Qwen3.8-2.4T
These artifacts are compatible with vLLM, SGLang, TokenSpeed, etc. The quantization method is fine-grained fp8 quantization with block size of 128, and its performance metrics are nearly identical to those of the original model. For users seeking managed, scalable inference without infrastructure maintenance, the official Qwen API service is provided by Qwen Cloud.
- ▪These artifacts are compatible with vLLM, SGLang, TokenSpeed, etc.
- ▪The quantization method is fine-grained fp8 quantization with block size of 128, and its performance metrics are nearly identical to those of the original model.
- ▪For users seeking managed, scalable inference without infrastructure maintenance, the official Qwen API service is provided by Qwen Cloud.
Hacker News (Front Page) files mainly under programming. We currently carry 1,484 of its stories. Top-voted stories on Hacker News.
Story provenance
Source · retrieval · rights · ranking — open for full record
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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-FP8 |
| Publication time | Wed, 12 Aug 2026 16:26:16 +0000 |
| Retrieval time | 2026-08-12T18:36:37.280Z |
| Last seen | 2026-08-12T18:36:37.280Z |
| 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 | None |
| Cluster logic | Not yet clustered, or no peer story found in the clustering window. |
| 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-FP8 like 87 Follow Qwen 96.1k Text Generation Transformers Safetensors qwen3_5_moe_text conversational fp8 License: qwen3.8-max Model card Files Files and versions xet Community 2 Deploy Copy to bucket new Use this model Instructions to use Qwen/Qwen3.8-2.4T-A95B-FP8 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-FP8 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-FP8") 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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