Entity trail

Qwen3 5 122B A10B

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

Briefing refs

Findings

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Sources

Corpus findings

2026-05-12 / reddit-researcherDGX Cooled with Tap Water Runs Qwen3.5-122b-A10B at 18.77 Tokens/Second with 80K ContextA r/LocalLLaMA user shared their unconventional DGX cooling solution using tap water, keeping GPU temperatures below 68°C at 95% utilization. The setup runs Qwen3.5-122b-A10B at Q6_K precision with 110GB memory usage, achieving 18.77 tokens/second for continuous inference at 80K context. The 388-upvote post highlights the creative hardware hacking culture in the local AI community.
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.
2026-03-22 / reddit-researcherQwen3.5-122B-A10B Uncensored Aggressive GGUF: Full Refusal Removal on Flagship MoEThe community released Qwen3.5-122B-A10B 'Aggressive' as GGUF — the largest Qwen3.5 MoE with all safety filters completely stripped while preserving the original personality without alteration. The 256-upvote post with 93 comments signals strong practitioner demand for uncensored frontier-scale local models, distinct from earlier Qwen uncensored releases that applied subtler modifications. This makes the 122B flagship effectively unrestricted for local deployment.
2026-03-16 / reddit-researcherQwen3.5-122B-A10B Called 'Shocking' — 10B Active Params Beats GPT-5 Mini on Tool Calling by 30%The Qwen3.5-122B-A10B MoE model (only 10B active parameters at inference) is generating community buzz for its BFCL-V4 function/tool-calling score of 72.2, beating GPT-5 mini's 55.5 by ~30%. SWE-bench Verified hits 72.4%. At 10B active parameters this model runs on consumer hardware while delivering near-frontier agentic coding performance — a qualitative threshold shift for local deployments.

Graph relationships

BENCHMARKED AGAINST
Qwen3.5-122B-A10B -> GPT-5-mini
Qwen3.5-122B-A10B beats GPT-5 mini on tool calling by 30%
Source finding

Source trail

r/LocalLLaMA r/LocalLLaMA r/LocalLLaMA r/LocalLLaMA via Artificial Analysis

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