AI news daily: what changed on October 25, 2026

1. A 4B coding model that can generate 3D scenes

A user shared an early 4B parameter model trained for coding tasks and 3D scene generation. The model is an independent fine-tune of Qwen3.5-4B and includes Q4_K_M and Q8_0 GGUF formats. Results demonstrating 3D scene generation were shown in a video, with the user noting improved performance over smaller models. The model is available for download on Hugging Face, though training is still ongoing. The creator plans to update the model after training completes and release the training dataset for community use. No specific benchmarks or performance metrics were provided. The post invites others to test the model and share results.

Source: Reddit r/LocalLLaMA

2. [Benchmark] Strata/Basalt runs Qwen3.8 Flash Next IQ3_S with 16GB VRAM and 55GB RAM with up to 250 tok/s

A benchmark test evaluated Qwen3.8-Flash-Next IQ3_S on Basalt hardware. The system used an RTX 5080 with 16 GB VRAM, a Core Ultra 9 285K processor, and 62 GB DDR5-6800 RAM. It handled up to 262,000 context tokens with an int8 KV workload. During agent coding sessions, it processed 103 requests with a peak throughput of 5,118 tokens per second. Context sweeps tested prompts ranging from 15,000 to 207,000 tokens, achieving 5,662 tokens per second at peak. The system used 15.7 GB VRAM and 54.1 GB RAM during tests. Median time to first token was 0.2 seconds, with 99.5% of prompt tokens cached. Results included per-request averages for generated tokens and specific performance metrics.

Source: Reddit r/LocalLLaMA

3. Too good to be true? ISTA's GSQ-RCO 2-bit DeepSeek-V4.1-Flash scoring the same as the base model

A Reddit user questions the performance of ISTA's GSQ-RCO GGUF models for DeepSeek-V4.1-Flash, asking if their quality matches claimed benchmarks. The user notes that IQ2_XXS scores reportedly match the base model, but benchmarks show saturated results (90%+ accuracy, AIME25 at 100 for all versions). They cannot find KLD or PPL metrics for GSQ-RCO models and inquire about expected KLD at ~2 bpw. The post references a Hugging Face repository for the model and acknowledges translation assistance via an LLM. The user seeks confirmation if degradation is hidden due to benchmark limitations. No official claims or data about model performance are provided in the source. The discussion focuses on verifying reported results through independent measurements.

Source: Reddit r/LocalLLaMA

4. Artificial Analysis Index is non-representative of real-world performance. Tested Kimi 3.1 Pro through

A user tested Kimi 3.1 Pro, ranked #4 on the Artificial Analysis Index (AAI), and found its real-world performance significantly worse than DeepSeek 4.1 Flash. The AAI was criticized as easy to manipulate, with Kimi 3.1 Pro failing in practical tasks. The comparison highlights discrepancies between AAI scores and actual model effectiveness. No specific metrics were provided for Kimi 3.1 Pro's performance. The user suggests the AAI may not reflect real-world capabilities. DeepSeek 4.1 Flash outperformed Kimi 3.1 Pro in tested scenarios. The findings question the reliability of the AAI as a performance benchmark.

Source: Reddit r/LocalLLaMA

5. OpenAI and Anthropic blocked the reverse engineering of smart TVs spying on us

OpenAI and Anthropic blocked the reverse engineering of smart TVs, according to a Reddit post. The action targeted REA (Reserve Engineer Anything), a project linked to analyzing smart TV systems. The block occurred one day after the project was shared on Reddit by user /u/kroggens. The post referenced a Twitter thread by AbhinavXJ discussing the effort. No specific details about the technical methods or outcomes were provided. The move suggests companies are restricting unauthorized analysis of their devices. The significance remains unclear without further information. The Reddit thread includes a link to the original discussion.

Source: Reddit r/LocalLLaMA

6. model: DSV4.1 flash by am17an - Pull Request #31086 - ggml-org/llama.cpp

A model named DeepSeek-V4.1-Flash was shared on Hugging Face with 763B parameters. The model is part of the DeepSeek series developed by DeepSeek-AI. Technical details are outlined in a report linked on the Hugging Face page. The model's release was posted on Reddit's r/LocalLLaMA by user /u/jacek2023. No specific capabilities or performance metrics were mentioned in the summary. The model's size indicates it is a large-scale language model. The release includes a technical report for further information. The post includes links to the Hugging Face repository and the report.

Source: Reddit r/LocalLLaMA

7. Is it just me or Kimi K3.1 Pro don't look much better than DeepSeek 4.1 Flash?

A Reddit user compared Kimi K3.1 Pro and DeepSeek 4.1 Flash 1017 models, noting Kimi K3.1 Pro's 2.8b parameters but criticizing its performance. The user stated Kimi K3.1 Pro requires 104 active layers per token, making it slow and hard to run locally even when quantized. DeepSeek 4.1 Flash 1017 achieved similar results with a smaller footprint and faster processing. The user questioned whether Kimi K3.1 Pro's improvements over DeepSeek 1017 were significant. They recommended using DeepSeek 4.1 Flash 1017 instead of Kimi K3.1 Pro, which will be released on November

Source: Reddit r/LocalLLaMA

8. UK to invest 100m in 'world first' AI Biosecurity Lab

The UK government announced a 100 million investment to establish an AI Biosecurity Lab. The facility is described as the "world first" of its kind, focusing on AI applications for biosecurity. The lab aims to develop tools for monitoring biological threats and improving public health responses. Specific details about the lab's operations or timelines were not provided. The initiative highlights the government's emphasis on AI-driven solutions for global health challenges. No further technical specifications or partner organizations were mentioned. The funding is part of broader efforts to enhance biosecurity measures using artificial intelligence.

Source: Reddit r/LocalLLaMA

9. CMP170HX inspiration unlocks 30x/40x also, up to 2X Prefill speedup --> NVIDIA RTX 30 & RTX 40 GPUs Get

CMP170HX inspiration unlocks 30x/40x also, up to 2X Prefill speedup --> NVIDIA RTX 30 & RTX 40 GPUs Get was reported by Reddit r/LocalLLaMA. See the original report for details.

Source: Reddit r/LocalLLaMA

10. Blue Planet III is keeping the rough edges in the age of AI

BBC's Blue Planet III is emphasizing authenticity by retaining imperfect footage rather than polishing it. Previous seasons of the nature series were known for high-quality, seamless visuals that appeared overly refined. The show's creators aim to avoid AI detection by preserving raw, unedited shots. This approach contrasts with earlier efforts to present idealized imagery. The decision highlights concerns about AI-generated content appearing too flawless. No specific technical details about AI tools were provided. The series is part of BBC's ongoing nature programming. The strategy reflects broader industry discussions about distinguishing real footage from AI-enhanced material.

Source: The Verge AI