Qwen/Qwen3.8-2.4T-A95B
Qwen3.8-2.4T-A95B Qwen3.8 Highlights Model Overview Benchmark Results Quickstart Serving Qwen3.8API UsageBest Practices Citation Qwen3.8-2.4T-A95B This repository contains model weights and configuration files for the post-trained model in the Hugging Face Transformers format. These artifacts are compatible with vLLM, SGLang, TokenSpeed, etc. For users seeking managed, scalable inference without infrastructure maintenance, the official Qwen API service is provided by Qwen Cloud.
- ▪Qwen3.8-2.4T-A95B Qwen3.8 Highlights Model Overview Benchmark Results Quickstart Serving Qwen3.8API UsageBest Practices Citation Qwen3.8-2.4T-A95B This repository contains model weights and configuration files for the post-trained model in
- ▪These artifacts are compatible with vLLM, SGLang, TokenSpeed, etc.
- ▪For users seeking managed, scalable inference without infrastructure maintenance, the official Qwen API service is provided by Qwen Cloud.
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Story provenance
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | Huggingface |
| Canonical URL | https://huggingface.co/Qwen/Qwen3.8-2.4T-A95B |
| Publication time | Wed, 12 Aug 2026 15:01:17 +0000 |
| Retrieval time | 2026-08-12T15:31:37.477Z |
| Last seen | 2026-08-12T15:31:37.477Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | VVPrjDx_wb4E · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Qwen / Qwen3.8-2.4T-A95B like 113 Follow Qwen 96k Text Generation Transformers Safetensors qwen3_5_moe_text conversational License: qwen3.8-max Model card Files Files and versions xet Community 5 Deploy Copy to bucket new Use this model Instructions to use Qwen/Qwen3.8-2.4T-A95B with libraries, inference providers, notebooks, and local apps. Follow these links to get started. Libraries Transformers How to use Qwen/Qwen3.8-2.4T-A95B with Transformers: # Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-generation", model="Qwen/Qwen3.8-2.4T-A95B") messages = [ {"role": "user", "content": "Who are you?"}, ] pipe(messages) # Load model directly from transformers import AutoTokenizer, AutoModelForCausalLM tokenizer =…
Excerpt limited to ~120 words for fair-use compliance. The full article is at Huggingface.
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