Search “DeepSeek”

Placeholder code for the V5 series appears in DeepSeek's official code repository

On October 28, 2026, Phoenix Technology reported that placeholder code for DeepSeek-V5, V5-open, V5-next, and others had appeared in the official DeepSeek Harness code repository, and that the official team had made advance preparations for the V5 series release. The report noted that these code entries are currently only placeholders; when released in the future, the server side will only need to modify /models to go live, with no client release required. Among them, V5-open follows a "no version threshold" path, while V5-next follows a "client upgrade required" path. On October 30, TMTPost·AGI further reported that these model names appeared in the test code of the official DeepSeek Harness GitHub repository, corresponding respectively to three release paths: unrecognized by the current client, usable directly on any version, and requiring a DSH upgrade to use. Among them, deepseek-v5-next requires a minimum version of 99.0.0-alpha.1, while the publicly available DSH version remains at 0.2.x. The report also stated that these entries were uploaded on September 24, 2026, by DSH core contributor Jiang Yichen. There is currently no official release information.

View story:Placeholder code for the V5 series appears in DeepSeek's official code repository

DeepSeek open-sources inference engine DeepInfer on GitHub

On October 29, 2026, DeepSeek open-sourced the inference engine DeepInfer on GitHub; this engine is the inference engine behind DeepSeek-V4.1-Flash. Leiphone reported the same day that DeepInfer includes technologies such as MoE expert parallelism, asynchronous batch scheduling, custom kernels, and speculative decoding, and disclosed that a single cluster needs to process approximately 155 trillion tokens per day. Its Zero-Overhead Batch Scheduler lets the CPU schedule computation one round in advance, overlapping with GPU forward passes, and handles cross-round state misalignment through total_inflight_tokens accounting, Remap mapping, and DeferredRelease deferred reclamation. Currently, only offline inference capabilities are open; components such as online KV Cache storage and cross-replica load balancing have not yet been fully disclosed, and the official team has not separately published end-to-end speedup data for this scheduling mechanism relative to synchronous solutions.

View story:DeepSeek open-sources the inference engine DeepInfer on GitHub

Cursor launches DeepSeek V4.1 Flash

Cursor announced that DeepSeek V4.1 Flash is now available in Cursor. According to the official statement, this model is at the cost frontier of CursorBench across all effort levels, with a cost of $0.60 to $0.98 per task, and no model scores higher. Users can enable it in Cursor Settings > Models. There are currently no further developments.

Cursor launches DeepSeek V4.1 Flash

Cursor announced that DeepSeek V4.1 Flash is now available in Cursor. According to the official statement, this model is at the cost frontier of CursorBench across all effort levels, with a cost of $0.60 to $0.98 per task, and no model scores higher. Users can enable it in Cursor Settings > Models. There are currently no further developments.

View story:Cursor launches DeepSeek V4.1 Flash

DeepSeek and MiniMax completed open-source and overseas licensing use registration

On October 16, 2026, China's Ministry of Commerce and Ministry of Science and Technology issued Announcement No. 48, soliciting public comments on revisions to the Catalog of Technologies Prohibited or Restricted from Export in China, proposing to add 40 technologies, 23 of which fall under artificial intelligence, covering advanced large models, AI agents, and large-scale computing clusters. The draft sets three thresholds for frontier model weights, with any one triggering restrictions: training compute of no less than 10^26 floating-point operations, parameter count of no less than 2 trillion, or ranking in the global top ten on indicators such as public benchmark rankings and global call volume at the time of export; high-performance agents intended for critical infrastructure, national defense, or core government uses are directly prohibited from export. The comment period for the newly added portions of the catalog runs until November 15, 2026, and the already-effective pre-export registration requirement applies immediately. On October 23, DeepSeek and MiniMax completed registration for open-source and overseas authorized use, and will continue to open-source their models.

View story:China's Ministry of Commerce and Ministry of Science and Technology plan to expand the export control technology catalog

Artificial Analysis ranks DeepSeek V4.1 Flash 1017 as the top open model

Artificial Analysis reports that Kimi K3.1 Pro scored 64% on the Artificial Analysis Cyber Index, ranking first among openly available models. The index consists of three benchmarks: CWE-Bench-AA, DeepsecBench-AA, and CyberGym-E2E-AA; K3.1 Pro scored 95% on CyberGym-E2E-AA, higher than GPT-6 Sol (Daybreak Blue)'s 93%. Its cost per task is $2.81, higher than GPT-6 Sol (Daybreak Blue, max)'s $1.77 and DeepSeek V4.1 Flash 1017's $0.42. Earlier the same day, Artificial Analysis ranked DeepSeek V4.1 Flash 1017 first among openly available models with a score of 57%, second on the overall leaderboard, 12 points behind GPT-6 Sol (69%), which is offered through a trusted access program; this version improved by 16 points over its predecessor DeepSeek V4.1 Flash's 41%, mainly due to CyberGym-E2E-AA rising from 23% to 76%.

View story:Artificial Analysis says Kimi K3.1 Pro scores 64% on the Cyber Index

Nathan Lambert says DeepSeek processes 150T tokens per day on a single cluster

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.

View story:DeepSeek open-sources inference framework DeepInfer

OpenClaw launches DeepSeek V4.1 Flash

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.

OpenClaw launches DeepSeek V4.1 Flash

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.

View story:OpenClaw launches DeepSeek V4.1 Flash

Token Pass includes DeepSeek v4.1 Flash

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.

View story:ARC Prize announces ARC-AGI verification results for DeepSeek V4.1 Flash 1017

DeepSeek open-sources inference framework DeepInfer

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.

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.

DeepSeek integrates Harness with the web, App, and open platform teams

On October 16, 2026, DeepSeek established a product department, integrating its four teams—Harness, Web, App, and Platform—under the leadership of Cui Tianyi, who comes from a quantitative trading background, to oversee product, design, and R&D. Related reports noted that DeepSeek Harness was open-sourced under the MIT license on August 13, and by mid-October the repository had accumulated about 250,000 GitHub stars; the official website has posted job openings for two directions: AI product manager and Agent Harness. The reports also mentioned that Guo Daya, a core contributor to R1, left in March 2026 to join ByteDance Seed because he believed the Agent direction was not a high priority within DeepSeek. Currently, this integration is coordinated by Cui Tianyi, and there are no further developments with supporting evidence at this time.

ARC Prize announces ARC-AGI verification results for DeepSeek V4.1 Flash 1017

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 announces the ARC-AGI verified score of DeepSeek V4.1 Flash 1017

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.

View story:ARC Prize announces ARC-AGI verification results for DeepSeek V4.1 Flash 1017

DeepSeek integrates the Harness team with the web, App, and open platform teams

On October 16, 2026, DeepSeek established a product department, integrating its four teams—Harness, Web, App, and Platform—under the leadership of Cui Tianyi, who comes from a quantitative trading background, to oversee product, design, and R&D. Related reports noted that DeepSeek Harness was open-sourced under the MIT license on August 13, and by mid-October the repository had accumulated about 250,000 GitHub stars; the official website has posted job openings for two directions: AI product manager and Agent Harness. The reports also mentioned that Guo Daya, a core contributor to R1, left in March 2026 to join ByteDance Seed because he believed the Agent direction was not a high priority within DeepSeek. Currently, this integration is coordinated by Cui Tianyi, and there are no further developments with supporting evidence at this time.

View story:DeepSeek integrates Harness with the web, App, and open platform teams

Report: DeepSeek raises about 100 billion yuan in new funding round

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.

Report: DeepSeek's new funding round raises about 100 billion yuan

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.

View story:Report: DeepSeek raises about 100 billion yuan in new funding round

Artificial Analysis includes DeepSeek Search in 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.

View story:Artificial Analysis Adds DeepSeek Search to Its Search Index Evaluation

DeepSeek open-sources inference framework DeepInfer

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.