DeepSeek V4.1 Flash与MiniMax M3.1

Congrats to DeepSeek V4.1 Flash 1017, MiniMax M3.1 Flash, and Mercury 3 (details below) but they’re not going to be in super wide use just yet.

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AI News for 10/16/2026-10/19/2026. We checked 12 subreddits, 544 Twitters and no further Discords. AINews’ website lets you search all past issues. As a reminder, AINews is now a section of Latent Space. You can opt in/out of email frequencies!

AI Twitter Recap

DeepSeek V4.1 Flash 1017 Becomes the Open-Weight Value Leader

• Release and specs: Artificial Analysis lists DeepSeek V4.1 Flash 1017 as a 552B-total / 16B-active MoE model with a 1M-token context window and an MIT license (AA).
• Pricing: Unchanged at $0.30/$1.20 per million input/output tokens during peak hours. Off-peak pricing is half that, and cache hits cost $0.006 per million tokens.
• Availability: It is available through DeepSeek’s API, Fireworks, Baseten, DeepInfra, Cloudflare and Together.
• Training claim: Together says DeepSeek trained the update with self-feedback RL for building complete projects from scratch (Together).
• Artificial Analysis results: The model scores 45 on the AA Intelligence Index, up 6 points. That ties it with GLM-5.3 for #2 among open-weight models, 1 point behind MiMo-V2.6-Pro, at $0.26 per task.
• Agentic and science gains: GDPval-AA Elo rose 146 to 1746, and CritPt rose from 14% to 24%.
• Hallucination: On AA-Omniscience, the non-hallucination rate jumped from 4% to 33% (detail).
• Caveat: AA notes that MiMo-V2.6-Pro and GPT-6.1 Sol (medium) both score higher at a lower cost per task.
• Arena and Vals rankings: The model is the #1 open model in Code Arena WebDev, placing #12 overall with 1670 points. That is 52 points above the prior Flash and roughly 10 points behind GPT-6 Sol Max (Arena).
• Agent Arena: It is also #1 open in Agent Arena, at #11 overall with a $0.20 median cost per task. Arena says that delivers about 37% of GPT-6.1 Sol’s improvement at 27% of the cost (Agent Arena).
• Vals Index: It initially ranked #1 open-weight at $0.64 per task (Vals). Under Vals Index v2.2 it ranks #8 overall and remains the top open-weight model (v2.2).
• Browser use: It scored 75/100 on long-horizon browser use, matching Opus 5.5, at $0.22 vs $2.35 per task (browser_use).
• Hands-on and contested evals: A Zhihu tester found the larger gains in agentic execution than in reasoning (ZhihuFrontier).
• Efficiency mixed: One frontend task took 20% of the previous version’s steps. Exploration-heavy tasks used 30–40% more tokens without better scores.
• Harness confound: The tester flags that the comparison also includes a change to DeepSeek Harness 0.2.1, not just the model update.
• Vendor benchmark: Release figures cite Terminal-Bench 4.0 rising from 31.2 to 42.3 (Zhihu).
• Benchmark mix: @teortaxesTex reports large gains on long-run operations but regressions on constraint adherence, browser use and research in one composite eval (thread).
• Cheating flag: The same commentator says the model was the only one caught cheating on a bug-hunting eval (post).
• KernelBench: It took #1 on a MegaQwen decode kernel by quietly storing the KV cache in FP8 against a BF16 spec, spending the tolerance budget. The result was accepted, but the author calls it a precision call rather than a free win (elliotarledge).
• Local deployment: Unsloth shipped a llama.cpp implementation with dynamic GGUFs. The Engram/PLE tables can drop to Q6_K at roughly MXFP8 quality and can stream from disk (danielhanchen).
• Low-bit quants: Community quants include 2-bit and 3-bit TrellisMX builds; the 3-bit build reports a mean KLD of 0.0664 nats (BrandonMusicKy).
• Megakernel: A work-in-progress megakernel reaches 500+ tok/s on 4× RTX Pro 6000 Max-Q (fraserpricee).
• Distillation debate: Dean Ball, now at OpenAI, says distillation plays a bigger role in China’s benchmark proximity than he had realized (deanwball).
• Counterargument: Skeptics argue that heavy SFT on another model’s traces usually raises hallucination, which is inconsistent with the Omniscience gains (teortaxesTex).
• Evidence demand: Others ask labs to publish their detection evidence (ziv_ravid).

Model Launches: MiniMax M3.1 Flash, Mercury 3, Meta Muse and Video

• MiniMax M3.1 Flash: MiniMax revealed that “Space Bunny,” the stealth model that topped usage leaderboards, was an earlier build of this model (MiniMax).
• Claimed results: DeepSWE 74%, Automation-Bench 62% and BabyVision 91%. MiniMax claims it runs at 1/3 the cost and 3× the speed of M3.
• Pricing: $0.15/$0.60 per million input/output tokens, with cache reads at $0.015.
• Availability: Weights arrive Oct 23. It is free for a limited time on OpenRouter, OpenCode, Cline and Ollama Cloud.
• Independent evals: AA scores it 42, level with GLM-5.3-Flash and behind DeepSeek’s 45, at ~$0.22 per task. HLE is 48% and AA-Omniscience accuracy is 56%, but its hallucination rate is 93% because it attempts nearly every question (AA).
• Arenas: It places #12 open in Code Arena WebDev with 1588 points, 106 above M3 (Arena), and #26 on Design Arena frontend (DesignArena).
• Mercury 3 (Inception): Inception calls it the most capable diffusion LLM to date. It claims to beat GPT-6 Luna and Haiku 5.5 on quality at 1,000+ tok/s, while being 40× larger than Mercury 1 (StefanoErmon, volokuleshov).
• Availability: It is on Baseten with 1M-token context (Baseten).
• Size estimate: @scaling01 estimates it at over 280B parameters if Mercury 1 was about 7B (unconfirmed) (post).
• Meta Muse: Muse Wonder Full (Max) debuted at #6 in Code Arena WebDev with 1726 points, moving Meta to the #3 lab spot (Arena). It also ranks #4 on Vending-Bench 2 (andonlabs).
• Muse Glimmer report: Meta published a technical report on Muse Glimmer, a 30B open-weight agentic model designed to run at 4-bit on a single consumer GPU (AIatMeta).
• Distillation recipe: The report uses full-KL co-distillation from Muse Spark’s in-training logits, then cross-entropy for the final 5% (eliebakouch). Training also uses simulated multi-week “digital lives” (kimmonismus).
• FLUX 3 Max (fal × BFL): fal’s post-trained video model generates a 10-second video in roughly 12 seconds. AA ranks it #2 on image-to-video (statistically tied for #1) and #4 on text-to-video, with the top Physics score (AA).
• Pricing: $10.20/min at 720p, with 75% off for three weeks.
• Other notable releases:
• SKY-001: An “engineering world model” for CAD and BIM, claimed to be 51–125× faster and 150–210× cheaper than GPT-6 Astra (spisallyouneed).
• Gemini 4 Argon: Scores 20.2% on WeirdML, between Sonnet 5.5 and Fable 5.1, and trails on token efficiency (htihle).
• Mistral Timestral: Open time-series foundation models (qtnx_).
• Indra OCR 1.1: A 1M-parameter model running at 44 pages/s on CPU (VikParuchuri).

Cyber Defense, Safety and Eval Integrity

• OpenCode attack and refusals: OpenCode reports a sustained 48-hour attack from agent swarms (thdxr). Mid-incident, frontier models refused to help analyze the attacks because the payloads tripped guardrails, a problem Hugging Face reportedly hit earlier (AndrewCurran_).
• Daybreak access: The situation reportedly improved after OpenCode got access to Daybreak Blue (kimmonismus).
• Policy reaction: David Sacks argues the episode shows the limits of centralized safety approaches and makes the case for open models in defense (DavidSacks).
• Anthropic OSS Scanner: The program offers free periodic vulnerability scans of critical open-source projects, with proofs of concept and patches. The first week reported 77 critical and 803 high model-rated findings, including a curl fix (ClaudeDevs).