DeepSeek V4.1 Flash 1017

Headlines · 5

1. 2d
   Rivermark benchmark finds tuned open models competitive on design

   Rivermark developer JannVanDam reported preliminary results from 112 social and marketing design requests evaluated through more than 4,700 blind pairwise human judgments. He said DeepSeek v4.1 Flash 1017 and GLM 5.3 Flash, using Rivermark, matched or beat plain Claude Code with Sonnet 5.5 and /design, while Sonnet 5.5 achieved the strongest result with Rivermark. The design-specific harness has been tuned for some models used in production, though not for the benchmark test cases. The author is validating the findings with additional judges.

   r/LocalLLaMA · 🔥 0
2. 4d
   Artificial Analysis overhauls Intelligence Index with private evaluations

   Artificial Analysis launched Intelligence Index v5, with 60% of its evaluations now based on private test sets or held-out answers. The update adds FrontierCode 2.0 and Terminal-Bench-Science, upgrades three existing benchmarks, and introduces Progress Index v1 to track model capability over time; Claude Opus 5.5 leads the initial v5 ranking with 58 points.

   cognition (X) · 🔥 5
3. 4d
   GPT-6.1 Terra writing evaluation favors lower cost

   A Towards AI evaluation tested GPT-6.1 Terra on 10 YouTube script-writing tasks, generating five drafts per task and scoring them blindly out of 100 with four LLM judges. GPT-6.1 Terra ranked 23rd overall in an evaluation of 84 models, while GPT-5.6 Terra ranked 15th. Its low-effort setting achieved overlapping Elo scores for less than half the cost of GPT-5.6 Terra at medium effort. On maximum effort, GPT-6.1 Terra used about 9,500 thinking tokens per draft and cost roughly three times as much without improving the writing score. Only one of the four judges, OpenAI's GPT-6.1 Sol, clearly preferred GPT-6.1 Terra; the other three scored it lower.

   r/OpenAI · 🔥 0
4. 6d
   OpenAI and Anthropic Cut LLM Prices by Up to 80%

   Max Woolf’s analysis charts how OpenAI and Anthropic reduced API prices for major models between June and September, including an 80% cut for GPT-5.6 Luna and lower prices for GPT-6.1 Sol and Claude Opus 5.5. The reports say competition from lower-cost open-weight models, including DeepSeek and Kimi offerings, created pricing pressure, while improvements in inference efficiency may also have enabled lower prices. Price comparisons in the analysis cover input, output and cache-read charges per million tokens.

   Hacker News · AI（100+ 分） · 🔥 0
5. Oct 20
   DeepSeek V4.1 Flash 1017 debuts as open-weight value leader

   Latent Space's AINews roundup reports that DeepSeek V4.1 Flash 1017 is a 552B-total, 16B-active MoE model with a 1M-token context window under an MIT license, priced unchanged at $0.30/$1.20 per million input/output tokens at peak, with off-peak pricing half that. Artificial Analysis scores it 45 on its Intelligence Index, up six points and tied with GLM-5.3 for second among open-weight models, while noting MiMo-V2.6-Pro and GPT-6.1 Sol (medium) score higher at lower cost per task. The model is available through DeepSeek's API, Fireworks, Baseten, DeepInfra, Cloudflare and Together, and ranks first among open models in Code Arena WebDev at No. 12 overall with 1,670 points; Together says it was trained with self-feedback RL, and release figures cite Terminal-Bench 4.0 rising from 31.2 to 42.3.

   Latent Space · 🔥 0

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