AI Coding Live News

Independent evaluator Artificial Analysis announced on X on November 4 that its six Capability Indexes (Finance & Accounting, Strategy & Ops, Legal, Healthcare & Medical, Engineering, Economics) are now v2.0, aligned with Intelligence Index v5.0 evaluations and weighting Non-Hallucination and Agentic Tool Use more heavily. Across the indexes, HLE becomes HLE-Diamond, AA-Omniscience moves to v1.1 and GDPval-AA is removed; Engineering gains a new Science capability. Per Artificial Analysis, Claude Opus 5.5 (max) leads all six, with GPT-6 Astra (max) second in Finance & Accounting, Legal and Engineering. Among open-weights models, Kimi K3.1 Pro (weights not yet released) leads all six at #5 to #8.

Zoom

On November 3, model-compression company Pruna AI open-sourced P-H3-Image, which turns MiniMax-H3, the open-weights video model MiniMax released this summer, into a text-to-image and image-editing model. Per Pruna: sampling drops from 50 to 8 steps, a 4 MP image on one B200 goes from 12.4 s to 2.6 s, the 4-bit set is a 20 GB download (vs 143 GB for H3), and peak VRAM at 8 MP is about 21 GB. It renders 2 to 16 MP and edits with multiple reference images. Weights are on Hugging Face with native ComfyUI support. It keeps the MiniMax H3 Community License, which by default excludes the EU, UK, South Korea and the US.

Zoom

On October 31, independent evaluator Artificial Analysis released AA-Omniscience v1.1, its knowledge and hallucination benchmark and part of Intelligence Index v5. The question set shrinks from 6,000 to 3,000, dropping previously public and saturated questions, fixing errors and ambiguities, and adding new ones, and a new 300-question public set on Hugging Face is calibrated to the private set's difficulty, with 0.99 Pearson and Spearman correlation on Net Score. Gemini 4 Carbon (high) leads with a Net Score of 54, ahead of Claude Opus 5.5 at 48 and Claude Fable 5.1 at 46; Fable 5.1 has the highest accuracy (68%) and Gemini 4 Argon the lowest hallucination rate (4%). Models score about 1.9 points lower than on v1 on average, and MiniMax M3.1 Flash drops 22 points. All figures are as reported by Artificial Analysis.

Zoom

On October 29 Pika released Pika H3 Flex, a joint audio-video generator post-trained on MiniMax H3, with weights on Hugging Face, code on GitHub, and ComfyUI and Diffusers support. Pika says it distilled sampling from 50 denoising steps to six, averages about 1.8x faster DiT denoising than Fal H3 Max at 768p, and can produce a 15-second clip with soundtrack in as little as about 7 seconds; the hosted API adds 1080p to 4K upscaling and five exportable audio stems (dialogue, score, SFX, foley, ambience). All speed and quality figures are vendor-reported.

Zoom

On the Cheeky Pint podcast with Stripe co-founder John Collison, published October 29, Sam Altman discussed the memory shortage. He said many people assume open-source models and local inference solve the compute crunch, but from a global allocation perspective it is "quite terrible" for everyone to have scarce DRAM sitting in their own computer and being used about 5% of the time, and that a supply-constrained world wants maximum utilization in the cloud. A pubity post quoting him drew more than 26,000 likes and over 8 million views, and many users pushed back that PC memory is not only for AI and that local models matter for privacy and offline use. This is a summary of an X discussion, not a verified conclusion.

Zoom

Perplexity CEO Aravind Srinivas posted early evals of Gemini 4 Carbon on X: it scored a record 0.857 on Perplexity's Wide-And-Deep-Research (WANDR) long-form research benchmark at $5.86 per task, versus 0.802 ($7.88) for Gemini 4 Argon and 0.735 ($13.34) for GPT-6 Astra. He called Carbon the strongest model Perplexity has seen for long-form research and answer quality, and said it will come to all Pro and Max users inside Perplexity Computer once there is enough token capacity.

Zoom

On Oct 30 Anthropic's official @claudeai account announced that Max 5x is now called Max (still $100/month) and Max 20x is now Ultra (still $200/month), with nothing for existing subscribers to do. Verified Ultra accounts also lose the rolling 5-hour usage limit starting that day, beginning with most existing subscribers; newer accounts keep a temporary limit until verified, and weekly limits are unchanged.

Zoom

At GitHub Universe 2026 on Oct 28, GitHub made Copilot Fusion generally available. It merges the multi-model orchestration of the Project HydraFusion research preview with Copilot auto model selection: users pick Copilot Fusion and an effort level (Standard, High or Max) in the model picker, and the system decides which models to use and whether to run a Single, Cascade or Critique workflow. GitHub says Fusion Max scored 60 on the Artificial Analysis Coding Agent Index, two points below Claude Code with Opus 5.5 Max, at about half the API cost per task, about half the tokens and about 40% less time. Each underlying model is billed at its standard rate, and paid plans get 30% off through Nov 30.

Zoom

On Oct 28 independent evaluator Artificial Analysis released Intelligence Index v5, its biggest revision since v4 in January: it adds Cognition's FrontierCode 2.0 and Terminal-Bench-Science, swaps Humanity's Last Exam for HLE-Diamond, and now draws 60% of its weight from private or held-out test sets. Claude Opus 5.5 (max) leads at 58, ahead of GPT-6 Astra at 57 and GPT-6.1 Sol at 55; the top open-weights model, Kimi K3.1 Pro (weights not yet released), scores 46, widening the gap from 3 points in v4.3 to 12. It also launched Progress Index v1 for comparing models across years.

Zoom

Cursor announced on Oct 26 (UTC) that DeepSeek V4.1 Flash is now available in Cursor and can be turned on under Cursor Settings > Models. Cursor says every effort level sits on the CursorBench cost frontier, from $0.60 to $0.98 per task, with no model scoring higher at those prices. The official CursorBench 4.0 leaderboard lists DeepSeek V4.1 Flash 1017 at 47.7% on Max ($0.98 per task), 46.3% on Medium ($0.80), 45.6% on High ($0.77) and 44.9% on Low ($0.60). The top score on the board, Opus 5.5 Max, is 57.8% but costs $13.43 per task.

Zoom

On Oct 26 OpenAI released GPT-6.1 Terra, an efficient model for visual reasoning, precise computer use and natural writing. It is rolling out today to Plus, Pro, Enterprise and Edu users in ChatGPT Work and Codex, and in the API as gpt-6.1-terra. Standard API pricing is $1 input, $0.05 cached input and $5 output per million tokens, which OpenAI says is 50% lower than GPT-5.6 Terra and GPT-6.1 Sol, with a 1,050,000-token context window. By OpenAI's figures it scores 15 points higher than GPT-5.6 Terra on Agents' Last Exam at medium effort for about a third of the cost, and solves 50.3% of Terminal-Bench 4.0 at max effort.

Zoom

On 2026-10-23 (16:53 UTC) the official @blocks account unveiled Dessa, and Jack Dorsey called it the most authentic full-duplex speech model ever built. The official page block.xyz/dessa says Dessa is a true speech-to-speech model trained only on recordings of human conversation, with no text and no pretrained models. It is full-duplex, so it listens and talks at the same time, cuts in and backchannels naturally, runs faster than real time, and runs locally on a MacBook Pro M4 Max or better. Block says it was trained on a single NVIDIA GB200 NVL72 and learned language from hundreds of times fewer words than LLMs. There is no public API or weights yet; a small group of AI safety researchers is getting early access.

Zoom

On 2026-10-23 Artificial Analysis launched Coding Agent Index v2.0, which scores model-plus-harness combinations across 290 tasks with three equally weighted benchmarks: FrontierCode v1.1 from Cognition (100 tasks on real open-source repos, graded on whether a maintainer would merge the change) replaces DeepSWE v1.1, SWE-Atlas-QnA becomes the stricter SWE-Atlas-QnA-AA, and Terminal-Bench 4.0 is unchanged. Claude Code with Claude Opus 5.5 (max) leads at 61.7, ahead of Sonnet 5.5 at 59.3 and Muse Wonder Full at 58.9. Scores fall across the board: the 21 configurations measured on both versions drop from a mean of 54.8 to 47.4.

Zoom

Independent AI evaluation platform Artificial Analysis officially released HealthBench Professional alongside the length-normalized MLCR-AA index (@ArtificialAnlys). The benchmark revealed a pervasive industry blindspot: LLM-as-a-Judge evaluations suffer from acute 'verbosity bias', disproportionately rewarding longer generations regardless of medical conciseness. In raw HealthBench scoring where Anthropic outputs were 4–6x longer, Claude Opus 5.5 led at 71.4%. However, once length bias was scientifically normalized via MLCR-AA, GPT-6 Astra (max) tied Claude Sonnet 5.5 for #1, while Claude Opus 5.5 plummeted from #1 down to #6, setting a new rigorous standard for medical model evaluation.

Zoom