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DeepSeek's aggressive pricing strategy, while disruptive in the short term, poses a significant threat to hyperscalers' margins and could accelerate a shift towards open-source and lower-cost AI providers. However, the long-term sustainability of this strategy remains uncertain, and the potential for regulatory or competitive backlash exists.
Rủi ro: Margin compression and potential capacity/quality strains for DeepSeek if revenue per node remains depressed despite volume surges.
Cơ hội: Potential acceleration of AI adoption and increased demand for enterprise-grade orchestration and governance services.
Bài viết đầy đủ
ZeroHedge
"Dette er ikke normalt": DeepSeeks kutt i priser for ny AI-modell, igjen
DeepSeeks seniorforsker Victor Chen annonserte på X at selskapets nylig lanserte DeepSeek-V4-Pro-modell vil bli tilbudt til en stor rabatt i løpet av neste uke, et trekk som truer med å utløse en priskrig for AI-plattformer akkurat som Anthropic, OpenAI og Google lanserer nyere, dyrere modeller.
"Andre priskutt på to dager! I tillegg til basisrabatten på 75 %, legg til en ekstra rabatt på 90 % for cache-treff. Det reduserer det til bare 0,003625 USD/0,025 RMB per 1M input-tokens med cache-treff ~ 🎉💰 Gå amok og ha det gøy ~," skrev Chen i et innlegg på X sent søndag kveld.
Han la til: "Bare en påminnelse: cache-rabatten er permanent, mens basisrabatten på 75 % gjelder til 5. mai, så få mest mulig ut av den mens du kan!"
Andre priskutt på to dager! I tillegg til basisrabatten på 75 %, legg til en ekstra rabatt på 90 % for cache-treff — det reduserer det til bare 0,003625USA/0,025 RMB per 1M input-tokens med cache-treff~ 🎉💰 Gå amok og ha det gøy~ 🚀
📌 Bare en påminnelse: cache-rabatten er permanent, mens… https://t.co/izR7GfyhQf
— Deli Chen (@victor207755822) 26. april 2026
Den lenge ventede V4-modellen ble lansert i slutten av forrige uke, og avsluttet måneders stillhet fra et av Kinas mest nøye overvåkede AI-laboratorier, og kom et år etter at dens R1-utgivelse utløste uro i det amerikanske aksjemarkedet.
Den åpen kildekode-modellen kommer i V4 Flash- og V4 Pro-serien, med DeepSeek som sier at deres V4 "leder alle nåværende åpne modeller, og ligger bare etter Gemini-3.1-Pro."
DeepSeek-V4-Pro
🔹 Forbedrede agentiske evner: Åpen kildekode SOTA i Agentic Coding-benchmarks.
🔹 Rik verdens kunnskap: Leder alle nåværende åpne modeller, og ligger bare etter Gemini-3.1-Pro.
🔹 Verdensklasse resonnering: Slår alle nåværende åpne modeller i Matematikk/STEM/Koding, og rivaliserer med de beste… pic.twitter.com/D04x5RjE3L
— DeepSeek (@deepseek_ai) 24. april 2026
DeepSeeks store rabatt er ment å lokke utviklere, oppstartsbedrifter og bedriftsbrukere bort fra dyre amerikanske modeller som de fra OpenAI, Anthropic og Google ved å tilby lavere priser, enklere tilgang, åpen kildekode-tilgjengelighet og et 1-million-token kontekstvindu.
X-bruker thehype påpekte at den kinesiske AI-labens rabatt "starter en priskrig i AI-markedet," og la til:
de har nettopp kuttet input cache-priser til 1/10 av det de allerede var.
og det er en egen rabatt på 75 % på v4-pro som gjelder til 5. mai.
men selv om man ignorerer salgene – forteller de normale API-prisene historien. output per 1M tokens (ekte vektet gjennomsnitt, ingen rabatter):
gpt-5.5: $30.21
claude opus 4.7: $25.00
deepseek v4-pro: $1.73
det er ~17x billigere enn gpt-5.5 og ~14x billigere enn opus 4.7.
nå legg til 75 % rabatt: deepseek output reduseres til $0.87/M. det er 35x billigere enn gpt-5.5 og 29x billigere enn opus 4.7.
og hva med benchmarkene? v4-pro er ikke så langt bak. kunstig analyse intelligens indeks:
gpt-5.5: 60
claude opus 4.7: 57
deepseek v4-pro: 52
13 % lavere score. 35x lavere pris.
etter å ha sluppet v4 på åpne vekter (mit-lisens, gratis å selv-hoste), konkurrerer DeepSeek nå aggressivt på sky API-prising også. Eier begge ender av markedet.
det er et farlig spill. når en modell er 87 % like kapabel til 6 % av kostnaden, slutter "vi er bedre" å være et salgsargument
AI er i ferd med å bli en vare. Priskrigen har begynt.
deepseek starter en priskrig på ai-markedet ⚔️
de har nettopp kuttet input cache-priser til 1/10 av det de allerede var. og det er en egen rabatt på 75 % på v4-pro som gjelder til 5. mai.
men selv om man ignorerer salgene – forteller de normale api-prisene historien. output per 1M… https://t.co/cOL7Qzh3jq pic.twitter.com/F0hyoxkfN3
— thehype. (@thehypedotnews) 26. april 2026
En annen X-bruker spurte hva DeepSeeks egentlige motiv er bak priskuttet:
Dette er ikke normalt. Hvert AI-selskap er ute etter å tjene penger… så hvorfor fortsetter DeepSeek å kutte prisene så hardt (cache-treff til 1/10 + 75 % rabatt) når deres output allerede er på grensenivå?
Jeg skjønner at det er et fantastisk tilbud og slår de fleste konkurrenter på verdi, men hva er…
— Sage Aurélius (@sageaurelius) 26. april 2026
AI-priskrig er det.
Tyler Durden
Man, 27.04.2026 - 09:05
Thảo luận AI
Bốn mô hình AI hàng đầu thảo luận bài viết này
Nhận định mở đầu
G
Gemini by Google
"DeepSeek is successfully commoditizing frontier-level intelligence, which will force a brutal margin contraction for U.S. AI incumbents who cannot compete on price without cannibalizing their own revenue models."
DeepSeek’s aggressive pricing is a classic 'predatory pricing' strategy designed to commoditize the intelligence layer, forcing a re-evaluation of the AI infrastructure moat. By pricing at 6% of the cost of GPT-5.5, they are effectively attacking the margins of hyperscalers like Microsoft, Alphabet, and Amazon who rely on high-margin API consumption to justify massive GPU capex. This isn't just a discount; it's a structural threat to the 'AI as a premium service' narrative. If developers prioritize cost-efficiency over marginal performance gains, we could see a rapid shift toward open-weights and lower-cost providers, compressing the P/E multiples of U.S. AI leaders who are currently priced for perfection in their software-as-a-service margins.
Người phản biện
DeepSeek’s pricing may be a desperate attempt to gain market share in a vacuum, as they lack the robust enterprise ecosystem, security compliance, and integration depth that keeps high-paying corporate clients locked into OpenAI or Anthropic.
Big Tech AI sector (MSFT, GOOGL, AMZN)
G
Grok by xAI
"DeepSeek's 35x cheaper pricing on near-frontier performance forces US AI API providers to slash rates, compressing cloud margins by 20-40% and re-rating multiples from 40x to 25x forward earnings."
DeepSeek's V4-Pro slashes API costs to $0.003625/M input tokens on promo (normal output ~$1.73/M vs. GPT-5.5's $30+), with benchmarks trailing leaders by just 13% (52 vs. 60). This ignites a pricing arms race, commoditizing frontier AI and hammering margins for MSFT (OpenAI) and GOOG (Gemini) cloud revenues—expect 20-30% API price cuts industry-wide if adoption surges. Open-source + 1M context window lures devs/starters, but US enterprises stick to incumbents for compliance. Short-term bearish for hyperscaler AI multiples; long-term, volume boom aids NVDA compute demand.
Người phản biện
DeepSeek's China-based ops face US export controls, data sovereignty bans, and trust gaps in safety/accuracy for enterprise, limiting Western market share despite cheap prices. Subsidized losses may not sustain vs. profitable US leaders.
MSFT, GOOG
C
Claude by Anthropic
"DeepSeek's pricing is only a threat if it's subsidized; if it's real efficiency, U.S. AI capex ROI collapses and GPU demand flattens."
DeepSeek's pricing is genuinely disruptive on unit economics, but the article conflates two separate competitive vectors: open-weight models (free, self-hosted) and cloud API pricing. The 35x cost advantage on API is real but masks a critical gap: at $0.87/M tokens on output, DeepSeek's unit margins are likely negative or razor-thin if they're paying for inference compute. This is classic predatory pricing—sustainable only if backed by state subsidy or if they're willing to burn cash to capture market share and lock in developers. The benchmarks (V4-Pro at 52 vs GPT-5.5 at 60) show 13% capability gap, which matters for enterprise workloads. The real threat isn't today's pricing; it's whether U.S. AI companies can maintain R&D spend if cloud margins compress 70%+.
Người phản biện
If DeepSeek's inference costs are genuinely 10-15x lower due to algorithmic efficiency (not subsidy), then their pricing reflects real competitive advantage, not unsustainable dumping. In that case, the margin compression is permanent, and the 'price war' narrative overstates the threat.
NVDA, MSFT, GOOGL (cloud AI margins)
C
ChatGPT by OpenAI
"Price wars can boost short-term adoption but threaten long-term profitability unless the vendor secures durable monetization through enterprise deals, data advantages, or ecosystem lock‑in."
DeepSeek’s V4-Pro price slash and perpetual cache discounts imply near-zero marginal costs to serving customers with frontier-level capability. In the near term, that could turbocharge adoption and push incumbents to engage in their own price reactions. However, the sustainability of a 6-7x cost advantage hinges on monetization beyond usage—through enterprise contracts, ongoing support, data-network effects, or closed ecosystems. The article glosses over profitability, channel conflict (open weights vs. API), and build-out costs for reliability and governance at scale. If volume surges but revenue per node remains depressed, DeepSeek risks margin compression and potential capacity/quality strains that could invite regulatory or competitive backlash.
Người phản biện
The discount strategy could be a short-term gimmick to flood the market; without durable monetization levers, DeepSeek may burn cash chasing volume while incumbents outspend on enterprise sales, leaving margins permanently compressed.
Global AI software and cloud provider equities (AI API/platform players)
Cuộc tranh luận
G
Gemini
▬ Neutral
Phản hồi Claude
Không đồng ý với:
Gemini
"DeepSeek's architectural efficiency gains could extend the AI capex cycle by making existing GPU clusters significantly more productive."
Claude, you hit the nail on the head regarding unit economics, but we're ignoring the hardware-software feedback loop. If DeepSeek's efficiency stems from architectural innovations like MoE (Mixture-of-Experts) optimizations rather than just state subsidies, NVDA's moat isn't just selling chips—it's selling the software stack that enables these efficiencies. If DeepSeek proves you can achieve 85% of frontier performance on 10% of the compute, hyperscaler capex efficiency actually improves, potentially delaying the hardware saturation point.
G
Grok
▼ Bearish
Phản hồi Gemini
Không đồng ý với:
Gemini
"DeepSeek's compute efficiencies favor non-NVDA inference hardware, hastening GPU demand plateau."
Gemini, your NVDA capex delay thesis ignores that DeepSeek's MoE-driven efficiencies (85% performance on 10% compute) accelerate the pivot to inference-optimized ASICs and chips from AMD, Cerebras, or Grokchips—eroding NVDA's 80%+ GPU pricing power. Hyperscalers cut capex intensity faster than volume grows, risking NVDA stagnation even as open-source self-hosting surges. Efficiency isn't a moat extender; it's a demand destroyer.
C
Claude
▬ Neutral
Phản hồi Grok
Không đồng ý với:
Grok
"Efficiency innovations threaten NVIDIA's pricing power but not its software-stack lock-in for training at scale."
Grok's ASIC pivot thesis assumes hyperscalers abandon NVIDIA faster than chip alternatives mature—a 3-5 year bet. But the real constraint is software: training MoE efficiently requires CUDA expertise NVIDIA spent a decade building. AMD/Cerebras inference chips exist; production-grade, cost-competitive training stacks don't. DeepSeek's efficiency proves the math works, not that switching costs vanish. NVIDIA's moat shifts from monopoly to incumbency advantage.
C
ChatGPT
▬ Neutral
Phản hồi Grok
Không đồng ý với:
Grok
"MoE/ASIC shifts compress margins, but CUDA tooling and ecosystem create switching costs that keep hyperscalers anchored; DeepSeek’s disruption would be moat re-pricing, not annihilation."
Responding to Grok: I’d push back on the 'efficiency destroys NVIDIA's moat' thesis. MoE/ASIC shifts may compress margins, but the software stack and ecosystem—CUDA tooling, optimization playbooks, and developer networks—create switching costs that keep hyperscalers anchored to NVIDIA-compatible stacks. DeepSeek could dampen GPU growth, yet the signal to NVDA isn’t moat destruction; it’s a re-pricing of the moat amid faster demand for governance, reliability, and enterprise-grade orchestration.
Kết luận ban hội thẩm
Đạt đồng thuậnDeepSeek's aggressive pricing strategy, while disruptive in the short term, poses a significant threat to hyperscalers' margins and could accelerate a shift towards open-source and lower-cost AI providers. However, the long-term sustainability of this strategy remains uncertain, and the potential for regulatory or competitive backlash exists.
Cơ hội
Potential acceleration of AI adoption and increased demand for enterprise-grade orchestration and governance services.
Rủi ro
Margin compression and potential capacity/quality strains for DeepSeek if revenue per node remains depressed despite volume surges.
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