DeepSeek’s Back, and It’s Bringing a Price War

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Chinese AI lab DeepSeek has unveiled preview builds of its long-awaited V4, a new family of open-source models boasting 1M-token context windows, Huawei chip support, and pricing that puts serious pressure on U.S. competitors.

What’s in it:

  • Early third-party benchmarks rank V4 Pro near the top of the open-source field, and DeepSeek’s own evals put it in the same tier as GPT-5.4 and Gemini 3.1-Pro on reasoning tasks.
  • It leads Vals AI’s Vibe Code Bench, though it lands in the fourth tier on AA’s Intelligence Index, alongside Meta’s Muse Spark.
  • At $1.74/$3.48 per million input/output tokens, V4 Pro costs a fraction of GPT-5.5 ($5/$30) and Opus 4.7 ($5/$25) — a price gap that’s hard to ignore.
  • Huawei confirmed its Ascend chips can run V4, offering the clearest proof yet of a functional AI infrastructure stack built entirely outside of Nvidia.

DeepSeek is back — and while markets aren’t in freefall this time, V4 reframes the AI competition around cost as much as raw capability. The Huawei angle may ultimately be the bigger story, though. A domestic Chinese chip stack demonstrating real-world viability suggests that U.S. export restrictions, long seen as a hard ceiling on China’s AI ambitions, may be a more porous barrier than assumed.

OpenAI retakes the frontier with GPT 5.5

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OpenAI has unveiled GPT-5.5, internally codenamed “Spud,” marking a significant step forward in its model lineup. The release is being framed as a new class of intelligence, with performance gains that place it at or near the top of industry benchmarks—reportedly edging past Anthropic in several key areas.

Key Highlights

  • GPT-5.5 achieves top-tier results across reasoning, agent-based tasks, coding, and computer-use benchmarks, with some metrics approaching those seen in leading models like Claude Mythos.
  • Despite the performance gains, the model maintains similar speed to GPT-5.4 while improving efficiency. OpenAI notes that both Codex and GPT-5.5 were used to help optimize its own GPU infrastructure.
  • API pricing is set at $5 per million input tokens and $30 per million output tokens, with OpenAI positioning it as roughly half the cost of competing frontier coding models.
  • The rollout includes availability across ChatGPT plans and within Codex, including specialized Thinking and Provariants, alongside continued emphasis on generous usage tiers.

Why It Matters

After a stretch where Anthropic held much of the momentum, the competitive landscape appears to be shifting again. OpenAI is moving quickly with high-impact releases, signaling a renewed push to lead at the frontier. At the same time, Anthropic has been facing user concerns around rate limits and output quality, making this a notable moment in the broader AI race.

U.S. flags Chinese labs ‘industrial-scale’ AI theft

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The White House has released a memo formally accusing Chinese AI companies of running “industrial-scale” distillation operations against American frontier labs — a significant escalation arriving just weeks before Trump’s planned summit with Xi Jinping in Beijing.

What’s going on:

  • Distillation means training smaller models on the outputs of mor powerful ones. The memo, authored by Kratsios, alleges China is doing this systematically through thousands of fraudulent API accounts and jailbreak exploits.
  • Anthropic had already privately called out DeepSeek, Moonshot, and MiniMax for distillation back in February. This memo takes those allegations public and enshrines them as federal policy.
  • The Chinese embassy pushed back hard, branding the accusations as baseless — a response that sets an awkward tone ahead of the May 14–15 Beijing summit.
  • A House Foreign Affairs bill that passed its first vote this week would pressure the administration to place distillation offenders on the U.S. export blacklist.

Why it matters: Dario Amodei has publicly positioned China as roughly 6–12 months behind leading U.S. labs. The Kratsios memo challenges the narrative around how that gap is being closed — framing Chinese AI progress less as homegrown innovation and more as a product of systematic data extraction. The real question is how much of DeepSeek’s and Kimi’s trajectory actually traces back to distillation, versus genuine research breakthroughs. That distinction carries enormous implications for how the U.S. responds — and how seriously to take the threat.