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Friday

  1. Story1 reports · 1 facts

    AYi shares a tip for starting the Codex quota window early

    On October 29, 2026, AYi AI Notes published an article sharing a technique the community had figured out for starting the Codex 5-hour quota window early. The article states that the 5-hour quota countdown begins with the first message of the day, so at 7:00 AM one can use Grok Bot to automatically run codex exec ping to trigger the countdown; after the quota resets at 12:00 noon, it then covers the afternoon work period. The article provides a ready-to-copy scheduled prompt and notes that this mechanism comes from community testing rather than official OpenAI documentation, and that a read-only parameter must be included when executing it. Currently this is the only source reporting it, with no subsequent developments yet.

    ge of the day, so at 7:00 AM one can use Grok Bot to automatically run codex exec ping to trigger the countdown; after the quota resets at 12:00 noon, it then covers the afternoon work period. The article provides a ready-to-copy scheduled prompt and notes that this mechanism comes from community testing rather than official OpenAI documentation, and that a read-only parameter must be included when executing it. Currently this is the only source reporting it, with no subsequent developments yet.

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  2. Story1 reports · 1 facts

    Arena says GPT-6.1 Terra (Max) ranks 8th in Agent Arena

    Arena released measured results based on nearly 9,000 agent sessions: OpenAI's GPT-6.1 Terra (Max) ranks 8th in Agent Arena, with a net improvement of +10.6% and a median cost per task of $0.62. This cost is lower than the $1.09 of 7th-place Gemini 4 Argon (High), the $0.89 of 6th-place GPT-6.1 Sol (Max), and the $5.16 of 5th-place GPT-6 Astra (Max). In the subcategory rankings, it places 3rd in Bash Reliability (+13.2%), 7th in Steerability (+13.3%), and 9th in Praise vs Complaint (+16.8%). There are currently no further developments.

    Arena released measured results based on nearly 9,000 agent sessions: OpenAI's GPT-6.1 Terra (Max) ranks 8th in Agent Arena, with a net improvement of +10.6% and a median cost per task of $0.62. This cost is lower than the $1.09 of 7th-place Gemini 4 Argon (High), the $0.89 of 6th-place GPT-6.1 Sol (Max), and the $5.16 of 5th-place GPT-6 Astra (Max). In the subcategory rankings, it places 3rd in Bash Reliability (+13.2%), 7th in Steerability (+13.3%), and 9th in Praise vs Complaint (+16.8%). The

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  3. Story1 reports · 1 facts

    Arena.ai Publishes Per-Task Cost Comparison of Models on Agent Arena

    Arena.ai published a per-task cost comparison of models on Agent Arena on October 30, 2026. Statistics show that OpenAI's GPT-6.1 Sol (Max) costs $1.91 per task, 85% lower than Claude Opus 5.5 (Max) at $12.51 and 87% lower than GPT-6 Astra (Max) at $14.93. Arena.ai noted that these two cost advantages come from different sources: relative to Astra, Sol's advantage mainly comes from a lower per-token price; relative to Opus, it mainly comes from consuming fewer tokens per task. Per-task cost is calculated by multiplying the number of input, output, and cache-read tokens by their respective unit prices, and Arena.ai identifies the reasons for the cost reduction by comparing prices and token usage.

    Arena.ai published a per-task cost comparison of models on Agent Arena on October 30, 2026. Statistics show that OpenAI's GPT-6.1 Sol (Max) costs $1.91 per task, 85% lower than Claude Opus 5.5 (Max) at $12.51 and 87% lower than GPT-6 Astra (Max) at $14.93. Arena.ai noted that these two cost advantages come from different sources: relative to Astra, Sol's advantage mainly comes from a lower per-token price; relative to Opus, it mainly comes from consuming fewer tokens per task. Per-task cost is c

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  4. Story1 reports · 1 facts

    Baseten optimizes Qwen3-ASR batch transcription deployment

    On October 29, 2026, the Baseten engineering team published a blog post describing optimizations for deploying Qwen3-ASR 1.7B batch transcription. Through native audio decoding, FP8 quantization of the KV cache, and reduced host-device synchronization, the team increased batch transcription throughput by 7x and reduced latency by 6.9x on a single RTX PRO 6000. After optimization, transcribing one hour of audio costs about $0.0013, or 1/10 of a cent per audio hour, with no noticeable change in word error rate. The optimized version is now the default deployment in the Baseten Model Library and can be called through an OpenAI-compatible transcription client.

    dio decoding, FP8 quantization of the KV cache, and reduced host-device synchronization, the team increased batch transcription throughput by 7x and reduced latency by 6.9x on a single RTX PRO 6000. After optimization, transcribing one hour of audio costs about $0.0013, or 1/10 of a cent per audio hour, with no noticeable change in word error rate. The optimized version is now the default deployment in the Baseten Model Library and can be called through an OpenAI-compatible transcription client.

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Friday

  1. Story1 reports · 1 facts

    Artificial Analysis releases Coding Agent Index v2.0

    On October 23, 2026, Artificial Analysis released Coding Agent Index v2.0, replacing DeepSWE with Cognition's FrontierCode v1.1 and tightening the repository question-answering scoring; the leaderboard evaluates model-plus-harness combinations. Reports that day showed Claude Code paired with Claude Opus 5.5 (max) topping the list with 61.7 points, Claude Code paired with Sonnet 5.5 second with 59.3 points, Muse Code paired with Muse Wonder Full at 58.9 points, and the first OpenAI combination, Codex paired with GPT-6 Astra, at 54.7 points. Regarding comparisons between the old and new leaderboards, earlier reports said the average score of 21 configurations fell from 58.8% to 57.1%; later reports said the mean for the same batch of 21 configurations dropped from 54.8 to 47.4, with 20 declining, and stated that the main reason was FrontierCode's mean of about 45.1%, far below DeepSWE's 65.6%.

    Opus 5.5 (max) topping the list with 61.7 points, Claude Code paired with Sonnet 5.5 second with 59.3 points, Muse Code paired with Muse Wonder Full at 58.9 points, and the first OpenAI combination, Codex paired with GPT-6 Astra, at 54.7 points. Regarding comparisons between the old and new leaderboards, earlier reports said the average score of 21 configurations fell from 58.8% to 57.1%; later reports said the mean for the same batch of 21 configurations dropped from 54.8 to 47.4, with 20 decl

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Sunday

  2. Story1 reports · 1 facts

    n8n blog introduces running AI workflows locally on DGX Spark

    On October 19, 2026, the n8n blog published a tutorial on how to deploy a complete model stack locally on a single NVIDIA DGX Spark, enabling n8n workflows to handle transcription, OCR, document Q&A, and image generation without calling cloud APIs. The tutorial states that the entire stack exposes an OpenAI-compatible endpoint through LiteLLM, with the main model being the NVFP4 version of Qwen3.6-35B-A3B, achieving a generation speed of 120 tokens/s for a single user and 359 tokens/s combined for eight users. The author's hands-on testing found that image generation reduces conversation speed to about one-third, and recommends that small teams queue image tasks or schedule them outside working hours. Currently, this content has only the n8n blog as its source.

    DGX Spark, enabling n8n workflows to handle transcription, OCR, document Q&A, and image generation without calling cloud APIs. The tutorial states that the entire stack exposes an OpenAI-compatible endpoint through LiteLLM, with the main model being the NVFP4 version of Qwen3.6-35B-A3B, achieving a generation speed of 120 tokens/s for a single user and 359 tokens/s combined for eight users. The author's hands-on testing found that image generation reduces conversation speed to about one-third, a

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Wednesday

  2. Story1 reports · 1 facts

    Artificial Analysis Launches Dual HealthBench Leaderboards

    Artificial Analysis has launched leaderboards for OpenAI's two health dialogue benchmarks, HealthBench and HealthBench Professional. HealthBench contains 5,000 conversations with general users and health workers, while HealthBench Professional consists of 525 conversations all aimed at clinicians. The leaderboard results show that on HealthBench Professional, GPT-6 Astra (max) ranks first with a length-adjusted score of 66.0%, followed by GPT-6.1 Sol (max) at 65.1% and Claude Sonnet 5.5 (max with fallback) at 63.0%; on HealthBench, Claude Sonnet 5.5 (max with fallback) leads with 62.1%, while DeepSeek V4.1 Flash (max) scores 60.9%. In addition, Claude Opus 5.5 and Claude Fable 5.1 give average answers of about 5,900 characters, losing more than 11 points after length adjustment. There are currently no further developments.

    Artificial Analysis has launched leaderboards for OpenAI's two health dialogue benchmarks, HealthBench and HealthBench Professional. HealthBench contains 5,000 conversations with general users and health workers, while HealthBench Professional consists of 525 conversations all aimed at clinicians. The leaderboard results show that on HealthBench Professional, GPT-6 Astra (max) ranks first with a length-adjusted score of 66.0%, followed by GPT-6.1 Sol (max) at 65.1% and Claude Sonnet 5.5 (max wit

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Wednesday

  1. FactRelated story

    English translation is being prepared.

    On October 13, 2026, Google announced that developers can now use Gemini 4 Argon to build applications. This frontier model targets complex workflows such as real software engineering, enterprise knowledge work, and cybersecurity defense, and is designed for long-horizon tasks requiring deep reasoning and structural precision. Google also provided the Gemini API developer guide and entry points for using it in Google Antigravity and Android Studio. On the same day, Google disclosed an unattended experiment: letting Argon optimize the open-source framework google/adk-python, which has about 205,000 lines of code, within 11 hours. The model proposed 6 optimizations; after human review, 2 were merged into the main branch, memory session preparation time for long sessions was reduced by about 40%, and cold-start import speed improved by 21%. On October 14, Sundar Pichai called this a good summary of the safety and alignment work on Argon 4; Ethan Mollick commented that Gemini 4 is a major leap compared with previous Gemini models but still lags on complex multi-agent tasks. On October 15, Google began rolling out Gemini 4 Argon support to the AI programming tool Antigravity.

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    View story:Google opens Gemini 4 Argon to developers

Sunday

Tuesday

Wednesday

  1. Testing Catalog

    Artificial Analysis Intelligence Index v5 is live, Claude…

    Artificial Analysis Intelligence Index v5 is live, featuring 2 new benchmarks and 3 upgrades, of which 60% are based on private test sets or held-out answers. Claude Opus 5.5 (max) leads with 58 points, followed closely by GPT-6 Astra (max) at 57 points and GPT-6.1 Sol (max) at 55 points, with Gemini 4 Argon (high) further back at 50 points. The gap between open-weight models and the leader has widened from 3 points to 12 points; among released weights, DeepSeek V4.1 Flash 1017 (max) and GLM-5.3 (max) lead with 32 points.

    Artificial Analysis Intelligence Index v5 is live, featuring 2 new benchmarks and 3 upgrades, of which 60% are based on private test sets or held-out answers. Claude Opus 5.5 (max) leads with 58 points, followed closely by GPT-6 Astra (max) at 57 points and GPT-6.1 Sol (max) at 55 points, with Gemini 4 Argon (high) further back at 50 points. The gap between open-weight models and the leader has widened from 3 points to 12 points; among released weights, DeepSeek V4.1 Flash 1017 (max) and GLM-5.3

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    #hot-signal#Evaluations / benchmarks#Anthropic#OpenAI
  2. Official Pydantic AI articleSelected

    Pydantic compares code mode and tool calling across 5,276 runs

    Michael Pfaffenberger of Pydantic used 5 small Pydantic AI applications and 8 models to conduct 5,276 scored runs, comparing code mode with direct tool calling. On long tasks, code mode reduced average cost by 58%, latency by 51%, and increased success rate by 16 percentage points; however, for short tasks with 5 items, 3 out of 5 tasks were instead 21% to 38% more expensive. The author argues that models are better at writing loops than at acting as the loop, and the gap widens as tasks get longer.

    Michael Pfaffenberger avatar

    Michael Pfaffenberger of Pydantic used 5 small Pydantic AI applications and 8 models to conduct 5,276 scored runs, comparing code mode with direct tool calling. On long tasks, code mode reduced average cost by 58%, latency by 51%, and increased success rate by 16 percentage points; however, for short tasks with 5 items, 3 out of 5 tasks were instead 21% to 38% more expensive. The author argues that models are better at writing loops than at acting as the loop, and the gap widens as tasks get lon

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    #company#Evaluations / benchmarks#Agents#English text is being prepared.
  3. Unite.AI

    Perplexity Publishes LLM Gateway Best Practices Guide, Outlining Request Flow and Production Risks

    On October 27, 2026, Perplexity published an LLM gateway best practices guide explaining how this middleware layer routes, authenticates, caches, and logs model calls, and distinguishing four categories: API gateways, LLM gateways, MCP gateways, and AI gateways. The guide breaks down the mechanism through a six-step request lifecycle, while warning that the gateway centralizes credentials from various providers, and cites the LiteLLM gateway breach disclosed by Microsoft and two high-severity vulnerabilities, CVE-2026-35029 and CVE-2026-59823, reported by Check Point (already fixed in LiteLLM 1.83.9). The article also lists postmortems of Cloudflare AI Gateway and OpenRouter outages, four deployment paths, and paid plans starting at about $50 per month.

    On October 27, 2026, Perplexity published an LLM gateway best practices guide explaining how this middleware layer routes, authenticates, caches, and logs model calls, and distinguishing four categories: API gateways, LLM gateways, MCP gateways, and AI gateways. The guide breaks down the mechanism through a six-step request lifecycle, while warning that the gateway centralizes credentials from various providers, and cites the LiteLLM gateway breach disclosed by Microsoft and two high-severity vu

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    #hot-signal#Safety / alignment#English text is being prepared.#OpenAI

Thursday

  1. Ayi AI Notes

    The author built an "EQ plugin" with Claude Opus 5.5 and used UUMit to turn a local service into a team link

    The author used Cursor together with Claude Opus 5.5 to build a zero-dependency local web tool called "EQ plugin," which rewrites emotionally charged drafts according to the four elements of Nonviolent Communication, and includes seven types of communication targets and three tone levels: gentle, firm, and direct. The tool runs on the local machine at 127.0.0.1:8787, and the UUMit client generates a fixed HTTPS link to distribute to colleagues, with no need to buy a server or file for registration, and permissions can be granted and revoked per person. The article also provides an 800-character limit per input, default rate limits of 10 times per minute and 200 times per day, as well as the source code and System Prompt for two GitHub repositories.

    The author used Cursor together with Claude Opus 5.5 to build a zero-dependency local web tool called "EQ plugin," which rewrites emotionally charged drafts according to the four elements of Nonviolent Communication, and includes seven types of communication targets and three tone levels: gentle, firm, and direct. The tool runs on the local machine at 127.0.0.1:8787, and the UUMit client generates a fixed HTTPS link to distribute to colleagues, with no need to buy a server or file for registrati

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    #hot-signal#Tutorials / practice#Agents#English text is being prepared.

Tuesday

  1. Artificial Analysis full article

    Artificial Analysis releases Intelligence Index v5, with 60% of evaluations switched to private datasets

    Artificial Analysis releases Intelligence Index v5, adding two new benchmarks, FrontierCode 2.0 and Terminal-Bench-Science, upgrading HLE-Diamond, AA-Omniscience v1.1, and CritPt v2, with 60% of evaluations based on private test sets or held-out answers. Claude Opus 5.5 (max) ranks first with 58 points, followed closely by GPT-6 Astra (max) at 57 points and GPT-6.1 Sol (max) at 55 points, with Gemini 4 Argon (high) at 50 points. The gap between open-weight models and the leaders has widened from 3 points to 12 points; the released-weight DeepSeek V4.1 Flash 1017 (max) and GLM-5.3 (max) both score 32 points. The per-task cost of leading models differs by more than 13 times: GPT-6.1 Terra (max) is $0.96, while Claude Fable 5.1 (max) is $13.04. A Progress Index v1 was also released, placing models released since November 2022 on the same capability scale for comparison.

    Artificial Analysis releases Intelligence Index v5, adding two new benchmarks, FrontierCode 2.0 and Terminal-Bench-Science, upgrading HLE-Diamond, AA-Omniscience v1.1, and CritPt v2, with 60% of evaluations based on private test sets or held-out answers. Claude Opus 5.5 (max) ranks first with 58 points, followed closely by GPT-6 Astra (max) at 57 points and GPT-6.1 Sol (max) at 55 points, with Gemini 4 Argon (high) at 50 points. The gap between open-weight models and the leaders has widened from

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    #company#Evaluations / benchmarks#Agents#English text is being prepared.