OpenAI released o3 and o4-mini on April 16, its first o-series models that can call tools — web search, Python, image processing, image generation — inside the chain of thought instead of between turns. o3 scores 69.1% on SWE-bench Verified without custom scaffolding, against 49.3% for o3-mini and 62.3% for Claude 3.7 Sonnet, with o4-mini at 68.1%; o3 costs $10 per million input tokens and $40 per million output, while o4-mini holds o3-mini's $1.10/$4.40. Both launched with a longer-thinking o4-mini-high variant and a promised o3-pro.

The same day OpenAI published Codex CLI on GitHub under Apache-2.0: a local terminal coding agent that reads and edits files in the working directory and executes shell commands under approval modes the user configures. It occupies the lane Anthropic's Claude Code and Aider opened, and it gives the o-series models a first-party, auditable harness to drive.

Nvidia disclosed in an 8-K filed April 15 that the US government told it on April 9 that exporting H20 chips — and any chip matching H20's memory bandwidth, interconnect bandwidth, or a combination of both — to China, Hong Kong, Macau and D:5 countries requires a license, and then said on April 14 that the requirement will hold for the indefinite future. Nvidia expects up to roughly $5.5 billion of charges in the first quarter of fiscal 2026, covering H20 inventory, purchase commitments and related reserves; the stock fell about 6%.

The H20 was the compliant SKU designed to sit under earlier export thresholds and generated an estimated $12-15 billion of revenue in 2024, so this closes the purpose-built path to Chinese datacenters rather than tightening a rule the product already met. The bandwidth-based wording also reaches any future part cut to the same specification.

Z.ai, the international brand of Zhipu AI, released the GLM-4-32B-0414 series on April 14: a 32B dense base, GLM-Z1-32B-0414 for reasoning, a search-using GLM-Z1-Rumination-32B-0414 aimed at deep-research tasks, and 9B variants, all under the MIT license on Hugging Face. The base was pre-trained on 15T tokens with substantial reasoning-oriented synthetic data, ships with a 32K context extendable to 128K, and its config is a 61-layer, 6144-wide dense model in bf16 — one 80GB-class GPU.

Z.ai claims GLM-Z1-32B-0414 matches DeepSeek-R1 (671B) on certain tasks and that the base is comparable to GPT-4o and DeepSeek-V3-0324 (671B) on code generation and Q&A benchmarks. MIT means no field-of-use limit, no monthly-active-user trigger — unlike Llama 4's 700M-MAU clause — and no naming obligation. Two days later OpenAI's strongest reasoner shipped API-only at $10/$40 per million tokens, which is the contrast of the week: the gap between open weights and closed frontier is now measured in days, not releases.

OpenAI launched GPT-4.1, GPT-4.1 mini and GPT-4.1 nano on April 14, API-only, with a 1M-token input window, 32,768 output tokens and a June 2024 knowledge cut-off. GPT-4.1 completes 54.6% of SWE-bench Verified tasks against 33.2% for GPT-4o, more than doubles GPT-4o on Aider's polyglot diff benchmark and beats GPT-4.5 by 8 points absolute, because it was trained to emit diffs instead of rewriting whole files. Pricing is $2/$8 per million tokens, $0.40/$1.60 for mini, and $0.10/$0.40 for OpenAI's first nano-tier model.

In the same announcement OpenAI deprecated GPT-4.5 Preview — the largest model it had ever run, launched 27 February — and gave developers until July 14, 2025 to migrate, four and a half months of life for a flagship. OpenAI's stated reason is that GPT-4.1 matches or exceeds it on many capabilities at much lower cost and latency.