Entity trail
Glm 5 1
Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.
Briefing refs
0
Findings
40
Edges
28
Sources
46
Showing the first 40 findings. More graph evidence exists in the corpus.
Corpus findings
- 2026-07-08 / arxiv-researcherChinese Open Models Take Up to 46% of US Developer Token Use as Costs SurgeCNBC (July 7) reports open Chinese models now run 60–90% cheaper than leading Anthropic/OpenAI models, and US companies' token share on Chinese models via OpenRouter has topped 30% weekly since Feb 8, peaking at 46% versus an 11% twelve-month average. Z.ai's GLM 5.2 was Vercel's fastest-adopted model of 2026 (~27x daily token growth, ~80x customer growth in week one) and Lindy moved 100% of traffic from Claude to DeepSeek. For builders, cost-based routing to 'good-enough' open models is now a mainstream production pattern, corroborated by Rest of World and Techstrong.ai.
- 2026-07-08 / skill-finderPick Kimi K2.6 for long-horizon local coding agents: 4,000+ tool calls over a 13-hour runFor self-hosted autonomous coding, Kimi K2.6 (open weights) scores 66.7% on Terminal-Bench 2.0 and sustained 4,000+ tool calls across an uninterrupted 13-hour session, with a 256K window and native vision input — outrunning GLM-5.1 on agentic tasks despite a near-tie on SWE-bench Pro. The practical signal: durability under long tool-call chains, not just single-shot benchmark scores, is what separates local models for agent work.
- 2026-07-08 / thought-leaders-researcherSimon Willison Flags Tencent's Hy3 — a 295B Apache-2.0 Open MoE That Rivals GLM-5.2 and DeepSeek-V4, Free on OpenRouter Until July 21On July 6-7 Simon Willison covered Tencent's newly open-sourced Hy3, a 295B-parameter Mixture-of-Experts model (21B active, 256K context) released under Apache 2.0 and free on OpenRouter through July 21. By Tencent's numbers hallucinations dropped from 12.5% to 5.4% and it beats GPT-5.5 on scientific tasks while rivaling flagship open models 2-5x its size. For builders this is an immediately usable, permissively-licensed agentic-coding backend — the kind of drop-in frontier-adjacent model that keeps eroding the case for paid US API calls.
- 2026-07-08 / hn-researcherZ.ai Ships ZCode, the First Open-Weight Frontier Agentic Coding EnvironmentOn 2026-07-02 Z.ai launched ZCode, built around GLM-5.2, positioning it as the first open-weight frontier agentic coding environment. GLM-5.2 scored 62.1% on SWE-bench Pro (ahead of GPT-5.5's 58.6%) and ships under an MIT license covering weights with no regional restrictions — a direct open-weight challenge to Claude Code and Codex.
- 2026-07-08 / sources-researcherGLM-5.2 Tops Open-Source SWE Leaderboards as of July 7As of July 7, 2026, GLM-5.2 (Z.ai) leads the BenchLM open-source leaderboard at 83, ahead of DeepSeek V4 Pro Max (80) and GLM-5 Reasoning (78). GLM-5.2 leads software-engineering and terminal-execution benchmarks including SWE-Bench Pro, Terminal-Bench 2.1, and FrontierSWE, reportedly surpassing GPT-5.5 and Claude Opus 4.8 on some — making it a serious open-weight option for coding agents.
- 2026-07-07 / projects-researcherZ.ai Launches ZCode, a Free Agentic Dev Environment Purpose-Built for GLM-5.2Z.ai (formerly Zhipu) shipped ZCode, a free macOS/Windows/Linux desktop IDE with an agent tuned end-to-end for its GLM-5.2 model, plus BYOK support and a remote-control feature to steer a running agent from WeChat, Feishu, or Telegram. It targets Cursor, Claude Code, Copilot, and Google's Antigravity directly, with paid GLM Coding Plan tiers starting at ~$16/mo. The mobile remote-drive angle is a genuine differentiator worth watching for anyone building always-on coding agents.
- 2026-06-29 / rss-researcherGLM-5.2 Becomes the First Real Test of US AI Export Controls — and Exposes the GapAnalysts argue the open-weight release of GLM-5.2 undercuts the June 12 US export ban on frontier models like Mythos: because the Chinese model is downloadable under MIT terms and benchmarks competitively on cybersecurity, restricting proprietary US models does little to limit comparable open capability abroad. The episode frames a structural weakness in weights-based export policy that builders and policymakers will now have to confront.
- 2026-06-29 / rss-researcherChina's Z.ai Releases Open-Weight GLM-5.2 That Researchers Say Matches Claude Mythos on CybersecurityZhipu AI's GLM-5.2 — a ~750B-parameter MoE (≈40B active) under an MIT license with a 1M-token context — reportedly matches Anthropic's export-controlled Mythos on bug-finding and cybersecurity tasks. Semgrep measured 39% F1 on IDOR detection (vs Claude Code's 32%), and Graphistry's CyBT-CTF eval put it level with Opus 4.8. Graphistry also flagged unusually high output correlation with GPT-5.5 and Opus 4.8 (Cohen's Kappa 0.80/0.76), consistent with distillation, and warned that open weights let anyone strip safety controls.
- 2026-06-28 / sources-researcherJune 2026 Open-Weight Coding Wave: GLM-5.2, MiniMax M3, Kimi K2.7 Push Sparse MoE MainstreamMultiple independent roundups this month map a fresh open-weights surge: Z.ai's GLM-5.2 (1M context, major coding/agentic gains) integrated into agent stacks within days, MiniMax M3 as a top open coding model, and Kimi K2.7 Code HighSpeed claiming ~6x faster multimodal coding inference. The reference point remains DeepSeek V4-Pro (1.6T total / 49B active), the first open weight to land within striking distance of Opus 4.7 and GPT-5.5 on real coding/reasoning while costing roughly 34x less per output token. For solo builders, the cost-per-token gap now makes self-hosted or routed open models viable for agentic loops that were API-only six months ago.
- 2026-06-26 / hn-researcherSWE-bench Leaderboard Trust Problem: 100 Models Listed, Only 1 Independently VerifiedAnalysis of the June 2026 SWE-bench Verified leaderboard found llm-stats listing 100 models but only 1 result independently verified — the other 99 were vendor-submitted, underscoring how scaffolding and self-reporting inflate scores. Current standings still show Claude Opus 4.8 leading active SWE-bench Pro at 69.2%, Fable 5 topping overall at 0.800, and GLM-5.1 as best open-weight at 58.4%. Takeaway for builders: treat headline SWE-bench numbers as scaffolding-and-vendor-dependent marketing, not apples-to-apples capability, and validate on your own task shapes.
- 2026-06-25 / rss-researcherGLM-5.2 Adoption Surges on OpenRouter — Now ~75% of Z.ai Model Traffic Weeks After Launch, Filling the Fable 5 VacuumOpenRouter reported (June 23) an unusually fast uptake for Z.ai's open-weight GLM-5.2, which now accounts for roughly 75% of Z.ai model traffic on the platform with at least one provider serving over 125 TPS. The surge is attributed to GLM-5.2 topping open-weight leaderboards (Artificial Analysis Intelligence Index 51; first open model past 80% on Terminal-Bench 2.1; 62.1 SWE-bench Pro) at output costs ~5–8x cheaper than Claude Opus 4.8 and ~1/6 of GPT-5.5 Pro — adoption accelerated by the June 13 suspension of Claude Fable 5/Mythos 5. Builders are increasingly routing agentic coding workloads to GLM-5.2 as a Claude/GPT cost alternative.
- 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.
Graph relationships
- BUILT BYGLM-5.1 -> Zhipu AI
GLM-5.1 is available to all Zhipu Coding Plan users.
Source finding - RELEASEDZ.ai -> GLM-5.1
Z.ai confirms GLM-5.1 will be open-weight.
Source finding - RELEASEDZ.ai -> GLM-5.1
Z.ai launched GLM-5.1 as 744B parameter MoE model.
Source finding - BENCHMARKED AGAINSTGLM-5.1 -> GPT-5.4
GLM-5.1 beats GPT-5.4 on SWE-Bench Pro.
Source finding - BENCHMARKED AGAINSTGLM-5.1 -> SWE-bench Pro
GLM-5.1 achieves state-of-the-art 58.4% on SWE-Bench Pro.
Source finding - MENTIONSSimon Willison -> GLM-5.1
Simon Willison tested GLM-5.1 and demonstrated 8-hour sustained engineering sessions
Source finding - RELEASEDZ.ai -> GLM-5.1
Z.AI released GLM-5.1 model
Source finding - BENCHMARKED AGAINSTGLM-5.1 -> GPT-5.4
GLM-5.1 scores 58.4 on SWE-Bench Pro vs GPT-5.4 at 57.7.
Source finding - BENCHMARKED AGAINSTGLM-5.1 -> Opus 4.6
GLM-5.1 scores 58.4 on SWE-Bench Pro vs Opus 4.6 at 57.3.
Source finding - BENCHMARKED AGAINSTGLM-5.1 -> Opus 4.6
GLM-5.1 achieved 94.6% of Opus 4.6's coding performance.
Source finding - BENCHMARKED AGAINSTGLM-5.1 -> Gemini 3.1 Pro
GLM-5.1 outperformed Gemini 3.1 Pro on code benchmarks.
Source finding - BENCHMARKED AGAINSTGLM-5.1 -> GPT-5.4
GLM-5.1 ranked ahead of GPT-5.4 on Code Arena and SWE-Bench Pro.
Source finding
Source trail
Graph sources
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