MiniMax announced that M3.1 Flash gained support on Ollama on its first day of launch, with the model hosted in the US with zero data retention and ready for direct use in agent development. Ollama said the model supports image understanding and a 1M-token context window, is suited to fast coding and agentic workflows, and provided the commands for calling it on Ollama Cloud as well as in Claude Code and Codex.
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MiniMax announced that M3.1 Flash is now live on Cline and free to use, targeting agentic coding tasks that take a long time and where costs add up quickly. MiniMax thanked Cline for completing integration on launch day and recommends users try it on their most complex repositories.
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MiniMax announced that M3.1 Flash (also known as Space Bunny) is now available on GMI Cloud, and thanked the company for completing integration on day0. According to GMI Cloud, the model is designed for coding, agentic workflows, and computer use, cutting agentic task costs by 70%, scoring 73.7% on DeepSWE v1.1 and 82% on CyberGym.
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MiniMax officially confirmed that M3.1 Flash (also known as Space Bunny) is now live on Command Code and free for a limited time for all subscribers. According to Command Code, the model supports a 1M token context window, delivers frontier-level coding capabilities, and is available to users on all plans and subscriptions.
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Ant inclusionAI has open-sourced Ming-3.0-asr-tiny on GitHub, combining the Ling-tiny-v3 language model with an audio encoder to support Chinese-English transcription, dialect recognition, and Context ASR. Dialect evaluation covers 15 test sets including Hunan, Minnan, Cantonese, and Sichuan-Chongqing; Context ASR can recognize proper nouns via hotwords in prompts or preceding dialogue. The inference stack uses Transformers 5.12.1, fla-core 0.5.2, and PyTorch 2.11.0, and provides an SGLang accelerated deployment example.
Ant inclusionAI has open-sourced Ming-3.0-asr-tiny on GitHub, combining the Ling-tiny-v3 language model with an audio encoder to support Chinese-English transcription, dialect recognition, and Context ASR. Dialect evaluation covers 15 test sets including Hunan, Minnan, Cantonese, and Sichuan-Chongqing; Context ASR can recognize proper nouns via hotwords in prompts or preceding dialogue. The inference stack uses Transformers 5.12.1, fla-core 0.5.2, and PyTorch 2.11.0, and provides an SGLang accel
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Memory Tensor has open-sourced the MemT 1.0 series of memory-native models, comprising two variants: Nano with 36B parameters and 3B activated, and Flash with 288B parameters and 17B activated, built on the Qwen3.6-35B-A3B and DeepSeek-V4-Flash bases, respectively. The models add a memory branch parallel to attention within selected Transformer modules, encoding experience into an updatable matrix state that participates in subsequent generation. Across 500 SWE-bench Verified tasks, Nano achieved an average success rate of 69.73% at key checkpoints, versus a no-experience baseline of 66.07%; under a 128K long history, end-to-end inference speed is approximately 1.86 times that of the full-context approach, and the persistent state footprint per trajectory is one sixty-sixth that of the full-context KV Cache.
Memory Tensor has open-sourced the MemT 1.0 series of memory-native models, comprising two variants: Nano with 36B parameters and 3B activated, and Flash with 288B parameters and 17B activated, built on the Qwen3.6-35B-A3B and DeepSeek-V4-Flash bases, respectively. The models add a memory branch parallel to attention within selected Transformer modules, encoding experience into an updatable matrix state that participates in subsequent generation. Across 500 SWE-bench Verified tasks, Nano achieve
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Meta's open-weight model Muse Spark Open is available on Fireworks from day one of launch. It is an 816B-parameter MoE model that activates 42B parameters per token, with a 1M-token context window, targeting long-horizon coding and agentic tasks. Fireworks says it ranks first among 75 models on Vals AI's Harvey legal agent benchmark with 25.4%, nearly 4 times that of Claude Opus 5 (6.7%); on the Rogo Big Finance Bench it surpasses Claude Opus 5.5 at every difficulty level. Fireworks validated the weights with its own production stack, scoring 91.1% on AIME26, 89.7% on GPQA Diamond, and 84.3% on SWE-bench Verified, and reproduced consistent results with SGLang.
Meta's open-weight model Muse Spark Open is available on Fireworks from day one of launch. It is an 816B-parameter MoE model that activates 42B parameters per token, with a 1M-token context window, targeting long-horizon coding and agentic tasks. Fireworks says it ranks first among 75 models on Vals AI's Harvey legal agent benchmark with 25.4%, nearly 4 times that of Claude Opus 5 (6.7%); on the Rogo Big Finance Bench it surpasses Claude Opus 5.5 at every difficulty level. Fireworks validated th
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Vercel Developers announced that MiniMax M3.1 Flash is now live on AI Gateway and available for free, under the call name minimax/minimax-m3.1-flash. The model performs better at agentic tasks, coding, and cybersecurity, and is free through October 22 when served by MiniMax. Guillermo Rauch reposted the news and said, "More free AI."
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MiniMax officially claimed Space Bunny, a model tested anonymously on an overseas blind-test platform, confirming it as MiniMax-M3.1-Flash. The model supports a generation speed on the order of one hundred words per second and a one-million-token context; community tests measured generation speed steady at 85 to 112 words per second, capable of running through complex 3D scenes and code builds in a single pass within three minutes, and achieving near-imperceptible response in multi-file project repairs. The author believes this approach of anonymous blind testing first and public claiming afterward turns inference speed and million-token context into efficiency tools usable for everyday coding.
MiniMax officially claimed Space Bunny, a model tested anonymously on an overseas blind-test platform, confirming it as MiniMax-M3.1-Flash. The model supports a generation speed on the order of one hundred words per second and a one-million-token context; community tests measured generation speed steady at 85 to 112 words per second, capable of running through complex 3D scenes and code builds in a single pass within three minutes, and achieving near-imperceptible response in multi-file project
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According to the Vercel Developers account, AI Gateway logs can now show each agent session, grouping requests by conversation and displaying cost, cache hit rate, and the agent that ran the session; session affinity pins each session to the provider that holds its prompt cache. Guillermo Rauch reposted and praised this unified view, saying it covers personal and coding agents, apps, and API keys, and emphasized that Vercel AI Gateway gives users control over model choice, data (ZDR), and the metadata needed to understand RoI.
According to the Vercel Developers account, AI Gateway logs can now show each agent session, grouping requests by conversation and displaying cost, cache hit rate, and the agent that ran the session; session affinity pins each session to the provider that holds its prompt cache. Guillermo Rauch reposted and praised this unified view, saying it covers personal and coding agents, apps, and API keys, and emphasized that Vercel AI Gateway gives users control over model choice, data (ZDR), and the me
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Peter Yang said Tim Sweeney is right, and hopes the developers working on StarCraft 3 see this tweet and use AI to finish and release it before 2030. In the quoted post, Tim Sweeney recalled that when developing Unreal Engine 1, about 30% of his time went to hardcore coding, and 70% to typing code and refactoring; he believes handing the latter to AI is only natural, and was surprised that AI can also solve hard technical problems like "insta-Carmack" and understand complex 3D scenes.
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Anthropic released a report stating that by August 2026, the working hours of interactive AI agents deployed by employees had reached 6 times that of human employees, and in March, the company-wide total agent work hours exceeded human work hours for the first time. The report shows that the share of junior employees in the technology department fell from 21% in early 2025 to 14%, the share of junior tech job openings fell from 27% to 9%, and engineers using coding agents averaged 5 times as many code commits as they did 6 months earlier. The report also says its revenue per employee is 2 to 4 times that of Meta and Google during their high-growth periods, but Epoch AI cautions that the related estimates carry uncertainty.
Anthropic released a report stating that by August 2026, the working hours of interactive AI agents deployed by employees had reached 6 times that of human employees, and in March, the company-wide total agent work hours exceeded human work hours for the first time. The report shows that the share of junior employees in the technology department fell from 21% in early 2025 to 14%, the share of junior tech job openings fell from 27% to 9%, and engineers using coding agents averaged 5 times as man
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