Daily Digest

Friday, 17 April 2026

This dated roundup collects the most interesting AI and technology developments found for Friday, 17 April 2026.

3 min read Published from the latest available digest

Policy & Ethics

Payward to acquire Bitnomial, creating a fully CFTC-licensed derivatives platform

Combination of Bitnomial’s decade-built US regulatory infrastructure and Payward’s global distribution, scale, and multi-brand operating model to create one of the most comprehensively regulated and vertically integrated U.S. derivatives platforms The post Payward to acquire Bitnomial, creating a fully CFTC-licensed derivatives platform appeared first on Kraken Blog .

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Research & Products

Claude Opus 4.7 won 69 of 100 blind evals against Opus 4.6, judged by GPT-5.4, Gemini 3.1 Pro, and DeepSeek V3.2

I ran 100 blind questions across 5 categories (code, reasoning, analysis, communication, meta-alignment) and had three independent judges from three different model families evaluate both responses. Each judge saw responses labeled A and B with randomized order. Majority vote decides the winner. Per-judge results: |Judge|Opus 4.7 wins|Opus 4.6 wins|Ties|4.7 win %| |:-|:-|:-|:-|:-| |GPT-5.4|69|30|1|69.7%| |Gemini 3.1 Pro|76|22|0|77.6%| |DeepSeek V3.2|38|54|5|41.3%| |Aggregate|69|**

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Qwen 3.6 35B crushes Gemma 4 26B on my tests

I have a personal eval harness: A repo with around 30k lines of code that has 37 intentional issues for LLMs to debug and address through an agentic setup (I use OpenCode) A subset of the harness also has the LLM extract key information from reasonably large PDFs (40-60 pages), summarize and evaluate its findings. Long story short: The harness tests the following LLM attributes: - Agentic capabilities - Coding - Image-to-text synthesis - Instruction following - Reasoning Both models at UD-Q4_

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Don't ask Qwen 3.6 35b to give you aski image of Yoshi :)

https://preview.redd.it/dfqed57qgsvg1.png?width=1706&format=png&auto=webp&s=3859209698d2e844e2731326e355d60928658f8a The most fun part was reasoning, here is a gist: https://gist.github.com/anzax/5f06716c66180013cd715f6c2e5848df There is a lot of criticism about Qwen 3.6 long reasoning, but actually I found it overthink for silly request like this, and in practical agentic tasks, my experience, it stays focused and

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This digest was automatically generated • 3 min read