@xueyu1125: Running local large models requires at least 50 tokens/s for usability. Here are API output speeds for top models (Gemini Flash 300+) DeepSeek V4 Flash: 99.5 tokens/s GPT-5.6 Sol: 68.1 to…
Summary
Discusses the token speed requirements for running local large models and compares API output speeds of multiple top AI models.
View Cached Full Text
Cached at: 08/18/26, 06:37 PM
For running local large models to be usable, they need to hit at least around 50 tokens per second 🤣
Here’s a reference for the output speeds of top-tier model APIs (Gemini Flash hits 300+): DeepSeek V4 Flash: 99.5 tokens/s GPT-5.6 Sol: 68.1 tokens/s Grok 4.6: 56.5 tokens/s Claude Opus 4.8 by Anthropic: 54.4 tokens/s https://t.co/WY50yLUEuz
Similar Articles
@aehyok: Share an open-source project FreeToken, a local inference engine specifically for running ultra-large Mixture-of-Experts (MoE) models on consumer-grade computers. Qwen3.6 35B → 8GB RTX 4060 laptop @ 39 tok/s DeepSeek-V4-Flash 284B → R…
FreeToken is an open-source local inference engine designed to run large Mixture-of-Experts (MoE) models on consumer-grade computers, offering significantly faster performance than alternatives like Ollama with easy installation and native GUI.
@berryxia: Damn, even my eyes can't keep up with this speed! Daniel Han, founder of UnslothAI, YC S24, previously at NVIDIA doing ML, just released the experimental MTP GGUF of Qwen3.6. The 27B model hits 140 tokens/s on a single GPU. 35B-A...
UnslothAI founder Daniel Han released the experimental MTP GGUF version of Qwen3.6, achieving 140 tokens/s for the 27B model and 220 tokens/s for the 35B-A3B version on consumer GPUs — a 1.4x speedup with zero accuracy loss.
@nicebabycat: https://x.com/nicebabycat/status/2091726637155103126
This article provides a detailed test of the local deployment and performance of the Ling-3.0-tiny model on an Apple M5 chip Mac, demonstrating the feasibility of running a 7.9B parameter model at 47 tokens per second without a discrete GPU.
@RookieRicardoR: Domestic models break through again, matching top models like Claude 4.6 and Gemini 3.1 Pro. Just tested Qwen3.7-Max, sharing some real thoughts. Last night I topped up as soon as the API went live and chose three tasks (see video) to test Qwen3.7-Max's frontend capabilities…
The user tested Qwen3.7-Max and believes it matches top models like Claude 4.6 and Gemini 3.1 Pro in frontend, computing power, and Agent capabilities. Its reasoning ability has significantly improved, and with monthly iteration speed, it has become a first-tier domestic model.
@svpino: DeepSeek-V4-Flash running at 5.71 token/s on a Mac M5 Pro. Every day, we get better models running on consumer hardware…
The tweet highlights DeepSeek-V4-Flash running at 5.71 tokens per second on a Mac M5 Pro, emphasizing advancements in local AI inference on consumer hardware, with a mention of Tencent's open-source Palm-Infra for Apple Silicon optimization.