OpenClaw announced that DeepSeek's DeepSeek V4.1 Flash is now available in OpenClaw. The announcement was released by OpenClaw on October 23, 2026, and is first-party information. OpenClaw is also soliciting feedback from users who have already used it in their agents. There are currently no subsequent developments; the event status is based on this launch announcement.
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ARC Prize announced the results of DeepSeek V4.1 Flash 1017 on the ARC-AGI validation set: a score of 78.1% on ARC-AGI-2 at a cost of $0.16 per task, and a score of 94.5% on ARC-AGI-1 at a cost of $0.06 per task. The organization also listed the changes in the best scores of the DeepSeek Flash series on ARC-AGI-2: V4 Flash 0731 at 61.4%, V4.1 Flash at 72.9%, and V4.1 Flash 1017 rising to 78.1%. A day earlier, Guillermo Rauch announced that Vercel would add DeepSeek v4.1 Flash (1017) to Token Pass, using DeepSeek's new weights, supporting a 1M context window with no configuration changes required; he said the model is fast, extremely low-priced, and offers zero data retention, making it suitable for running subagents for tasks planned by larger, more expensive models. Currently, the public information consists of the above results and the addition to Token Pass.
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View story:ARC Prize announces ARC-AGI verification results for DeepSeek V4.1 Flash 1017
Arena announced that DeepSeek-V4.1-Flash-20261017 (Max) has entered Arena and ranks first among open models on both the Agent Arena and Code Arena: WebDev leaderboards. The news was released by Arena on October 21, 2026, and is the latest verifiable development to date. Arena also noted that the 3D world generated by the model and more detailed ranking information can be viewed in the related post. Apart from this top-ranking result, there are no other subsequent developments with qualified factual evidence.
Arena announced that DeepSeek-V4.1-Flash-20261017 (Max) has entered Arena and ranks first among open models on both the Agent Arena and Code Arena: WebDev leaderboards. The news was released by Arena on October 21, 2026, and is the latest verifiable development to date. Arena also noted that the 3D world generated by the model and more detailed ranking information can be viewed in the related post. Apart from this top-ranking result, there are no other subsequent developments with qualified fact
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Arena announced that DeepSeek-V4.1-Flash-20261017 (Max) has entered Arena and ranks first among open models on both the Agent Arena and Code Arena: WebDev leaderboards. The news was released by Arena on October 21, 2026, and is the latest verifiable development to date. Arena also noted that the 3D world generated by the model and more detailed ranking information can be viewed in the related post. Apart from this top-ranking result, there are no other subsequent developments with qualified factual evidence.
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View story:DeepSeek-V4.1-Flash-20261017 (Max) Tops Arena Open Model Leaderboard
ARC Prize announced the results of DeepSeek V4.1 Flash 1017 on the ARC-AGI validation set: a score of 78.1% on ARC-AGI-2 at a cost of $0.16 per task, and a score of 94.5% on ARC-AGI-1 at a cost of $0.06 per task. The organization also listed the changes in the best scores of the DeepSeek Flash series on ARC-AGI-2: V4 Flash 0731 at 61.4%, V4.1 Flash at 72.9%, and V4.1 Flash 1017 rising to 78.1%. A day earlier, Guillermo Rauch announced that Vercel would add DeepSeek v4.1 Flash (1017) to Token Pass, using DeepSeek's new weights, supporting a 1M context window with no configuration changes required; he said the model is fast, extremely low-priced, and offers zero data retention, making it suitable for running subagents for tasks planned by larger, more expensive models. Currently, the public information consists of the above results and the addition to Token Pass.
ARC Prize announced the results of DeepSeek V4.1 Flash 1017 on the ARC-AGI validation set: a score of 78.1% on ARC-AGI-2 at a cost of $0.16 per task, and a score of 94.5% on ARC-AGI-1 at a cost of $0.06 per task. The organization also listed the changes in the best scores of the DeepSeek Flash series on ARC-AGI-2: V4 Flash 0731 at 61.4%, V4.1 Flash at 72.9%, and V4.1 Flash 1017 rising to 78.1%. A day earlier, Guillermo Rauch announced that Vercel would add DeepSeek v4.1 Flash (1017) to Token Pas
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ARC Prize announced the results of DeepSeek V4.1 Flash 1017 on the ARC-AGI validation set: a score of 78.1% on ARC-AGI-2 at a cost of $0.16 per task, and a score of 94.5% on ARC-AGI-1 at a cost of $0.06 per task. The organization also listed the changes in the best scores of the DeepSeek Flash series on ARC-AGI-2: V4 Flash 0731 at 61.4%, V4.1 Flash at 72.9%, and V4.1 Flash 1017 rising to 78.1%. A day earlier, Guillermo Rauch announced that Vercel would add DeepSeek v4.1 Flash (1017) to Token Pass, using DeepSeek's new weights, supporting a 1M context window with no configuration changes required; he said the model is fast, extremely low-priced, and offers zero data retention, making it suitable for running subagents for tasks planned by larger, more expensive models. Currently, the public information consists of the above results and the addition to Token Pass.
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View story:ARC Prize announces ARC-AGI verification results for DeepSeek V4.1 Flash 1017
According to Bloomberg, DeepSeek raised about 100 billion yuan (approximately 15 billion US dollars) in its latest funding round, with CATL and Tencent among the largest investors in this round. People familiar with the matter said that during its discussions with investors, DeepSeek raised its funding target at least twice, from an initial 50 billion yuan to 80 billion yuan, and ultimately to 100 billion yuan. Shanghai Securities News reported the same day that Tencent and CATL were the largest contributors in this round, with the deal expected to be formally completed within the next few days, though the final amount is still not fully determined; DeepSeek, Tencent and other relevant investors have not publicly responded. There is currently no subsequent development with evidence.
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View story:Report: DeepSeek raises about 100 billion yuan in new funding round
Artificial Analysis has added DeepSeek Search to its search index evaluation. The evaluation results from October 22, 2026 show that DeepSeek Search scored 69 on the index, ranking 17th among 27 search products, and is the lowest-priced paid search API on the list: charging $0.75 per 1k searches, with a cost of about $0.032 per task, making it the 5th cheapest among the 27 products. In terms of accuracy, it scores 70% on AA-Omniscience, ranking 10th, but only 63% on BrowseComp, which requires multi-hop reasoning, ranking 25th. In addition, each search returns about 7k tokens, raising the model cost to the 2nd highest on the list. There are currently no further developments.
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View story:Artificial Analysis Adds DeepSeek Search to Its Search Index Evaluation
Artificial Analysis has added DeepSeek Search to its search index evaluation. The evaluation results from October 22, 2026 show that DeepSeek Search scored 69 on the index, ranking 17th among 27 search products, and is the lowest-priced paid search API on the list: charging $0.75 per 1k searches, with a cost of about $0.032 per task, making it the 5th cheapest among the 27 products. In terms of accuracy, it scores 70% on AA-Omniscience, ranking 10th, but only 63% on BrowseComp, which requires multi-hop reasoning, ranking 25th. In addition, each search returns about 7k tokens, raising the model cost to the 2nd highest on the list. There are currently no further developments.
Artificial Analysis has added DeepSeek Search to its search index evaluation. The evaluation results from October 22, 2026 show that DeepSeek Search scored 69 on the index, ranking 17th among 27 search products, and is the lowest-priced paid search API on the list: charging $0.75 per 1k searches, with a cost of about $0.032 per task, making it the 5th cheapest among the 27 products. In terms of accuracy, it scores 70% on AA-Omniscience, ranking 10th, but only 63% on BrowseComp, which requires mu
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On October 20, 2026, DeepSeek announced the open-sourcing of its internal production-grade inference framework, DeepInfer. According to Latent Space, the framework powers DeepSeek-V4.1-Flash, is customized based on vLLM, supports distributed inference, speculative decoding, SWA Bounded Replay, and structured output, and targets the NVIDIA SM100 and Huawei Ascend 950 platforms; the published single-cluster production figures are 155 trillion tokens processed per day, a 96% input cache hit rate, 400 ms first-token latency, and a generation speed of 230 tokens/s. The report also noted that components such as KV cache management and load balancing have not yet been fully open-sourced. The next day, DeepSeek published the DeepInfer technical report on Zhihu, disclosing internal details including the hardware selection for Prefill and Decode and the KVCache targets, and providing data showing a single cluster serving 155 trillion Tokens/day at $38 per card per hour at off-peak prices. The framework is currently open-sourced, but the KV cache system, Prefill/Decode disaggregation, and load balancing required for a complete service are not fully included in this open-source project.
On October 20, 2026, DeepSeek announced the open-sourcing of its internal production-grade inference framework, DeepInfer. According to Latent Space, the framework powers DeepSeek-V4.1-Flash, is customized based on vLLM, supports distributed inference, speculative decoding, SWA Bounded Replay, and structured output, and targets the NVIDIA SM100 and Huawei Ascend 950 platforms; the published single-cluster production figures are 155 trillion tokens processed per day, a 96% input cache hit rate, 4
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On October 20, 2026, DeepSeek announced the open-sourcing of its internal production-grade inference framework, DeepInfer. According to Latent Space, the framework powers DeepSeek-V4.1-Flash, is customized based on vLLM, supports distributed inference, speculative decoding, SWA Bounded Replay, and structured output, and targets the NVIDIA SM100 and Huawei Ascend 950 platforms; the published single-cluster production figures are 155 trillion tokens processed per day, a 96% input cache hit rate, 400 ms first-token latency, and a generation speed of 230 tokens/s. The report also noted that components such as KV cache management and load balancing have not yet been fully open-sourced. The next day, DeepSeek published the DeepInfer technical report on Zhihu, disclosing internal details including the hardware selection for Prefill and Decode and the KVCache targets, and providing data showing a single cluster serving 155 trillion Tokens/day at $38 per card per hour at off-peak prices. The framework is currently open-sourced, but the KV cache system, Prefill/Decode disaggregation, and load balancing required for a complete service are not fully included in this open-source project.
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View story:DeepSeek open-sources inference framework DeepInfer
On October 20, 2026, Foreign Ministry spokesperson Mao Ning, responding at a regular press conference to reports that the US government has asked its agencies to stop using artificial intelligence tools from Chinese companies such as DeepSeek, said that China consistently opposes overgeneralizing the concept of national security and politicizing science, technology, and economic and trade issues, and will resolutely safeguard the legitimate rights and interests of Chinese companies. On the same day, reports said that the US Department of Homeland Security had ordered the removal of DeepSeek-related technology from most government systems and barred civilian government agencies from using DeepSeek and any technology built with its models; the reports said the ban took effect at the end of July and that agencies under the Department of Defense are not covered. Other reports said the order, based on the 2018 Federal Acquisition Supply Chain Security Act, requires civilian agencies to remove DeepSeek and related products from their information technology systems, as well as third-party products and services developed using DeepSeek, with exceptions requiring an application submitted 60 days in advance with reasons stated.
Ning, responding at a regular press conference to reports that the US government has asked its agencies to stop using artificial intelligence tools from Chinese companies such as DeepSeek, said that China consistently opposes overgeneralizing the concept of national security and politicizing science, technology, and economic and trade issues, and will resolutely safeguard the legitimate rights and interests of Chinese companies. On the same day, reports said that the US Department of Homeland S
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On October 20, 2026, Foreign Ministry spokesperson Mao Ning, responding at a regular press conference to reports that the US government has asked its agencies to stop using artificial intelligence tools from Chinese companies such as DeepSeek, said that China consistently opposes overgeneralizing the concept of national security and politicizing science, technology, and economic and trade issues, and will resolutely safeguard the legitimate rights and interests of Chinese companies. On the same day, reports said that the US Department of Homeland Security had ordered the removal of DeepSeek-related technology from most government systems and barred civilian government agencies from using DeepSeek and any technology built with its models; the reports said the ban took effect at the end of July and that agencies under the Department of Defense are not covered. Other reports said the order, based on the 2018 Federal Acquisition Supply Chain Security Act, requires civilian agencies to remove DeepSeek and related products from their information technology systems, as well as third-party products and services developed using DeepSeek, with exceptions requiring an application submitted 60 days in advance with reasons stated.
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View story:Foreign Ministry responds to US demand to stop using DeepSeek
On October 20, 2026, DeepSeek open-sourced its internal inference framework DeepInfer. According to Yuchen Jin, citing data disclosed by DeepSeek, a single cluster processes 155 trillion tokens per day and generates $38 in revenue per GPU-hour (off-peak pricing); DeepInfer supports both NVIDIA Blackwell and Huawei Ascend. A subsequent 36Kr report stated that its accompanying open-source deepseek-recipe supports NVIDIA SM100 GPUs and Huawei Ascend 950 NPUs. On October 21, swyx, citing Latent.Space data, said a single cluster processes 155T tokens per day with a 96% input cache hit rate, and argued that the lifetime value of each sold GPU has risen by about 30%. On October 24, Nathan Lambert said DeepSeek's single cluster processes 150T tokens per day, exceeding the combined open-source model inference volume of OpenRouter, Fireworks, Together, and BaseTen, and noted that the actual number of clusters is unknown; on the same day, LMSYS published a same-hardware benchmark comparison, stating that SGLang meets or exceeds DeepInfer on DeepInfer's own benchmark, with prefill throughput up to 1.04x and decode step length shortened by 1.1%–7.4% on 64x GB300.
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View story:DeepSeek open-sources inference framework DeepInfer
On October 17, 2026, DeepSeek launched two APIs, Search and Fetch. According to TMTPost, these two interfaces are driven by a self-developed search engine, charging 5 yuan per 1,000 successful requests, with failed, no-result, or timed-out requests not billed; official billing starts on November 1; previously they were free to use in DeepSeek Harness, Claude Code, and Codex, each rate-limited to 5 requests per second. On October 18, DeepSeek issued an announcement stating that the DeepSeek API now supports web search and scraping, billed by number of requests at a unit price of 5 yuan per 1,000 successful requests; accessing the Search and Fetch interfaces via server-side tool calls in DeepSeek Harness, Claude Code, and Codex is currently not billed, and will be charged per request starting at 00:00 Beijing time on November 1, 2026. The announcement also explained that the Search interface returns structured results by query, and the Fetch interface scrapes a single web page and returns the title and body in Markdown; both are raw JSON APIs with the Base URL api.deepseek.com. Currently both interfaces are live, and billing has not yet started.
On October 17, 2026, DeepSeek launched two APIs, Search and Fetch. According to TMTPost, these two interfaces are driven by a self-developed search engine, charging 5 yuan per 1,000 successful requests, with failed, no-result, or timed-out requests not billed; official billing starts on November 1; previously they were free to use in DeepSeek Harness, Claude Code, and Codex, each rate-limited to 5 requests per second. On October 18, DeepSeek issued an announcement stating that the DeepSeek API n
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On October 17, 2026, DeepSeek released DeepSeek-V4.1-Flash-1017, which the company says delivers stronger benchmark performance, faster task completion, and shorter outputs, achieving a Pareto improvement in performance and cost; it is now available on the official website, App, and API, and the model also launched on OpenRouter the same day. The company also announced that the Search and Fetch APIs are open to everyone, priced at $0.75 per 1,000 calls per endpoint, with calls made through server-side tools in DeepSeek Harness, Claude Code, and Codex temporarily free, and billing starting at 16:00 UTC on October 31, 2026. On October 17, Thomas Wolf commented that DeepSeek called this a "minor update," yet Terminal-Bench 4.0 rose from 31.2 to 42.3. On October 19, Arena announced that the model, with a score of 1670, became the highest-ranked open-source model on Code Arena: WebDev. On October 20, OpenCode updated it to version 1017 in Go and Free; Unsloth released a GGUF that can run locally, with the 1-bit quantized version retaining about 88.2% accuracy and shrinking in size from 508GB to 250GB; Arena then announced that it topped the Agent Arena open-source model leaderboard.
On October 17, 2026, DeepSeek released DeepSeek-V4.1-Flash-1017, which the company says delivers stronger benchmark performance, faster task completion, and shorter outputs, achieving a Pareto improvement in performance and cost; it is now available on the official website, App, and API, and the model also launched on OpenRouter the same day. The company also announced that the Search and Fetch APIs are open to everyone, priced at $0.75 per 1,000 calls per endpoint, with calls made through serve
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On October 17, 2026, DeepSeek launched two APIs, Search and Fetch. According to TMTPost, these two interfaces are driven by a self-developed search engine, charging 5 yuan per 1,000 successful requests, with failed, no-result, or timed-out requests not billed; official billing starts on November 1; previously they were free to use in DeepSeek Harness, Claude Code, and Codex, each rate-limited to 5 requests per second. On October 18, DeepSeek issued an announcement stating that the DeepSeek API now supports web search and scraping, billed by number of requests at a unit price of 5 yuan per 1,000 successful requests; accessing the Search and Fetch interfaces via server-side tool calls in DeepSeek Harness, Claude Code, and Codex is currently not billed, and will be charged per request starting at 00:00 Beijing time on November 1, 2026. The announcement also explained that the Search interface returns structured results by query, and the Fetch interface scrapes a single web page and returns the title and body in Markdown; both are raw JSON APIs with the Base URL api.deepseek.com. Currently both interfaces are live, and billing has not yet started.
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On October 20, 2026, DeepSeek announced the open-sourcing of its internal production-grade inference framework, DeepInfer. According to Latent Space, the framework powers DeepSeek-V4.1-Flash, is customized based on vLLM, supports distributed inference, speculative decoding, SWA Bounded Replay, and structured output, and targets the NVIDIA SM100 and Huawei Ascend 950 platforms; the published single-cluster production figures are 155 trillion tokens processed per day, a 96% input cache hit rate, 400 ms first-token latency, and a generation speed of 230 tokens/s. The report also noted that components such as KV cache management and load balancing have not yet been fully open-sourced. The next day, DeepSeek published the DeepInfer technical report on Zhihu, disclosing internal details including the hardware selection for Prefill and Decode and the KVCache targets, and providing data showing a single cluster serving 155 trillion Tokens/day at $38 per card per hour at off-peak prices. The framework is currently open-sourced, but the KV cache system, Prefill/Decode disaggregation, and load balancing required for a complete service are not fully included in this open-source project.
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View story:DeepSeek open-sources inference framework DeepInfer