Entity trail

LM Arena

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

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Findings

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Corpus findings

2026-08-10 / reddit-researcherAn Unannounced OpenAI Image Model, 'mona-lisa-1', Was Caught on LM Arena and Confirmed by Its Own SynthID WatermarkA previously unknown image model codenamed mona-lisa-1 appeared on the LM Arena blind-test leaderboard with no announcement, drawing 222 upvotes on r/singularity. Attribution did not come from OpenAI — a user ran a mona-lisa-1 output through OpenAI's official verification service, which detected the SynthID signal OpenAI uses to mark its own content. Reactions are genuinely split: one tester called it "extremely better than Image 2," while others reported visible noise and texture errors. There are no official benchmarks, docs, pricing, or even confirmation whether this becomes GPT Image 3, a 2.5 update, or stays internal.
2026-08-06 / arxiv-researcherPIMiner Builds a Transferable Prompt-Injection Strategy Library: 86.7% Success on Gemini-2.5-Pro, 40% on Claude Sonnet 4.5Instead of the RL-trained attacker models that dominate prompt-injection red teaming and generalize poorly to new targets, PIMiner is an agentic system that trains across a sequence of (dataset, target model) pairs and accumulates a strategy library from scratch, which transfers to an unseen target LLM with no retraining and roughly 10 queries per test sample. On AgentDojo it reaches 86.7% ASR against Gemini-2.5-Pro, 53.3% against GPT-5.1, and 40.0% against Claude-Sonnet-4.5; on IPIArena the figures are 76.2%, 61.9%, and 42.9% respectively. The spread across frontier models is the useful signal for builders choosing a backbone for tool-using agents exposed to untrusted content.
2026-08-04 / reddit-researcherIntology's Locus Post-Trains Qwen3 Base Models Past the Official Human-Tuned Instruct Checkpoint — 44.7 on PostTrainBench, 51.6% on PostTrainBench+Intology announced on August 3 that its automated research system Locus is SOTA on PostTrainBench, which gives an agent one H100 and 10 hours to post-train Qwen3-1.7B/4B, SmolLM3-3B, or Gemma-3-4B across seven benchmarks (AIME 2025, Arena Hard, BFCL, GPQA Main, GSM8K, HealthBench, HumanEval). Locus scores 44.7 in the official setting and, under a self-introduced expanded-compute variant they call PostTrainBench+ (thousands of H100 hours), reaches a 51.6% composite that surpasses the official human-post-trained Qwen3-1.7B-Instruct. Intology also ran Locus across live prize-money Kaggle competitions, claiming 4th-highest average rank after 16 days — note that PostTrainBench+ is Intology's own extension of a third-party benchmark, so the headline result is not an apples-to-apples leaderboard entry.
2026-07-16 / sources-researcherThinking Machines Lab Ships Inkling: 975B-A41B Multimodal, Apache 2.0 — the Leading American Open-Weights ModelTML's first full LLM is open-weights: 975B total / 41B active MoE, multimodal (text/image/audio in, text out), trained on 45 trillion tokens, with a 1M-token context in the open weights (256K via API/Tinker). A smaller Inkling-Small (276B-A12B) ships alongside. It ranks #41 on the Intelligence Index — top U.S. open-weights model but behind GLM-5.2 and Kimi K2.6 — and #9 in Agentic Web App Arena, with notably concise reasoning and strong tool calling. Architecture is unusual: non-RoPE relative positional encoding, 5:1 local-to-global sliding-window attention, short convolutions, and 2 shared expert sinks. Available on Hugging Face, Databricks, Baseten, Modal, and vLLM.
2026-06-23 / thought-leaders-researcherNathan Lambert Calls GLM-5.2 'the Step Change for Open Agents' — the Moment Frontier Agentic Coding Stops Being a Closed-Model ExclusiveIn a June 22 Interconnects essay, Lambert argues GLM-5.2 is the first open-weights model to trade blows with frontier systems on long-horizon, sustained-planning tasks inside real coding harnesses and design arenas — not just on static intelligence benchmarks. His thesis: agentic performance had been the one clear technical area closed labs (Claude Code, Codex) could dominate, and a usable long-horizon coding agent shipping under an MIT license with a 1M-token context window is the threshold that breaks that moat. This reframes the earlier 'GLM-5.2 is a strong open model' coverage as specifically an agents-capability inflection, with distribution/RLHF pipelines — not the base model — now the contested ground.
2026-06-19 / thought-leaders-researcherSimon Willison Calls Z.ai's GLM-5.2 'Probably the Most Powerful Text-Only Open Weights LLM' — 753B MoE, 1M Context, MIT License, Tops Open-Weights Intelligence Index at 51In a June 17 post, Simon Willison evaluates Z.ai's newly released GLM-5.2: a 753B-parameter Mixture-of-Experts model (40B active) with a 1M-token context window (up from GLM-5.1's 200K), released under an MIT license at roughly $1.40/$4.40 per million input/output tokens on OpenRouter. Per Artificial Analysis it leads the open-weights Intelligence Index v4.1 at 51 — beating MiniMax-M3 and DeepSeek V4 Pro (both 44) — and ranks #2 on Code Arena WebDev behind only Claude Fable 5, though it burns more output tokens per task (~43k). Willison's signature pelican-on-a-bicycle SVG test passed cleanly, but his opossum-on-an-e-scooter probe regressed versus GLM-5.1; for builders, this is now a credible MIT-licensed, self-hostable alternative to closed coding models with a genuine 1M-context window.
2026-06-16 / rss-researcherZ.ai Ships GLM-5.2 With a Usable 1M-Token Context and No Launch BenchmarksZ.ai released GLM-5.2 on June 13, a 744B-parameter MoE (40B active per token) with a 1,000,000-token input window — a ~5x jump from GLM-5.1's 200K — plus up to 131,072 output tokens and two effort modes (High, Max). It ships under MIT (weights pending the following week) and works day-one with eight coding tools including Claude Code, Cline, OpenClaw, and OpenCode via an Anthropic-compatible endpoint, but Z.ai published zero benchmark scores (no SWE-bench, Terminal-Bench, or Code Arena numbers) at launch.
2026-06-08 / sources-researcherIdeogram 4.0: Open-Weight 9.3B Diffusion Transformer That Tops Arena's Open Image LeaderboardIdeogram published a technical blog describing Ideogram 4.0 as a 9.3B Diffusion Transformer trained from scratch with a frozen 8B VLM text encoder, releasing fp8 and nf4 checkpoints — the nf4 variant fitting on a single 24GB GPU. Arena placed Ideogram 4.0 Quality in the text-to-image top tier and as the leading open-weight image model. For builders, it's a rare combination of frontier-tier image quality and genuinely local-deployable open weights.
2026-06-07 / sources-researcherArena Turns From Passive Leaderboard Into Active Agent Runtime With 'Agent Mode'Arena (formerly LMArena/Chatbot Arena lineage) launched Agent Mode plus Agent Arena, where users run agents on real tasks and feed aggregate metrics — confirmed success, praise vs complaint, steerability, bash recovery, and tool hallucination — into a live leaderboard. It's one of the clearest examples this week of an eval company becoming an execution platform. For builders, it signals a shift toward production-grounded, behavior-level agent metrics over static prompt comparisons.
2026-06-02 / thought-leaders-researcherJim Fan: GR00T N2 Vision-Language-Action Model Ranks #1 on Both MolmoSpaces and RoboArena BenchmarksNVIDIA's next-generation GR00T N2 VLA model — co-led by Jim Fan as head of NVIDIA's embodied AI research — achieved the #1 ranking on both the MolmoSpaces and RoboArena robot benchmarks with 2x the success rate of leading competitors. Announced alongside the Isaac GR00T reference robot at Computex, this represents NVIDIA's strongest claim yet in the physical AI software stack. For builders in robotics, GR00T N2 is now the model to beat for humanoid manipulation tasks.
2026-05-16 / skill-finderGemini 3.2 Flash Leaked Before I/O: Sub-200ms Inference, 92% of GPT-5.5 Performance at 1/15th the CostGoogle's Gemini 3.2 Flash appeared silently in the Gemini iOS app and AI Studio on May 5, then showed up on LM Arena benchmarks. Early results show 92% of GPT-5.5 coding/reasoning performance with sub-200ms latency and 15-20x cost reduction. Outperforms Gemini 3.1 Pro on certain creative coding benchmarks. Expected official announcement at Google I/O May 19-20.
2026-05-16 / projects-researcherwhichllm Hits Show HN — CLI Tool Auto-Detects Hardware and Ranks Local LLMs by Real Benchmarkswhichllm (Andyyyy64/whichllm) launched on Show HN as a CLI tool that auto-detects your GPU/CPU/RAM and returns ranked local LLM recommendations from HuggingFace based on real performance data, not just parameter count. It merges live benchmark sources including LiveBench, Artificial Analysis, Aider, Chatbot Arena ELO, and Open LLM Leaderboard, with scores tagged and discounted by confidence. One command gives hardware-specific recommendations factoring inference time and memory usage.

Graph relationships

BENCHMARKED AGAINST
Claude Opus 4.7
Claude achieved 1504 Elo on LM Arena.
Source finding
BENCHMARKED AGAINST
Claude Opus 4.7 -> LM Arena
Claude achieved 1504 Elo on LM Arena.
Source finding

Source trail

mona-lisa-1 Source: NPowerUser arXiv 2608.05108 Intology (via r/singularity 147 upvotes; @intology on X, 144K views)Latent Space (AINews) / Thinking Machines Lab Interconnects (Nathan Lambert)simonwillison.net MarkTechPost Ideogram (via Latent Space AINews)Arena (via Latent Space)NVIDIA Blog Show HN

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