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<rss version="2.0"><channel><title>Gnosly Feed - benchmark</title><link>https://gnosly.com/feed/benchmark/</link><description>Business Intelligence Console and Prediction Algorithms</description><item><id>3513</id><handler>@OpenDesignHQ</handler><handler_name>OpenDesign</handler_name><external_id /><title>OpenDesign benchmarked Kimi K3.1 Pro on real-world design tasks based on user requests. It ranked #1 among 21 models, narrowly beating GPT-6.1 Sol, with a 93% delivery rate, but at a higher cost and with longer waits</title><text>&lt;p&gt;Source: OpenDesignHQ (X)&lt;/p&gt;</text><analysis /><region /><search_query /><result_type /><url>https://x.com/OpenDesignHQ/status/2115021820462268589</url><published_at /><credits>0.0010</credits><parent_id /><referenced_id /><created_at>2026-10-28T06:24:18.939210+00:00</created_at><source><id>2</id><name>x.com</name></source><tags><tag>benchmark</tag><tag>ai</tag><tag>openai</tag><tag>kimik3</tag></tags><media><media_item><id>3365</id><link>https://pbs.twimg.com/media/HVoREKpaoAAOoMV?format=png&amp;name=small</link><alt>Image</alt><media_type /><file /><file_name /><file_ext /><created_at>2026-10-28T06:24:20.009840+00:00</created_at></media_item></media></item><item><id>3512</id><handler>@AiBattle_</handler><handler_name>AiBattle</handler_name><external_id /><title>The AA-Intelligence Index has been updated to V5 - Kimi, and Muse Wonder has been replaced with GPT6 Astra and Sol</title><text>&lt;p&gt;&lt;strong&gt;Rankings Before:&lt;/strong&gt; &lt;/p&gt;&lt;p&gt;1. Claude Opus 5.5 (Max) - 58 &lt;/p&gt;&lt;p&gt;2. Claude Sonnet 5.5 (Max) - 56 &lt;/p&gt;&lt;p&gt;3. Muse Wonder Full (Max)- 56 &lt;/p&gt;&lt;p&gt;4. Kimi K3.1 Pro - 55 &lt;/p&gt;&lt;p&gt;5. Claude Fable 5.1 (Max) - 53 &lt;/p&gt;&lt;p&gt;&lt;strong&gt;Rankings now:&lt;/strong&gt; &lt;/p&gt;&lt;p&gt;1. Claude Opus 5.5 (Max) - 58 &lt;/p&gt;&lt;p&gt;2. GPT-6-Astra (Max) - 57 &lt;/p&gt;&lt;p&gt;3. GPT-6.1-Sol (Max)- 55 &lt;/p&gt;&lt;p&gt;4. Claude Sonnet 5.5 (Max) - 54 &lt;/p&gt;&lt;p&gt;5. GPT-6.1-Terra (Max) - 51&lt;/p&gt;</text><analysis /><region /><search_query /><result_type /><url>https://x.com/AiBattle_/status/2115269739069026766</url><published_at /><credits>0.0010</credits><parent_id /><referenced_id /><created_at>2026-10-28T05:59:49.521983+00:00</created_at><source><id>2</id><name>x.com</name></source><tags><tag>ai</tag><tag>anthropic</tag><tag>benchmark</tag><tag>openai</tag><tag>kimik3</tag></tags><media><media_item><id>3364</id><link>https://pbs.twimg.com/media/HVrySLuWgAAG6Ju?format=jpg&amp;name=small</link><alt>Image</alt><media_type /><file /><file_name /><file_ext /><created_at>2026-10-28T05:59:49.968300+00:00</created_at></media_item></media></item><item><id>3509</id><handler>@ArtificialAnlys</handler><handler_name>Artificial Analysis</handler_name><external_id /><title>Announcing Artificial Analysis Intelligence Index v5, featuring 2 new benchmarks and 3 upgrades. For the first time, the majority of the Index is built on private datasets The Artificial Analysis Intelligence Index is our composite measure of model capabilities across tasks</title><text>&lt;p&gt;Key results:&lt;/p&gt;&lt;p&gt;➤ Claude Opus 5.5 (max) leads at 58, ahead of GPT-6 Astra (max, 57) and GPT-6.1 Sol (max, 55): Anthropic and OpenAI hold the top five models. Gemini 4 Argon (high) is next at 50&lt;/p&gt;&lt;p&gt;➤ The open weights gap widens from 3 points to 12: Kimi K3.1 Pro (weights not yet released) is the top open weights model at 46. Among released weights, DeepSeek V4.1 Flash 1017 (max) and GLM-5.3 (max) lead at 32 - 26 points behind the leader and below Claude Haiku 5.5 (max, 36)&lt;/p&gt;&lt;p&gt;➤ Cost per task varies by more than 13x among the leading models: of the 10 highest-scoring models shown, GPT-6.1 Terra (max) is the cheapest at $0.96 per Intelligence Index task and Claude Fable 5.1 (max) the most expensive at $13.04&lt;/p&gt;</text><analysis /><region /><search_query /><result_type /><url>https://x.com/ArtificialAnlys/status/2115265133467635877</url><published_at /><credits>0.0010</credits><parent_id /><referenced_id /><created_at>2026-10-28T05:19:17.869366+00:00</created_at><source><id>2</id><name>x.com</name></source><tags><tag>ai</tag><tag>anthropic</tag><tag>benchmark</tag><tag>deepseek</tag><tag>openai</tag></tags><media><media_item><id>3361</id><link>https://pbs.twimg.com/media/HVrubbmaoAA_Kry?format=jpg&amp;name=small</link><alt>Image</alt><media_type /><file /><file_name /><file_ext /><created_at>2026-10-28T05:19:18.875953+00:00</created_at></media_item></media></item><item><id>3506</id><handler>@cognition</handler><handler_name>Cognition</handler_name><external_id /><title>Cognition is introducing FrontierCode 2.0: our new coding benchmark that measures a model’s ability to go beyond the spec. Most coding evals measure a model’s ability to write code that meets a spec. With FrontierCode 1.0, we asked a new question: would you actually merge the PR?</title><text>&lt;p&gt;FrontierCode 2.0 is comprised of more diverse tasks, featuring larger scopes and higher mergeability standards. We are now asking: not only would you merge this PR, but should you? &lt;/p&gt;&lt;p&gt;One key feature of FrontierCode 2.0 is underspecified prompts. Rather than including every engineering decision, prompts are deliberately ambiguous, giving the models room to demonstrate their judgment. &lt;/p&gt;&lt;p&gt;The result is a benchmark that is far from saturated, with the top model scoring just 45%.&lt;/p&gt;</text><analysis /><region /><search_query /><result_type /><url>https://x.com/cognition/status/2115132488775524793</url><published_at /><credits>0.0020</credits><parent_id /><referenced_id /><created_at>2026-10-28T04:28:52.577872+00:00</created_at><source><id>2</id><name>x.com</name></source><tags><tag>coding</tag><tag>benchmark</tag><tag>ai</tag></tags><media><media_item><id>3359</id><link>https://pbs.twimg.com/media/HVplDzybQAAEbbZ?format=jpg&amp;name=small</link><alt>Image</alt><media_type /><file /><file_name /><file_ext /><created_at>2026-10-28T04:28:54.848196+00:00</created_at></media_item></media></item><item><id>960</id><handler>@KarelMercx</handler><handler_name>KarelMercx</handler_name><external_id /><title>High-quality physical crude in the West is trading...</title><text>High-quality physical crude in the West is trading at at least $126.80. Dated Brent tracks Brent, Forties, Oseberg, Ekofisk, Troll and WTI Midland delivered into Europe. The cheapest qualifying barrel sets the benchmark, which means comparable grades are even more expensive.</text><analysis /><region /><search_query /><result_type /><url>https://x.com/KarelMercx/status/2100523971259105498</url><published_at /><credits>0.0050</credits><parent_id /><referenced_id /><created_at>2026-09-17T16:40:45.098816+00:00</created_at><source><id>2</id><name>x.com</name></source><tags><tag>crude</tag><tag>oil</tag><tag>benchmark</tag></tags><media><media_item><id>814</id><link /><alt /><media_type>IMAGE</media_type><file>/media/content/960/image.png</file><file_name>image.png</file_name><file_ext>png</file_ext><created_at>2026-09-17T16:41:15.634113+00:00</created_at></media_item></media></item><item><id>346</id><handler>@thsottiaux</handler><handler_name>Tibo</handler_name><external_id /><title>We are going to need a different AGI benchmark. Wh...</title><text>We are going to need a different AGI benchmark. Where is the goalpost moving next?</text><analysis /><region /><search_query /><result_type /><url>https://x.com/thsottiaux/status/2095601101701820752</url><published_at /><credits>0.0030</credits><parent_id /><referenced_id /><created_at>2026-09-04T07:08:08.053766+00:00</created_at><source><id>2</id><name>x.com</name></source><tags><tag>technology</tag><tag>benchmark</tag><tag>agi</tag></tags><media><media_item><id>318</id><link>https://pbs.twimg.com/media/HRUR_7HbwAAz3n5?format=jpg&amp;name=small</link><alt>Image</alt><media_type /><file /><file_name /><file_ext /><created_at>2026-09-04T07:08:08.787215+00:00</created_at></media_item></media></item><item><id>269</id><handler>@MultiverseCompu</handler><handler_name>Multiverse Computing</handler_name><external_id /><title>🚀 Introducing Quasar 438B, the top European AI mod...</title><text>🚀 Introducing Quasar 438B, the top European AI model. Externally validated by @ArtificialAnlys: in their latest benchmark comparison, Quasar is the strongest-performing European model evaluated. It is the first large model released by Multiverse Computing. 438 billion parameters, English and Spanish, built for enterprise-scale agents, coding and complex multi-step workloads.</text><analysis /><region /><search_query /><result_type /><url>https://x.com/MultiverseCompu/status/2095061011501846631</url><published_at /><credits>0.0070</credits><parent_id /><referenced_id /><created_at>2026-09-02T12:51:21.833832+00:00</created_at><source><id>2</id><name>x.com</name></source><tags><tag>european</tag><tag>benchmark</tag><tag>ai</tag></tags><media><media_item><id>242</id><link>https://abs.twimg.com/emoji/v2/svg/1f680.svg</link><alt>🚀</alt><media_type /><file /><file_name /><file_ext /><created_at>2026-09-02T12:51:22.092663+00:00</created_at></media_item><media_item><id>243</id><link>https://pbs.twimg.com/media/HRMm2Y6WwAEkhQF?format=jpg&amp;name=small</link><alt>Image</alt><media_type /><file /><file_name /><file_ext /><created_at>2026-09-02T12:51:22.127519+00:00</created_at></media_item></media></item></channel></rss>