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Wednesday19 items

  5. Fireworks AIFirst-partyModel releases
    AI score62

    Fireworks Research Releases Ember-1: A Token-Saving Specialized Model Based on Kimi K3

    Fireworks Research has released Ember-1, a specialized model trained on Kimi K3 that reduces token consumption by about 40% while maintaining equivalent quality. The company says that across 7 benchmarks and production traffic from two customers, K3's reasoning process can be shortened by 35–50% without any drop in accuracy; on Bedside Bench, Ember-1 sits on the Pareto frontier for cost and task completion. The model is available on Serverless as a Research Preview, offered alongside the base Kimi K3, with training support on enterprises' own data also opened up.

    Same story · 2 reports

    #Model releases#Reasoning#English text is being prepared.

  6. Ant Ling: Developer BlogFirst-partyModel releases
    AI score69

    Ant Ling open-sources two 6B models in the Ming-Image-0.1-Design series

    Ant Ling has open-sourced the Ming-Image-0.1-Design series, comprising two 6B models: Design generates complete visual designs such as UIs, infographics, and posters from text requirements, while Layer decomposes a design image into 2–9 semantically independent RGBA layers; Design Skill and PPT Skill are also open-sourced. In the UI/UX Design evaluation updated by Artificial Analysis on September 18, 2026, Design ranks 1st among open-source models with an Elo score of 1082; Layer achieves the best results on all 12 metrics of Crello-Test, reducing single-inference time from 795 seconds to 183 seconds. After Ant's internal Huamei integrated Layer, the time to first obtain editable layers dropped from over 5 minutes to about 40 seconds.

    English text is being prepared.

    #Model releases#Open-source ecosystem#Multimodal

  9. sherwin_wuModel releases
    AI score61

    English translation is being prepared.

    Quoted postOpenAI Developers · @OpenAIDevs

    GPT-6 Sol and Luna just landed in Astra’s orbit. Both launch today with API prices 50% lower than GPT-5.6. Build with Sol. Scale with Luna. To production and beyond. https://t.co/ZCEFp4JdjV

    Same story · 2 reports

    #Industry news#OpenAI#Model releases

  14. anthropicaiModel releases
    AI score67

    English translation is being prepared.

    Quoted postClaude · @claudeai

    Introducing Claude Opus 5.5, the first model in our new Claude 5.5 family. It performs at the level of Claude Fable 5.1 for most tasks, and costs 40% less to run than Opus 5. https://t.co/Q9C2VKQ79f

    Same story · 4 reports

    #Model releases#Anthropic

Tuesday16 items

  3. stepfun_aiFirst-partyModel releases
    AI score56

    English translation is being prepared.

    Quoted postArtificial Analysis · @ArtificialAnlys

    StepFun's Step 5 Preview scores 44 on the Artificial Analysis Intelligence Index, matching Kimi K3 (max) at ~2.8x lower cost per task, but trails peers on agentic evaluations Step 5 Preview is @StepFun_ai's new flagship model, with 600B total and 27B active parameters, succeeding Step 3.7 Flash (released May 2026). It scores 44 on the Intelligence Index, level with Kimi K3 (max) and just behind GLM-5.3 (max, 45) and Qwen3.8 Max (45) Key takeaways: ➤ Step 5 Preview costs ~2.8x less per Intelligence Index task than models at the same score. It costs ~$0.72 per task, against ~$2.00 for Kimi K3 (max) at the same score of 44 and ~$2.01 for GLM-5.3 (max) at 45. This is driven by pricing: at $1/$2.70 per 1M input/output tokens, it is priced below both on input and output. MiMo-V2.6-Pro is the one model that scores higher (46) at a lower cost per task ($0.13) ➤ Frontier reasoning is the standout strength, and where the jump from Step 3.7 Flash is largest. Step 5 Preview scores 46% on Humanity's Last Exam, in line with Kimi K3 (max, 47%), and 21% on CritPt, between Kimi K3 (23%) and GLM-5.3 (max, 19%). Both are up sharply from Step 3.7 Flash: +25 points on HLE and +19 points on CritPt ➤ Higher AA-Omniscience accuracy than GLM-5.3 at fewer parameters, but with more hallucination. At 600B total parameters, Step 5 Preview reaches 42% accuracy on AA-Omniscience, our benchmark measuring factual recall and hallucination, ahead of GLM-5.3 (max, 34%, 753B) and behind Kimi K3 (max, 48%, 2.8T). It attempts more questions than GLM-5.3 (68% vs 55%) and hallucinates more often when it does (43% vs 30%), landing at 16 on the AA-Omniscience Index, between GLM-5.3 (14) and Kimi K3 (20) ➤ Agentic evaluations are where Step 5 Preview lags peers at a similar Intelligence Index score. It scores 1,566 Elo on GDPval-AA, our primary evaluation for agentic performance, behind Qwen3.8 Max (1,668) and GLM-5.3 (max, 1,646). The gap holds on Terminal-Bench 4.0 (33% vs 39% and 42%), AA-Briefcase (1,432 Elo vs 1,640 and 1,525) and AutomationBench-AA (51% vs 56% and 62%) Key model details: ➤ Model Size: 600B total parameters, 27B active MoE model ➤ Context window: 1M tokens ➤ Multimodality: Text, image and video input, text output ➤ Pricing: $1/$2.70 per 1M input/output tokens, with cached input at $0.05/M ➤ Availability: StepFun first-party API, with open weights release planned for October 15th ➤ Licensing: Closed weights currently, with weights release planned for October 15th

    #Model releases#Evaluations / benchmarks#OpenAI