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Qwen3 is an AI model family developed by Alibaba, released as a set of large language models for natural-language tasks.
…Across five GUI-grounding benchmarks and multiple Qwen backbones , VISTA consistently improves grounding accuracy. On ScreenSpot-Pro , it raises Qwen3-VL 4B/8B/30B-A3B from 55.5/52.7/53.7…
…Generated by Qwen/Qwen2.5-Coder-32B-Instruct Memory benchmarks for LLM agents largely assume single-user settings, leaving shared assistants for hospitals, workplaces, campuses, and households understudied. In these deployments, multiple…
…Generated by Qwen/Qwen2.5-Coder-32B-Instruct Enterprise agents increasingly operate inside workspaces: they read heterogeneous files, invoke tools, and deliver business artifacts. We introduce EnterpriseClawBench, an enterprise agent benchmark constructed…
…Alibaba claims the machine’s single-core general-purpose performance “exceeded 70 points in the SPECint 2006 benchmark test.” Photos from Tuesday event at which Alibaba announced the chip suggest its SPECInt…
Alibaba previewed Qwen3.8-Max this week. The claim: a 2.4T-parameter multimodal model that's second only to Anthropic's Fable 5. The pricing is what makes it interesting. - Fable 5: $10 in / $50 out per M tokens - Qwen3.…
I know why Qwen3.8 27B shipped with xhigh reasoning as default, it's to do its best in benchmarks. Models from top labs often get benchmarked at multiple reasoning levels, but that same treatment doesn't apply to other l…
submitted by /u/anderspitman to r/LocalLLaMA [link] [comments]
https://preview.redd.it/uvdb7g4o7djh1.png?width=1600&format=png&auto=webp&s=1db6176144bcf8f40efb15cc04e8370ad52bfe2f https://preview.redd.it/rj4l66eq7djh1.png?width=1257&format=png&auto=webp&s=692b5f76c96e5910fff22ebf576…
Just came across this coding benchmark: SciCode Artificialanalysis.ai reports a ranking which contradicts the feeling we've towards those models in real life coding. Is Gemma 4 really that good, or a benchmarking issue? …
…Distill-Qwen-14B by an average of 3.1 points (from 48.2 to 51.3) and boosts Qwen3-14B performance from 58.8 to 61.1 on six benchmarks, which are…
…Long-Horizon Terminal Bench, while agentic PPO lifts Qwen3.5-27B to 49.44%, 32.00%, and 22.07% on the three benchmarks, corresponding to relative gains of 20.0%, 41.2…
…Across math, coding, and chat benchmarks on dense and MoE Qwen3 models, JetSpec consistently outperforms bidirectional-head and tree-based SD baselines. On H100 GPUs, JetSpec achieves up to 9.64x speedup…
…WorldLines benchmark evaluates long-term memory in embodied agents through household scenarios, while ObsMem framework addresses challenges in partial observability and memory translation for decision-making. Generated by Qwen/Qwen2.5-Coder…
…Generated by Qwen/Qwen2.5-Coder-32B-Instruct We introduce the Massive Video Embedding Benchmark (MVEB), a 23-task benchmark for video embeddings spanning classification, zero-shot classification , clustering, pair classification, retrieval…
…Across three 7-8B instruction-tuned models (Qwen2.5, Qwen3, OLMo-3), SCOPE improves open-ended performance by up to +10.4 points on eight benchmarks and matches or exceeds GRPO_data…