments that rely more heavily on the chips Google made in-house, called tensor processing units, or TPUs, which are designed for the sort of calculations required for inference and can offer performance advantages over general-purpose AI chips like the Nvidia-designed GPUs. https://www.msn.com/en-us/money/other/openai-ditches-nvidia-for-faster-ai-inference-chips-threatening-chipmaker-s-dominance/ar-AA1VxVDP?ocid=msedgdhp&pc=HCTS&cvid=698255e0d75841f79f7f190ebe8ae65d&ei=85
0 · Reply
Seenalot
Seenalot Feb. 3 at 8:09 PM
$GSIT "just beat nvda and qcom..." Nope. They didn't. They DO NOT have a chip that does what the APU connected with the external DRAMs (used for the test) does. The study merely showed that IF they could somehow change their chip to include WAY more data on it AND somehow eliminate the bottlenecks that are currently in it, THEN they show the stated results.
0 · Reply
Stockfreshman
Stockfreshman Feb. 3 at 7:49 PM
$GSIT It is one month old baby now. It will grow to very big guy.
0 · Reply
dipbuyerripseller
dipbuyerripseller Feb. 3 at 4:43 PM
$GSIT buyout price billion or more so 20+? So let’s work backwards. The company has amazing hardware that just beat NVDA and QCOM in publicly announced tests. Drone market is massive with contracts flying off the shelf. What’s this leave? Software is key. Government funding is specifically earmarked for software development. Building the software stack for sentinel award now. When it’s done, good luck! Shorts are dead imho
1 · Reply
DrocDolf
DrocDolf Feb. 3 at 4:00 PM
$GSIT 2/2 -GSI is almost certainly hiding that their chip did not run Gemma-3 at all, only the pre-generation RAG phase. APU lack the MAC units required for matrix multiplication, which is critical for AI workloads. -In the October 20 PR reporting on Cornell's paper, GSI never disclosed this critical and materially important fact (on the contrary, they portrayed the findings as actual results of their current chip, deceiving most investors in the process): Cornell SIMULATED HBM2E EXTERNAL MEMORY INTERFACE, the most important part of an AI system, and both performance and energy consumption were based on that simulation. In other words, Cornell studied a fictitious chip that GSI DOES NOT HAVE. -GSI has exposed itself to securities fraud lawsuits, by lying about easily verifiable, material facts. Investors who bought at $18 and lost money would likely win. The company is flush with investor cash obtained through deception & immediate dilution, so full compensation is entirely feasible
0 · Reply
DrocDolf
DrocDolf Feb. 3 at 3:51 PM
$GSIT 1/2 GSIT's investors can now be SURE that GSIT cannot compete in the Edge AI sector. This is why they blatantly lie and hide data. Summary of findings: -The exact same model GSI talks about in its fraudulent January 29 PR, Gemma-3 12B, has been benchmarked on Jetson Thor. -Jetson Thor is actually 58 TIMES FASTER than GSIT's APU. -GSI lied to investors claiming that Jetson Thor needs 3 seconds for TTFT. For the exact same model, Gemma-3 12B, Jetson Thor has a TTFT latency of 52 milliseconds, 58 times faster than 3 seconds. -GSIT's APU is completely outside the range considered acceptable for real-time detection, at most 200 milliseconds. A detection every 3 seconds is laughable and completely useless, especially for military drones. -Even on a much larger model than Gemma-3 12B, concretely on Qwen-3 32B, and with a much larger input size, 2040 tokens vs 256 tokens, TTFT on Jetson Thor is 385 milliseconds.
1 · Reply
OleStockHound
OleStockHound Feb. 3 at 1:31 AM
$GSIT I think if this is to happen these 3 stocks will be needed: 1. $GSIT : Edge computing, especially the CIM architecture for optimal use and conservation of energy. Initial stages you will be dealing with a finite amount of energy available for robots and machinery and need split second decisions without data centers. The signal would take forever to get from Earth to Mars. 2. $ASTI lightweight and saves space and cost per launch. Elon is big on solar and this thin film technology can be damaged and still work. A vital source of energy when starting a colony on an alien world. Beaming technology might be in play as well. 3. $KULR Power source for high wattage batteries and already operating on Mars. Their batteries have achieved the highest certification for safety and quality. Their TPS prevents lithium runaway because of a bad cell. They specialize in thermal management and vibration reduction. Both are a plus on an alien world. https://youtu.be/az5nQLRNzhM?si=AFapCVj39WGNJe2Y
0 · Reply
OleStockHound
OleStockHound Feb. 2 at 5:06 PM
$GSIT Edge AI anyone? https://defence-industry.eu/lockheed-martin-tests-sniper-networking-targeting-pod-in-first-multi-aircraft-f-16-flight-demonstration/
1 · Reply
Seenalot
Seenalot Feb. 2 at 4:04 PM
$GSIT @DrocDolf @Peaceouty Part 2 AI Response 2. What is a "Benchmark"? A Benchmark is a standardized test used to measure performance (like a 40-yard dash for athletes). For these chips, the benchmark usually measures speed (how many words/tokens it can generate per second) or latency (how long it takes to start responding). Core Argument The Stocktwits user claims that GSI Technology (GSIT) is misleading or that the comparison is unfair because: NVIDIA's website shows how fast its Thor chip runs a small 3B model. GSI claims its Gemini-II chip performed well, but it was tested using a much larger 12B model. Why the comparison is invalid: If Chip A runs a 5lb weight (3B model) and Chip B runs a 20lb weight (12B model), their finish times are not comparable. The heavier 12B model naturally slows down any chip. Comparing it to a speed score from a lighter 3B model is not mathematically valid.
0 · Reply
Latest News on GSIT
GSI Technology, Inc. (GSIT) Q3 2026 Earnings Call Transcript

Jan 29, 2026, 8:22 PM EST - 4 days ago

GSI Technology, Inc. (GSIT) Q3 2026 Earnings Call Transcript


GSI Technology: A Speculative Buy Scaling To Profitability

Jan 13, 2026, 2:39 PM EST - 21 days ago

GSI Technology: A Speculative Buy Scaling To Profitability


GSI Technology, Inc. (GSIT) Q2 2026 Earnings Call Transcript

Oct 30, 2025, 7:26 PM EDT - 3 months ago

GSI Technology, Inc. (GSIT) Q2 2026 Earnings Call Transcript


Equity Raise Sets Clear Price Tag On GSI Technology Stock

Oct 22, 2025, 1:37 PM EDT - 3 months ago

Equity Raise Sets Clear Price Tag On GSI Technology Stock


GSI Technology, Inc. (GSIT) Q1 2026 Earnings Call Transcript

Aug 1, 2025, 11:35 AM EDT - 6 months ago

GSI Technology, Inc. (GSIT) Q1 2026 Earnings Call Transcript


GSI Technology, Inc. Announces First Quarter Fiscal 2026 Results

Jul 31, 2025, 4:05 PM EDT - 6 months ago

GSI Technology, Inc. Announces First Quarter Fiscal 2026 Results


GSI Technology, Inc. (GSIT) Q4 2025 Earnings Call Transcript

May 1, 2025, 8:29 PM EDT - 9 months ago

GSI Technology, Inc. (GSIT) Q4 2025 Earnings Call Transcript


GSI Technology, Inc. (GSIT) Q3 2025 Earnings Call Transcript

Jan 30, 2025, 8:16 PM EST - 1 year ago

GSI Technology, Inc. (GSIT) Q3 2025 Earnings Call Transcript


GSI Technology, Inc. (GSIT) Q2 2025 Earnings Call Transcript

Oct 24, 2024, 9:57 PM EDT - 1 year ago

GSI Technology, Inc. (GSIT) Q2 2025 Earnings Call Transcript


GSI Technology, Inc. (GSIT) Q1 2025 Earnings Call Transcript

Jul 25, 2024, 8:58 PM EDT - 1 year ago

GSI Technology, Inc. (GSIT) Q1 2025 Earnings Call Transcript


GSI Technology, Inc. (GSIT) Q4 2024 Earnings Call Transcript

May 3, 2024, 11:24 AM EDT - 1 year ago

GSI Technology, Inc. (GSIT) Q4 2024 Earnings Call Transcript


GSI Technology, Inc. (GSIT) Q3 2024 Earnings Call Transcript

Jan 25, 2024, 6:41 PM EST - 2 years ago

GSI Technology, Inc. (GSIT) Q3 2024 Earnings Call Transcript


GSI Technology, Inc. Reports Third Quarter Fiscal 2024 Results

Jan 25, 2024, 4:05 PM EST - 2 years ago

GSI Technology, Inc. Reports Third Quarter Fiscal 2024 Results


Seenalot
Seenalot Feb. 3 at 8:24 PM
$GSIT This is the reason the stock has continued to slide lower. Almost everybody (apparently not everybody) has realized the headline publication was just hype. The term Vaporware seems appropriate.
0 · Reply
OleStockHound
OleStockHound Feb. 3 at 8:23 PM
$GSIT Interesting read. Open AI looking for faster inference chips. It mentioned S-Ram, something GSIT does as well. $NVDA AI dominance might be feeling the pressure soon: Competing products such as Anthropic’s Claude and Google’s Gemini benefit from deployments that rely more heavily on the chips Google made in-house, called tensor processing units, or TPUs, which are designed for the sort of calculations required for inference and can offer performance advantages over general-purpose AI chips like the Nvidia-designed GPUs. https://www.msn.com/en-us/money/other/openai-ditches-nvidia-for-faster-ai-inference-chips-threatening-chipmaker-s-dominance/ar-AA1VxVDP?ocid=msedgdhp&pc=HCTS&cvid=698255e0d75841f79f7f190ebe8ae65d&ei=85
0 · Reply
Seenalot
Seenalot Feb. 3 at 8:09 PM
$GSIT "just beat nvda and qcom..." Nope. They didn't. They DO NOT have a chip that does what the APU connected with the external DRAMs (used for the test) does. The study merely showed that IF they could somehow change their chip to include WAY more data on it AND somehow eliminate the bottlenecks that are currently in it, THEN they show the stated results.
0 · Reply
Stockfreshman
Stockfreshman Feb. 3 at 7:49 PM
$GSIT It is one month old baby now. It will grow to very big guy.
0 · Reply
dipbuyerripseller
dipbuyerripseller Feb. 3 at 4:43 PM
$GSIT buyout price billion or more so 20+? So let’s work backwards. The company has amazing hardware that just beat NVDA and QCOM in publicly announced tests. Drone market is massive with contracts flying off the shelf. What’s this leave? Software is key. Government funding is specifically earmarked for software development. Building the software stack for sentinel award now. When it’s done, good luck! Shorts are dead imho
1 · Reply
DrocDolf
DrocDolf Feb. 3 at 4:00 PM
$GSIT 2/2 -GSI is almost certainly hiding that their chip did not run Gemma-3 at all, only the pre-generation RAG phase. APU lack the MAC units required for matrix multiplication, which is critical for AI workloads. -In the October 20 PR reporting on Cornell's paper, GSI never disclosed this critical and materially important fact (on the contrary, they portrayed the findings as actual results of their current chip, deceiving most investors in the process): Cornell SIMULATED HBM2E EXTERNAL MEMORY INTERFACE, the most important part of an AI system, and both performance and energy consumption were based on that simulation. In other words, Cornell studied a fictitious chip that GSI DOES NOT HAVE. -GSI has exposed itself to securities fraud lawsuits, by lying about easily verifiable, material facts. Investors who bought at $18 and lost money would likely win. The company is flush with investor cash obtained through deception & immediate dilution, so full compensation is entirely feasible
0 · Reply
DrocDolf
DrocDolf Feb. 3 at 3:51 PM
$GSIT 1/2 GSIT's investors can now be SURE that GSIT cannot compete in the Edge AI sector. This is why they blatantly lie and hide data. Summary of findings: -The exact same model GSI talks about in its fraudulent January 29 PR, Gemma-3 12B, has been benchmarked on Jetson Thor. -Jetson Thor is actually 58 TIMES FASTER than GSIT's APU. -GSI lied to investors claiming that Jetson Thor needs 3 seconds for TTFT. For the exact same model, Gemma-3 12B, Jetson Thor has a TTFT latency of 52 milliseconds, 58 times faster than 3 seconds. -GSIT's APU is completely outside the range considered acceptable for real-time detection, at most 200 milliseconds. A detection every 3 seconds is laughable and completely useless, especially for military drones. -Even on a much larger model than Gemma-3 12B, concretely on Qwen-3 32B, and with a much larger input size, 2040 tokens vs 256 tokens, TTFT on Jetson Thor is 385 milliseconds.
1 · Reply
OleStockHound
OleStockHound Feb. 3 at 1:31 AM
$GSIT I think if this is to happen these 3 stocks will be needed: 1. $GSIT : Edge computing, especially the CIM architecture for optimal use and conservation of energy. Initial stages you will be dealing with a finite amount of energy available for robots and machinery and need split second decisions without data centers. The signal would take forever to get from Earth to Mars. 2. $ASTI lightweight and saves space and cost per launch. Elon is big on solar and this thin film technology can be damaged and still work. A vital source of energy when starting a colony on an alien world. Beaming technology might be in play as well. 3. $KULR Power source for high wattage batteries and already operating on Mars. Their batteries have achieved the highest certification for safety and quality. Their TPS prevents lithium runaway because of a bad cell. They specialize in thermal management and vibration reduction. Both are a plus on an alien world. https://youtu.be/az5nQLRNzhM?si=AFapCVj39WGNJe2Y
0 · Reply
OleStockHound
OleStockHound Feb. 2 at 5:06 PM
$GSIT Edge AI anyone? https://defence-industry.eu/lockheed-martin-tests-sniper-networking-targeting-pod-in-first-multi-aircraft-f-16-flight-demonstration/
1 · Reply
Seenalot
Seenalot Feb. 2 at 4:04 PM
$GSIT @DrocDolf @Peaceouty Part 2 AI Response 2. What is a "Benchmark"? A Benchmark is a standardized test used to measure performance (like a 40-yard dash for athletes). For these chips, the benchmark usually measures speed (how many words/tokens it can generate per second) or latency (how long it takes to start responding). Core Argument The Stocktwits user claims that GSI Technology (GSIT) is misleading or that the comparison is unfair because: NVIDIA's website shows how fast its Thor chip runs a small 3B model. GSI claims its Gemini-II chip performed well, but it was tested using a much larger 12B model. Why the comparison is invalid: If Chip A runs a 5lb weight (3B model) and Chip B runs a 20lb weight (12B model), their finish times are not comparable. The heavier 12B model naturally slows down any chip. Comparing it to a speed score from a lighter 3B model is not mathematically valid.
0 · Reply
Seenalot
Seenalot Feb. 2 at 4:03 PM
$GSIT @DrocDolf @peaceouty In case others are as lost as I am, here's and AI explanation I found helpful: I dont' understand what benchmark and model mean in this context. Can you explain the following phrase, "Thor’s benchmark shown on NVIDIA website is the 3B LLM. GSI tested with a more complicated 12B LLM model. You can’t compare the two" AI answer (Part 1): In this context, the critique is highlighting an "apples-to-oranges" comparison. Here is the breakdown of what those terms mean for these specific chips: 1. What is a "Model"? (The 3B vs. 12B) In AI, a Model is the software "brain" the chip is running. The numbers 3B and 12B refer to "Parameters"—the billions of connections inside that brain. 3B (3 Billion): A smaller, lighter model. It requires less memory and less processing power to run. 12B (12 Billion): A significantly larger and more "complicated" model. It is roughly 4x heavier, meaning the chip has to work much harder and move more data to get an answer.
1 · Reply
DrocDolf
DrocDolf Feb. 2 at 2:30 PM
$GSIT Further proof that GSIT are lying. Video shows that even on a much larger model than Gemma-3 12B, Qwen-3 32B: -TTFT is 385 ms for Jetson Thor. -The estimated ~1:4 ratio between TPOT & TTFT is still valid. Input size: This test: 2040 tokens Gemma-3: 256 tokens Link to the video: https://x.com/i/status/2018330459860508986 .
0 · Reply
Peaceouty
Peaceouty Feb. 2 at 1:53 PM
0 · Reply
DrocDolf
DrocDolf Feb. 2 at 10:01 AM
$GSIT It is not that those trying to confound people are complete idiots who do not understand simple arithmetic. It is that they are connected to criminal insiders and are desperate because they know they are finished. There is a real possibility that some of them will end up in jail.
0 · Reply
Peaceouty
Peaceouty Feb. 2 at 9:47 AM
$GSIT Hahah I see what you did there. 3B LLM vs 12B LLM is x4. Stop pulling numbers out of your ass dude.
1 · Reply
WallStreetBuyDip
WallStreetBuyDip Feb. 2 at 4:03 AM
many rushing into $GSIT but i'll wait for H% to get low first like this
0 · Reply
DrocDolf
DrocDolf Feb. 2 at 2:00 AM
$GSIT Are you stupid? You're using the same PR from GSI that I proved is full of lies as a counterargument. 🤦🏻🤡 It's like showing someone a broken scale that says 200 kg, proving it's broken, and then they insist "No, you're wrong, it really says 200 kg".
1 · Reply
BullishLongs
BullishLongs Feb. 2 at 12:19 AM
$GSIT enough said lol
0 · Reply
Stock_Catcher
Stock_Catcher Feb. 2 at 12:08 AM
Money Monday Watchlist Pt.7 $SIDU $LUNR $SLV $GSIT $CLSK New Month February , Let's Find Another 5000% Runner Team
1 · Reply
OleStockHound
OleStockHound Feb. 1 at 11:39 PM
$GSIT if this chip is integrated into autonomous defense stacks across several programs, it's on. NATO and the EU markets open up and GSIT can reach triple digits in stock price https://youtu.be/XZqnJZ3Fnlg?si=c_hVkiaWPCTm3mTH
2 · Reply
Peaceouty
Peaceouty Feb. 1 at 7:06 PM
$GSIT Perfect for drones.
2 · Reply
DrocDolf
DrocDolf Feb. 1 at 3:13 PM
$GSIT To be clear, I'm not comparing tokens per second with time to first token (TTFT). I'm comparing TTFT for BOTH, Jetson Thir and GSIT's APU-2. This is an apples to apples comparison. Period. Here is the accurate estimate of Time to First Token (TTFT) for Jetson Thor, using EXACTLY the same VLM model allegedly used by GSIT (Gemma-3 12B): We know that on Thor: -Tokens per second: 76.94 -TTFT is ~4x TPOT (Time Per Output Token) So: TPOT: 1/76.94 = 13ms TTFT is ~4x TPOT -->13x4=52ms So, TTFT is: Thor: 52 ms GSIT: 3000 ms 🚨THOR IS 58X TIMES FASTER GSIT are a bunch of liars. In fact people who lost money buying at 18 could easily win a lawsuits against the GSI for securities fraud. In the PR reporting Cornell paper GSI omitted a material and critical fact deceiving most investors: Cornell simulated HBM2e therefore studied a fictitious chip that GSI DO NOT HAVE This should be very easy to win and the company is loaded with cash so you can demand full compensation for your losses
0 · Reply