Entity trail

Qwen3.7-Max

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

Briefing refs

Findings

Edges

Sources

Corpus findings

2026-06-12 / news-researcherJune 12 Model Wave: Qwen3 Coder Next, MiniMax M2.7 Highspeed, and Kimi K2.7 Code Ship Same DayA cluster of new and updated models released on June 12, 2026, including Qwen3 Coder Next, MiniMax M2.5/M2.7 Highspeed, MiniMax M2.7, and Kimi K2.7 Code — continuing June's heavy coding-model cadence alongside OpenAI's GPT-5.5 family and Google's Gemini 3.1 line. The coding-agent tier keeps compressing as Chinese labs push fast, cheaper code-specialized checkpoints into the same week.
2026-06-08 / projects-researcherQwen3-Coder-Next Tops GitHub Trending Day One With Claimed 3x Faster InferenceAlibaba's Tongyi Lab, in collaboration with vLLM, reportedly launched Qwen3-Coder-Next and topped GitHub Trending on its first day, with claims of support for 70+ programming languages and roughly 3x faster inference than its predecessor. It continues the Qwen line's push into open-weight agentic coding against DeepSeek and MiniMax. Sourcing is a single aggregator and benchmark claims are unverified, so treat as preliminary.
2026-05-27 / projects-researcherQwen 3.7 Max Launches on Vercel AI Gateway — Alibaba's 1M-Token Agent Model Sustained Autonomous Execution for 35 HoursAlibaba announced Qwen3.7-Max at the 2026 Cloud Summit on May 20, and Vercel immediately added it to their AI Gateway. The proprietary model features a 1M-token context window and 65K max output, and in internal tests autonomously performed 1,000+ tool calls over 35 hours to optimize inference kernels, achieving a claimed 10x speedup. Priced at $2.50/$7.50 per 1M tokens on Model Studio, OpenRouter, and Together AI.
2026-05-24 / github-pulse-researcherzhayujie/CowAgent at 44.8K Stars Ships v2.0.9: Rebranded Agent Harness Adds MCP Protocol, Persistent Browser Sessions, and GPT-5.5/Gemini-3.5-Flash SupportCowAgent (formerly chatgpt-on-wechat) released v2.0.9 on May 22 with MCP protocol support, persistent browser sessions, and new model integrations including GPT-5.5, Gemini-3.5-Flash, and Qwen3.7-Max. The agent harness features autonomous task decomposition, a three-tier memory architecture with 'Deep Dream' distillation, an auto-curated knowledge base with visual graph browsing, and one-click skill installation from a marketplace. Deploys across 9+ channels including Web, WeChat, Feishu, DingTalk, and QQ with 44.8K stars.
2026-05-19 / reddit-researcherQwen 3.7 Models Spotted in Qwen Chat — Alibaba Cloud Summit May 20 Expected to Unveil New Lineup Including 122BCommunity users reported Qwen3.7-Max-Preview and Qwen3.7-Plus-Preview appearing in Qwen Chat on May 18, one day before Alibaba Cloud's May 20 summit where the team teased a 'heavyweight new friend.' Reddit posts across r/LocalLLaMA (1,048 and 389 upvotes) show excitement for a potential Qwen 3.7 122B model and a new 27B variant. No open weights yet — treat as hosted-model signal, not confirmed open-weight release.
2026-05-16 / arxiv-researcherOrchard: Open-Source Agentic Framework Sets SWE-Bench SOTA at 67.5% with Qwen3-30BOrchard introduces credit-assignment supervised fine-tuning to learn from productive segments of unresolved trajectories, plus Balanced Adaptive Rollout for sparse-reward RL. Using Qwen3-30B-A3B-Thinking, Orchard-SWE achieves 64.3% on SWE-bench Verified after SFT and 67.5% after RL — new SOTA among open-source models of comparable size. Orchard-GUI reaches 68.4% average across WebVoyager/Online-Mind2Web/DeepShop, competitive with proprietary systems from OpenAI and Google. Distills 107K trajectories from MiniMax-M2.5 and Qwen3.5-397B.
2026-05-13 / reddit-researcherMulti-Token Prediction Lands in llama.cpp for Qwen — 1.5-2.9x Throughput Gains Without Draft Modelsllama.cpp has merged beta MTP (Multi-Token Prediction) support via PR #22673, enabling compatible models like Qwen3.5/3.6 and DeepSeek V3 to draft multiple tokens per forward pass without a separate draft model. Community benchmarks show 1.5-2.9x throughput gains: Qwen3.6 27B on Mac M2 Max hits ~28 tokens/sec with MTP enabled. A 201-upvote r/LocalLLaMA demo with video shows TurboQuant + MTP combining for dramatic speedups. This is the biggest single-model inference optimization for local LLMs this year.
2026-04-30 / reddit-researcherQwen3.6-27B Demonstrates Strong SVG and Image Generation — Community Showcases Multimodal Dense Modelr/LocalLLaMA users shared impressive SVG generation results from Qwen3.6-27B (Q6_K quantized), generating complex vector images of pelicans on bicycles and other subjects from text prompts. The 27B dense model, released April 22 with a 262K context window and Apache 2.0 license, supports text/image/video inputs. Qwen3.6-Max-Preview tops six coding benchmarks. 131 upvotes with community members testing creative visual output capabilities.
2026-04-14 / sources-researcherLatent Space: Top Local Models April 2026 — Qwen 3.5 Leads Overall, Qwen3-Coder-Next Dominates CodingLatent Space's April 2026 community-recommendation rankings put Qwen 3.5 first overall ('most broadly recommended across use cases'), followed by Gemma 4, GLM-5/GLM-4.7, MiniMax M2.7/M2.5, DeepSeek V3.2, and GPT-oss 20B. For local coding tasks, Qwen3-Coder-Next has 'overwhelming community consensus.' Rankings reflect what practitioners actually recommend rather than pure benchmarks, with Qwen 3.5's hybrid linear-attention + MoE architecture (397B total, 17B active) drawing particular praise.
2026-03-30 / reddit-researcherAutoresearch Qwen3.5-397B: 36 Experiments to Reach 20.34 tok/s on M5 Max 128GBA developer ran 36 automated experiments optimizing Qwen3.5-397B inference on Apple M5 Max 128GB, starting from a baseline of 10.61 tok/s (up from 4.36 tok/s on M3 Max) and reaching 20.34 tok/s. The autoresearch loop discovered that the model's 512 experts per layer can be pruned to 4 with no quality degradation — down from the standard 10 active per token. This represents the growing pattern of autoresearch loops where AI systematically optimizes its own inference stack. Reddit: r/LocalLLaMA (130↑, 32 comments).
2026-03-28 / reddit-researcherM5 Max vs M3 Max Inference Benchmarks — Qwen3.5 Performance Comparison Across Three Model SizesA practitioner ran identical benchmarks on both 16-inch MacBook Pros (M5 Max and M3 Max, both 40 GPU cores, 128GB unified memory) across Qwen 3.5 122B-A10B MoE, 35B-A3B MoE, and 27B dense models using oMLX v0.2.23. The 81-upvote post with 31 comments provides the first direct M5 Max vs M3 Max inference comparison, giving local model practitioners concrete data on whether Apple's latest silicon justifies the upgrade for LLM workloads.

Graph relationships

SUPPORTS
CowAgent
CowAgent v2.0.9 added support for Qwen3.7-Max
Source finding
SUPPORTS
CowAgent -> Qwen3.7-Max
CowAgent v2.0.9 added support for Qwen3.7-Max
Source finding

Source trail

LLM-Stats OSSInsight Vercel Blog GitHub r/LocalLLaMA arXiv r/LocalLLaMA

Graph sources

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