Qwen 3.5-122B
PulseAugur coverage of Qwen 3.5-122B — every cluster mentioning Qwen 3.5-122B across labs, papers, and developer communities, ranked by signal.
3 day(s) with sentiment data
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GPT-OSS model celebrates one year, praised as top local LLM
The open-source model gpt-oss has reached its one-year anniversary, with users praising its 20B and 120B versions as top-tier local models. While Qwen 3.5 122B is considered its main competitor, gpt-oss is noted for its…
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LLM choices explode for DGX Spark, users compare Qwen 3.5 and anticipate Ling 3.0
The r/LocalLLaMA community is discussing a rapidly expanding landscape of large language models suitable for DGX Spark hardware. Users are comparing current models like Qwen 3.5 122B, Laguna 2.1, Deepseek v4, and Inklin…
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LLM Stability Varies Wildly: Qwen 3.5 122B Outperforms GPT-5.5, Opus, Gemini
A recent discussion on LessWrong highlights the significant differences in the stability and reliability of various large language models when left to run unattended for extended periods. Models like Anthropic's Opus an…
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User seeks help tuning llama-server cache for large models
A user on Reddit is seeking assistance with optimizing the cache settings for llama-server, particularly when running large models like Qwen 3.5 122B. They are experiencing significant processing time (10-20 minutes) du…
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Debate erupts over MoE model effectiveness vs. dense models
The effectiveness of Mixture-of-Experts (MoE) models is being questioned, with some arguing that their active parameters are not comparable to dense models of similar size. This perspective suggests that if a large MoE …
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Qwen 3.6 27B model struggles with agentic tasks, user reports
A user on Reddit's r/LocalLLaMA forum has reported significant issues with the Qwen 3.6 27B model when performing agentic tasks. While the model excels at generating impressive single prompts and longer content compared…
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Hardware query for running Qwen 3.5 122B MoE model
A user on Reddit's r/LocalLLaMA community is inquiring about the hardware requirements for running a large mixture of experts (MoE) model, specifically Qwen 3.5 122B. The user is asking for practical results or experien…
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LLM Pricing Fluctuates: NVIDIA, Qwen, and Z.ai See Changes; New Models Added · 10 sources tracked
The Token Ledger has released daily updates on LLM pricing changes throughout early August 2026. Several models saw price adjustments, including NVIDIA Nemotron 3 Super and Ultra, Qwen variants, and Z.ai's GLM 5.2, with…
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Mimo 2.5 excels at large context tasks on consumer GPUs
The Mimo 2.5 large language model demonstrates impressive speed and performance with large context windows, particularly on dual RTX Pro 6000 GPUs. This is attributed to its efficient 5-to-1 local/global sliding-window …
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LLM community calls for urgent release of 80-160B parameter models
Users on the r/LocalLLaMA subreddit are expressing a strong need for new large language models (LLMs) in the 80-160 billion parameter range. Current models are either too small for users with high-capacity but slower un…
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User seeks to prevent llama.cpp from swapping KV cache
A user on Reddit's r/LocalLLaMA subreddit is seeking advice on how to prevent the llama.cpp software from offloading its KV cache to swap memory. Despite using specific flags, the user experiences offloading when RAM us…
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User returns Asus Spark AI hardware citing cost and performance
A user returned their Asus Spark AI hardware due to its high cost and disappointing performance, particularly with larger models. They cited limited memory bandwidth as a key issue, hindering its ability to run models e…
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Qwen 3.5 122B leads local VLMs in detecting AI-generated hand errors
A user tested four local Visual Language Models (VLMs) to determine their effectiveness in detecting poorly generated hands in AI images. Qwen 3.5 122B emerged as the best performer, offering 100% precision with a decen…
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Windows vs. Linux: No Speed Difference for llama.cpp MoE Models
A user tested the performance of llama.cpp on Windows 11 and Linux, finding no significant speed difference for medium to large Mixture of Experts (MoE) models. The tests involved specific hardware configurations and de…
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LLMs possess shared internal 'preference vector' across personas
Researchers have identified a shared internal 'preference vector' within large language models that influences their behavior across different personas. By training probes on activation data from Gemma-3-27B and Qwen-3.…