Image created with Flux Pro v1.1 Ultra. Image prompt: River bridge catwalk at night with an industrial search beam sweeping the water; a bold centered title reading “DeepSeek” in geometric sans, high contrast; investigative maps glow on a tablet; focused, electric blue accents, sleek minimal UI
New DeepSeek V3.1 beats Opus and R1 for a dollar https://x.com/scaling01/status/1957892601098432619
Deepseek V3.1 is already 4th trending on HF with a silent release without model card 😅😅😅 The power of 80,000 followers on @huggingface (first org with 100k when?)! https://x.com/ClementDelangue/status/1957897020741402751
Introducing DeepSeek-V3.1: our first step toward the agent era! 🚀 🧠 Hybrid inference: Think & Non-Think — one model, two modes ⚡️ Faster thinking: DeepSeek-V3.1-Think reaches answers in less time vs. DeepSeek-R1-0528 🛠️ Stronger agent skills: Post-training boosts tool use and”” / X https://x.com/deepseek_ai/status/1958417062008918312
• DeepSeek V3.1 Reasoner improves on DeepSeek R1 on the Extended NYT Connections Benchmark: 48.6% → 57.7%. • DeepSeek V3.1 Non-Think improves on DeepSeek V3-0324: 16.8% → 21.6%. • Mistral Medium 3.1 improves on Mistral Medium 3: 11.5% → 15.2%. • GPT-5 (low https://x.com/LechMazur/status/1958970478712037548
@deepseek_ai Now Available and default model in anycoder: https://x.com/_akhaliq/status/1958488877024362966
@scaling01 Just to clarify, it’s “”trained using the UE8M0 FP8.”” DeepSeek stated this is designed for the upcoming generation of chips”” / X https://x.com/Anonyous_FPS/status/1958437047359995914
@teortaxesTex Maybe I missed something, but I could only find the Base model, and no model card. Where did they upload the Thinking/Reasoning model? https://x.com/rasbt/status/1957982932594778596
📢 New Model(s) Drop: DeepSeek v3.1 Thinking & Chat are now on Yupp! The latest edition from @deepseek_ai offers hybrid thinking built in, for quicker answers and stronger, tool-savvy agents. We checked them out with some prompts on Yupp: https://x.com/yupp_ai/status/1958935061677711451
🥇DeepSeek v3.1 INT4 model: https://x.com/HaihaoShen/status/1958507863749325197
9:15 AM in China, I predict we’ll see the second item soon (logically, V3.1–Instruct) and hopefully a model card/tweets. My biggest wish is to also see «With the release of DeepSeek-V3.1, the V3 series comes to an end… the DeepSeek V4 series will be released in the future» https://x.com/teortaxesTex/status/1957975224768430179
BIG LAUNCH: @deepseek_ai’s V3.1 is now live on W&B Inference! One model, two modes: toggle between high-speed ‘Non-Think’ & deep ‘Think’. Priced at just $0.55/$1.65 per 1M tokens, it’s a game-changer for building intelligent agents. Want $50 in free credits? Details below. https://x.com/weave_wb/status/1958681269484880026
DeepSeek had been using UE8M0 FP8 for a long time, you can see it in DeepGEMM. But maybe? https://x.com/teortaxesTex/status/1958437815710089697
DeepSeek is doubling down on their open source commitments with an MIT license for -Base. This is not only their first permissively licensed base model, it is the first large* permissively licensed base model in the industry. * unless you count dots.llm1 from RedNote @ 140B. https://x.com/georgejrjrjr/status/1957867653764379073
Deepseek just released a new model! https://x.com/ClementDelangue/status/1957823652298166340
DeepSeek launches V3.1, unifying V3 and R1 into a hybrid reasoning model with an incremental increase in intelligence Incremental intelligence increase: Initial benchmarking results for DeepSeek V3.1 show Artificial Analysis Intelligence Index of 60 in reasoning mode, up from https://x.com/ArtificialAnlys/status/1958432118562041983
DeepSeek V3.1 beats Claude 4 Opus on Aider Polyglot This makes it the best non-TTC coding model and all of that for ~$1 https://x.com/scaling01/status/1957890953026392212
DeepSeek V3.1 dropped and the Cline community is testing it out. Early sentiment: “”Makes 10,000 assumptions even when told to clarify”” for planning tasks. What’s your experience been? (early data — 13.3% diff edit failure rate)”” / X https://x.com/cline/status/1959032407828602886
DeepSeek v3.1 is live on our Model APIs! https://x.com/basetenco/status/1958716181256577347
DeepSeek V3.1 Now Available on Chutes, with hybrid inference (one-model, two-modes) $0.1999 USD / M Input $0.8001 USD / M Output Available now: https://x.com/chutes_ai/status/1958507978476106196
DeepSeek-V3.1 Release | DeepSeek API Docs https://api-docs.deepseek.com/news/news250821
DeepSeek-V3.1-4bit running with MLX on M3 Ultra 512GB at 21 toks/sec! 🔥 Using only 380GB! 👀 <think> or </think> that is the question. https://x.com/ivanfioravanti/status/1958778366229655971
Linear scaling achieved with multiple DeepSeek v3.1 instances. 4x macs = 4x throughput. 2x M3 Ultra Mac Studios = 1x DeepSeek @ 14 tok/sec 4x M3 Ultra Mac Studios = 2x DeepSeek @ 28 tok/sec DeepSeek V3.1 is a 671B parameter model – so at its native 8-bit quantization, it https://x.com/MattBeton/status/1958946396062851484
Looking into the V3 vs V3.1 a bit – modelling and config for the latest deepseek models is exactly the same? What’s the difference then? purely data? if purely data then why release base model too? and not just release a refresh for instruct?”” / X https://x.com/reach_vb/status/1957824849633485249
looks like @deepseek_ai is still on track to ship DeepSeek V4! https://x.com/swyx/status/1957902542136045608
Now on MLX 🚀 > pip install mlx-lm”” / X https://x.com/Prince_Canuma/status/1958791001301987628
Reminder that there’s 15 hours difference between SF and Hangzhou/Beijing. DeepSeek release cycle is as follows: do tests, push the model to prod at ≈ 7 PM local time, go home/out for drinks/whatever, next day maybe leisurely add a model card. They sleep through the release. https://x.com/teortaxesTex/status/1957954702781686094
some highlights from the release: > optional thinking mode achieves same/ competitive results as R1-0528 > MMLU, GPQA): 80.1 on GPQA (pretty strong) > LiveCodeBench: scores 74.8 > R1 > AIME 2024: scores 93.1 > R1 > support for tool use (non-thinking mode only) > new search”” / X https://x.com/reach_vb/status/1958430639595864378
@deepseek_ai 3.1 reasons to get hyped about DeepSeek v3.1 1: Hybrid reasoning 2: Agentic tool use 3: Improved coding 3.1: Best-in-class latency on Baseten https://x.com/basetenco/status/1958515897972232526
@nrehiew_ That’s not why it’s because reasoning uses up context length too fast to get to the end of an agentic coding loop”” / X https://x.com/Teknium1/status/1958898159326765075
DeepSeek trained its agentic coder as a non reasoner. There is a reason Anthropic evaluated Opus 4.1 without thinking on SweBench, Claude Code has thinking off by default and Qwen released Qwen Coder for Qwen code as a non reasoner. We do not need reasoning for Agentic Coding. https://x.com/nrehiew_/status/1958838487895117956
DeepSeek-V3.1 officially released! Key highlights of the update: – hybrid thinking model – more efficient reasoning – improved reasoning for search – better tool calling and agentic capabilities – improvements on many benchmarks: SWE-Bench: 44.6% -> 66%, Aider Polyglot https://x.com/scaling01/status/1958438863279681824
DeepSeek-V3.1 on par with o3, Opus 4 and Gemini 2.5 Pro Preview on coding It achieves a 76.3% score on Aider Polyglot with Thinking https://x.com/scaling01/status/1958438007104549243
just a minor version bump. booooring https://x.com/willccbb/status/1958420877537849801
🚀 Exciting news: DeepSeek-V3.1 from @deepseek_ai now runs on vLLM! 🧠 Seamlessly toggle Think / Non-Think mode per request ⚡ Powered by vLLM’s efficient serving — scale to multi-GPU with ease 🛠️ Perfect for agents, tools, and fast reasoning workloads 👉 Guide & examples: https://x.com/vllm_project/status/1958580047658491947
DeepSeek-V3.1 is fully ready on Hugging Face Inference Providers! https://x.com/ben_burtenshaw/status/1958449429511352549
China’s DeepSeek Releases V3.1, Boosting AI Model’s Capabilities – Bloomberg https://www.bloomberg.com/news/articles/2025-08-19/china-s-deepseek-release-v3-1-boosting-ai-model-s-capabilities
WE ARE SO BACK!!! https://x.com/reach_vb/status/1957821171249934486
Quick hacks for tool calling and thinking flag support for DeepSeek V3.1 in SGLang: https://t.co/EoUWKu4MEE Then run with: –tool-call-parser deepseekv31 –reasoning-parser qwen3 And in request body: “”chat_template_kwargs””: {“”thinking””: true} This is up on @chutes_ai now, but”” / X https://x.com/jon_durbin/status/1958488353478758599
