Tracked topic
Qwen3 is an AI model family developed by Alibaba, released as a set of large language models for natural-language tasks.
LocateAnything-3B, Qwen-AgentWorld-35B-A3B, and Qwen3.5-122B-A10B models now available on Amazon SageMaker JumpStart Posted on: Aug 11, 2026 NVIDIA's LocateAnything-3B, Qwen's Qwen-AgentWorld-35B-A3B, and Qwen's Qwen3.5-122B-A10B models are now available on Amazon SageMaker JumpStart, expanding the… …
… The website relies on Qwen 3.5 models for benchmarking: Qwen3.5-9B – Required Small device baseline Qwen3.5-27B – Required Mid-range device baseline Qwen3.5-35B-A3B MoE – Optional MoE performance reference Qwen3.5-122B-A10B MoE – Optional Large memory device reference Qwen3.5-397B-A17B MoE – Option… …
… Qwen 3.6, a new series of high-performance, open weight large language models LLMs from Alibaba, are ideal for running local agents like Hermes. …
… Figure 3: Qwen code deployment Step 1: Install node.js bash curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.39.7/install.sh | bash nvm install --lts nvm use --lts node -v npm -v Step 2: install Qwen code bash Install Qwen Code npm install -g @qwen-code/qwen-code@latest verify qwen --versio… …
… NVIDIA In-Game Inferencing Plugins & Model Support The NVIDIA In-Game Inferencing SDK provides plugin support for a number of different language and speech models including: NVIGI Plugin Supported Inference Hardware Supported Models Speech - ASR Local TRT CUDA-Enabled GPU Riva ASR Speech - TTS Loca… …
… Plugging Qwen into VS Code via the Continue extension is what made me realize how powerful local AI can be . …
… Typical VRAM Usage by Popular Models LLM DeepSeek R1 Distill Qwen 32B Q6 28GB Mistral Small 3.1 24B Instruct 2503 Q8 27GB Text to Image Flux.1 Schnell 24GB SD 3.5 Medium 17GB See endnote RPW-496 Massive Gains for Massive Models Up to 5× Faster with 32GB VRAM 100% 361% 437% 454% 447% 496% Phi 3.5 Mo… …
Hey locallama! We recently open sourced a Qwen3-TTS 1.7B implementation that achieves 10 requests per second (RPS) and sub-50 ms p95 time-to-first-audio (TTFA) while maintaining real-time playback on 1 x H100. This exten…
QwQ was genuine next-gen performance usable on local hardware, but the massive required context (it's reasoning style was akin to "if I say every possible word, I'll notice the right one!") kinda made it unusable for age…
Looking for V100 users to share your config and it's performance. GPU: Tesla V100 PCIE 32Gb Qwen3.6 27B Q4_K_M + Q8_0 MTP 128K context length Pi coding agent llama.cpp model preset: [*] spec-default = 1 ctx-size = 131072…
Qwen3.8-Max (2.4T) is another massive contribution to the open weight community. On benchmarks, it performs closely to Kimi K3 and DeepSeek V4 flash across all categories and is better at coding and software tasks. Qwen3…
Good afternoon, everyone! I wanted to show the work I've been doing around porting Ninfer over to the CMP170HX (Github) So, first, I do want to call out the amazing work that Neroued, Sergiuszm and specifically Don-Chad …
… A 0.6B Qwen3 interpreter executing PAW programs matches the performance of direct prompting of Qwen3-32B, while using roughly one fiftieth of the inference memory and running at 30 tokens/s on a MacBook M3. …
… Qwen 3.5 4B handles most of the routine work It supports tool calling and is small enough to run alongside Ollama I evaluated a bunch of local LLMs here, but ended up using Qwen 3.5 4B. …
… Running open models like the Gemma 4 family on NVIDIA GPUs achieves optimal performance because NVIDIA Tensor Cores accelerate AI inference workloads to deliver higher throughput and lower latency for local execution. …