# M3.1 Flash

Published articles for M3.1 Flash.

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## MiniMax M3.1 Flash vs. MiniMax M3: One is cheaper, but not faster or better

DevFeed: [MiniMax M3.1 Flash vs. MiniMax M3: One is cheaper, but not faster or better](<https://devfeed.tech/articles/minimax-m3-1-flash-vs-minimax-m3-one-is-cheaper-but-not-faster-or-better-100704.md>)

Original publisher: [Read original article](<https://thenewstack.io/minimax-flash-agent-tests/>)

Author: Jessica Wachtel

Published: 2026-10-26T13:30:00Z

Content type: comparison

Language: en

Sources: [The New Stack](<https://devfeed.tech/sources/the-new-stack.md>)

Topics: [Benchmark](<https://devfeed.tech/topics/benchmark.md>), [Cache](<https://devfeed.tech/topics/cache.md>), [Test automation](<https://devfeed.tech/topics/test-automation.md>)

Tags: [2026](<https://devfeed.tech/tags/2026.md>), [agent-tasks](<https://devfeed.tech/tags/agent-tasks.md>), [agentic](<https://devfeed.tech/tags/agentic.md>), [agentic-tasks](<https://devfeed.tech/tags/agentic-tasks.md>), [ai-agents](<https://devfeed.tech/tags/ai-agents.md>), [ai-models](<https://devfeed.tech/tags/ai-models.md>), [artificial-analysis](<https://devfeed.tech/tags/artificial-analysis.md>), [automationbench](<https://devfeed.tech/tags/automationbench.md>), [benchmark](<https://devfeed.tech/tags/benchmark.md>), [cost](<https://devfeed.tech/tags/cost.md>), [large-language-models](<https://devfeed.tech/tags/large-language-models.md>), [m3](<https://devfeed.tech/tags/m3.md>), [m3-1-flash](<https://devfeed.tech/tags/m3-1-flash.md>), [minimax](<https://devfeed.tech/tags/minimax.md>), [minimax-m3-1-flash](<https://devfeed.tech/tags/minimax-m3-1-flash.md>), [october](<https://devfeed.tech/tags/october.md>), [software-testing](<https://devfeed.tech/tags/software-testing.md>), [vs](<https://devfeed.tech/tags/vs.md>)

### AI overview

MiniMax M3.1 Flash cost less than M3 in the author's three one-off tests, but did not show a clear overall improvement: it was slower overall, tied M3 on both graded tasks, and neither model reliably answered the long-context task. In a tool-based bug fix, Flash corrected all three bugs but used its 25-turn limit before reporting a wrong test; M3 finished faster but missed a case. In an incident investigation, both scored 10/10, while Flash completed in fewer turns and at lower estimated cost. Flash's first long-context run exhausted the output allowance; with a lower limit it answered only 3 of 33 affected services, while M3 again failed to answer. Costs were estimates at list prices, and results came from one run per task through OpenRouter, so they do not establish general performance or cost differences.

### Source excerpt

MiniMax released M3.1 Flash on October 19, 2026, and says it cuts the overall cost of agentic tasks by 70% The post MiniMax M3.1 Flash vs. MiniMax M3: One is cheaper, but not faster or better appeared first on The New Stack.

## MiniMax M3.1 Flash Now Available on SambaCloud

DevFeed: [MiniMax M3.1 Flash Now Available on SambaCloud](<https://devfeed.tech/articles/minimax-m3-1-flash-now-available-on-sambacloud-98650.md>)

Original publisher: [Read original article](<https://sambanova.ai/blog/minimax-m3.1-flash-now-available-on-sambacloud>)

Author: SambaNova

Published: 2026-10-24T03:19:34Z

Content type: release

Language: en

Sources: [Sambanova](<https://devfeed.tech/sources/sambanova.md>)

Topics: [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [agentic-coding](<https://devfeed.tech/topics/agentic-coding.md>), [LLM evaluation / benchmarking](<https://devfeed.tech/topics/llm-evaluation-benchmarking.md>), [LLM optimization](<https://devfeed.tech/topics/llm-optimization.md>), [Cybersecurity](<https://devfeed.tech/topics/cybersecurity.md>), [AI-assisted coding](<https://devfeed.tech/topics/ai-assisted-coding.md>), [Loop Engineering](<https://devfeed.tech/topics/loop-engineering.md>), [Frontier AI](<https://devfeed.tech/topics/frontier-ai.md>)

Tags: [agentic](<https://devfeed.tech/tags/agentic.md>), [agentic-tasks](<https://devfeed.tech/tags/agentic-tasks.md>), [agents](<https://devfeed.tech/tags/agents.md>), [benchmarks](<https://devfeed.tech/tags/benchmarks.md>), [blog](<https://devfeed.tech/tags/blog.md>), [coding](<https://devfeed.tech/tags/coding.md>), [computer-use](<https://devfeed.tech/tags/computer-use.md>), [cost](<https://devfeed.tech/tags/cost.md>), [cybergym](<https://devfeed.tech/tags/cybergym.md>), [cybersecurity](<https://devfeed.tech/tags/cybersecurity.md>), [deepswe-v1-1](<https://devfeed.tech/tags/deepswe-v1-1.md>), [faster](<https://devfeed.tech/tags/faster.md>), [inference](<https://devfeed.tech/tags/inference.md>), [long-running-agents](<https://devfeed.tech/tags/long-running-agents.md>), [m3-1-flash](<https://devfeed.tech/tags/m3-1-flash.md>), [minimax](<https://devfeed.tech/tags/minimax.md>), [minimax-m3-1-flash](<https://devfeed.tech/tags/minimax-m3-1-flash.md>), [model](<https://devfeed.tech/tags/model.md>), [osworld](<https://devfeed.tech/tags/osworld.md>), [osworld-v2](<https://devfeed.tech/tags/osworld-v2.md>), [performance](<https://devfeed.tech/tags/performance.md>)

### AI overview

MiniMax M3.1 Flash is available on SambaCloud at over 200 tokens/s, with the source reporting nearly 3x faster inference and 70% lower usage costs than its predecessor. It highlights results of 73.7% on DeepSWE v1.1, 61.7 on OSWorld V2, and 82% on CyberGym, alongside claims of strong performance in enterprise workflow automation, coding, computer use, and cybersecurity. The source describes DeepSWE as testing independent codebase work and validation, and OSWorld V2 as measuring computer operation across applications. MiniMax M3 requests on SambaCloud are being rerouted to M3.1 Flash; callers are asked to change the model string to `MiniMax-M3.1-Flash`. The supplied text includes a Python API example for making a chat completion request.

### Source excerpt

Frontier Agentic Performance at a Fraction of the Cost. Build Fast, Cheap, Long-Running Agents on SambaCloud MiniMax M3.1 Flash is the next-generation Flash model from MiniMax, built for agentic tasks, coding, computer use, and cybersecurity. It delivers a generational leap in capability over its predecessor while making inference nearly 3x faster and cutting usage costs by 70%. It hits 73.7% on DeepSWE v1.1, 61.7 on OSWorld V2, and 82% on CyberGym, placing it alongside top models on the benchmarks that matter for real-world agents.

## vLLM Delivers Day-0 Support for MiniMax-M3.1-Flash

DevFeed: [vLLM Delivers Day-0 Support for MiniMax-M3.1-Flash](<https://devfeed.tech/articles/vllm-delivers-day-0-support-for-minimax-m3-1-flash-96723.md>)

Original publisher: [Read original article](<https://vllm.ai/blog/2026-10-23-minimax-m31-flash>)

Author: Inferact and the vLLM Team

Published: 2026-10-23T00:00:00Z

Content type: release

Language: en

Sources: [vLLM Blog](<https://devfeed.tech/sources/vllm-blog.md>)

Topics: [vllm](<https://devfeed.tech/topics/vllm.md>), [Model Optimizer](<https://devfeed.tech/topics/model-optimizer.md>), [NVFP4](<https://devfeed.tech/topics/nvfp4.md>), [quantization](<https://devfeed.tech/topics/quantization.md>), [rocm](<https://devfeed.tech/topics/rocm.md>), [NVIDIA Vera Rubin](<https://devfeed.tech/topics/nvidia-vera-rubin.md>)

Tags: [ai-engineering](<https://devfeed.tech/tags/ai-engineering.md>), [amd](<https://devfeed.tech/tags/amd.md>), [blackwell](<https://devfeed.tech/tags/blackwell.md>), [day-0-support](<https://devfeed.tech/tags/day-0-support.md>), [decoding](<https://devfeed.tech/tags/decoding.md>), [dspark](<https://devfeed.tech/tags/dspark.md>), [flash](<https://devfeed.tech/tags/flash.md>), [gpus](<https://devfeed.tech/tags/gpus.md>), [hardware](<https://devfeed.tech/tags/hardware.md>), [kernels](<https://devfeed.tech/tags/kernels.md>), [llm-inference](<https://devfeed.tech/tags/llm-inference.md>), [m3](<https://devfeed.tech/tags/m3.md>), [m3-1-flash](<https://devfeed.tech/tags/m3-1-flash.md>), [minimax](<https://devfeed.tech/tags/minimax.md>), [minimax-m3-1-flash](<https://devfeed.tech/tags/minimax-m3-1-flash.md>), [model-serving](<https://devfeed.tech/tags/model-serving.md>), [nvfp4](<https://devfeed.tech/tags/nvfp4.md>), [nvidia](<https://devfeed.tech/tags/nvidia.md>), [nvidia-blackwell](<https://devfeed.tech/tags/nvidia-blackwell.md>), [nvidia-rubin](<https://devfeed.tech/tags/nvidia-rubin.md>), [open-source-ai](<https://devfeed.tech/tags/open-source-ai.md>), [performance](<https://devfeed.tech/tags/performance.md>), [rl](<https://devfeed.tech/tags/rl.md>), [series](<https://devfeed.tech/tags/series.md>), [support](<https://devfeed.tech/tags/support.md>), [vllm](<https://devfeed.tech/tags/vllm.md>), [vllm-blog](<https://devfeed.tech/tags/vllm-blog.md>)

### AI overview

vLLM provides day-0 MiniMax-M3.1-Flash support on NVIDIA Blackwell and Rubin and AMD MI350-series GPUs, with NVFP4 KV cache and MoE support, DSpark speculative decoding, and RL training from the NVFP4 checkpoint. The model's sparse attention selects at most 16 blocks of 128 tokens per query, limiting attention to 2,048 keys; the article estimates long-context decode HBM traffic at about 12.5% of dense attention. On four B300s, NVFP4 reduces checkpoint size 44.6% and KV-cache bytes per token 43.75%; at 256K context, the stated deployment fits 76 sequences versus 28 for the prior model's FP8 cache. Hardware-specific optimizations include CUDA 13.4 QMUL4 kernels on Blackwell, distinct MSA kernels on Rubin, and table-based NVFP4 conversion, context parallelism, and fused low-latency decoding on AMD. Reported AgentX results vary by platform and metric: Rubin reaches 724.9 tokens/s per user at the latency-sensitive frontier, while AMD MI355X reaches 133.3M total tokens per dollar at the cost-efficient frontier. Day-0 RL uses veRL, FSDP2, rank-32 LoRA, and token-level importance sampling; a 16-GB300, 200-step run raises AIME-2024 accuracy from 36.3% to 67.5%. Prebuilt NVIDIA and AMD vLLM-

### Source excerpt

Day-0 vLLM support for MiniMax-M3.1-Flash on NVIDIA Blackwell, NVIDIA Rubin, and AMD MI350-series GPUs, with NVFP4 MSA kernels, NVFP4 MegaMoE, DSpark speculative decoding, AgentX results, and day-0 RL.

## MiniMax launches M3.1 Flash model, says it cuts AI agent costs by 70%

DevFeed: [MiniMax launches M3.1 Flash model, says it cuts AI agent costs by 70%](<https://devfeed.tech/articles/minimax-launches-m3-1-flash-model-says-it-cuts-ai-agent-costs-by-70-90485.md>)

Original publisher: [Read original article](<https://siliconangle.com/2026/10/19/minimax-launches-m3-1-flash-model-says-it-cuts-ai-agent-costs-by-70/>)

Author: Duncan Riley

Published: 2026-10-19T22:25:50Z

Content type: news

Language: en

Sources: [SiliconANGLE](<https://devfeed.tech/sources/siliconangle.md>)

Topics: [LLM optimization](<https://devfeed.tech/topics/llm-optimization.md>), [Artificial Intelligence](<https://devfeed.tech/topics/ai.md>), [Large Language Model](<https://devfeed.tech/topics/llm.md>), [AI Agent](<https://devfeed.tech/topics/ai-agent.md>), [LLM evaluation / benchmarking](<https://devfeed.tech/topics/llm-evaluation-benchmarking.md>), [AI Chat](<https://devfeed.tech/topics/ai-chat.md>)

Tags: [agent](<https://devfeed.tech/tags/agent.md>), [agent-costs](<https://devfeed.tech/tags/agent-costs.md>), [agentic-tasks](<https://devfeed.tech/tags/agentic-tasks.md>), [ai](<https://devfeed.tech/tags/ai.md>), [ai-agents](<https://devfeed.tech/tags/ai-agents.md>), [api](<https://devfeed.tech/tags/api.md>), [bankertoolbench](<https://devfeed.tech/tags/bankertoolbench.md>), [benchmark](<https://devfeed.tech/tags/benchmark.md>), [berkeley](<https://devfeed.tech/tags/berkeley.md>), [cybergym](<https://devfeed.tech/tags/cybergym.md>), [cybersecurity](<https://devfeed.tech/tags/cybersecurity.md>), [deepseek](<https://devfeed.tech/tags/deepseek.md>), [deepswe](<https://devfeed.tech/tags/deepswe.md>), [hangzhou-deepseek](<https://devfeed.tech/tags/hangzhou-deepseek.md>), [hong-kong](<https://devfeed.tech/tags/hong-kong.md>), [inference](<https://devfeed.tech/tags/inference.md>), [initial-public-offering](<https://devfeed.tech/tags/initial-public-offering.md>), [large-language-model](<https://devfeed.tech/tags/large-language-model.md>), [large-language-models](<https://devfeed.tech/tags/large-language-models.md>), [m-plan](<https://devfeed.tech/tags/m-plan.md>), [m3](<https://devfeed.tech/tags/m3.md>), [m3-1-flash](<https://devfeed.tech/tags/m3-1-flash.md>), [minimax](<https://devfeed.tech/tags/minimax.md>), [minimax-code](<https://devfeed.tech/tags/minimax-code.md>), [model-weights](<https://devfeed.tech/tags/model-weights.md>), [news](<https://devfeed.tech/tags/news.md>), [openrouter](<https://devfeed.tech/tags/openrouter.md>), [osworld-v2](<https://devfeed.tech/tags/osworld-v2.md>), [reasoning](<https://devfeed.tech/tags/reasoning.md>), [release](<https://devfeed.tech/tags/release.md>), [space-bunny](<https://devfeed.tech/tags/space-bunny.md>), [sparsity](<https://devfeed.tech/tags/sparsity.md>), [the-latest](<https://devfeed.tech/tags/the-latest.md>), [top-story-3](<https://devfeed.tech/tags/top-story-3.md>), [top-story-6](<https://devfeed.tech/tags/top-story-6.md>), [university-of-california](<https://devfeed.tech/tags/university-of-california.md>), [v4-1-flash](<https://devfeed.tech/tags/v4-1-flash.md>)

### AI overview

MiniMax released M3.1 Flash, a faster, lower-cost update to its M3 large language model aimed at reducing the cost of running AI agents. The company reports 70% lower agentic-task costs and inference speeds close to three times faster than its previous model, along with benchmark results for computer operation, banking workflows, cybersecurity, and software engineering. The model is available through MiniMax's API, subscription plan, and desktop app; the company says it plans to release the weights later.

### Source excerpt

Chinese artificial intelligence developer MiniMax Group Inc. today released M3.1 Flash, a faster and cheaper update to the M3 large language model it launched in June. The release takes aim at the cost of running AI agents, which often need dozens of model calls to finish a single job. MiniMax said Flash represents its "ongoing [...] The post MiniMax launches M3.1 Flash model, says it cuts AI agent costs by 70% appeared first on SiliconANGLE.