BenchmarksToday
minimax-m2.5 - SWE-Bench Verified
SWE-Bench Verified resolved rate 75.8
View sourceMiniMax
MiniMax reasoning and coding model family tuned for agentic software workflows and long-context production runs, with open weights for private cluster deployment.
Running this yourself: likely needs a high-memory cloud gpu.
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57.6
Quality Score
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Arena ELO
229B
Parameters
197K
Context
This measures the amount of verifiable public evidence we have, not how capable the model is. A missing field means it has not been verified yet, not that its value is zero.
18 of 22 public signals
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382.1K
Downloads
1.5K
Likes
Feb 2026
Released
4/5 signals
3/4 signals
4/5 signals
3/4 signals
4/4 signals
Parameters
229B
Training compute
Not reported
Dataset scale
Not reported
Base model
Not reported
Source-reported access: Open weights (unrestricted) · Likely confidence
Gaps we are still tracking
Benchmarks
9
API
1
Open Source
2
Research
2
General
2
Recent launch, pricing, benchmark, and API signals linked to this model or its provider.
SWE-Bench Verified resolved rate 75.8
View sourceMiniMax M2.5 - SOTA in Coding and Agent, Designed for Agent Universe | MiniMax Models LLM MiniMax M3 MiniMax M2.7 MiniMax M2.5 VIDEO MiniMax H3 SPEECH & MUSIC MiniMax Speech 2.8 MiniMax Music 3.0 Product MiniMax Code MiniMax Design Audio Talkie API Plan Research Company Intelligence with everyone About News Investor Relations Contact Us Models LLM MiniMax M3 NEW MiniMax M2.7 MiniMax M2.5 VIDEO MiniMax H3 NEW SPEECH & MUSIC MiniMax Speech 2.8 NEW MiniMax Music 3.0 NEW
MiniMax M2.5 - SOTA in Coding and Agent, Designed for Agent Universe | MiniMax Models LLM MiniMax M3 MiniMax M2.7 MiniMax M2.5 VIDEO MiniMax H3 SPEECH & MUSIC MiniMax Speech 2.8 MiniMax Music 3.0 Product MiniMax Code MiniMax Design Audio Talkie API Plan Research Company Intelligence with everyone About News Investor Relations Contact Us Models LLM MiniMax M3 NEW MiniMax M2.7 MiniMax M2.5 VIDEO MiniMax H3 NEW SPEECH & MUSIC MiniMax Speech 2.8 NEW MiniMax Music 3.0 NEW
View sourceMiniMax M2.5 - SOTA in Coding and Agent, Designed for Agent Universe | MiniMax Models LLM MiniMax M3 MiniMax M2.7 MiniMax M2.5 VIDEO MiniMax H3 SPEECH & MUSIC MiniMax Speech 2.8 MiniMax Music 3.0 Product MiniMax Code MiniMax Design Audio Talkie API Plan Research Company Intelligence with everyone About News Investor Relations Contact Us Models LLM MiniMax M3 NEW MiniMax M2.7 MiniMax M2.5 VIDEO MiniMax H3 NEW SPEECH & MUSIC MiniMax Speech 2.8 NEW MiniMax Music 3.0 NEW
View sourceMiniMax M2.5 - SOTA in Coding and Agent, Designed for Agent Universe | MiniMax Models LLM MiniMax M3 MiniMax M2.7 MiniMax M2.5 VIDEO MiniMax H3 SPEECH & MUSIC MiniMax Speech 2.8 MiniMax Music 3.0 Product MiniMax Code MiniMax Design Audio Talkie API Plan Research Company Intelligence with everyone About News Investor Relations Contact Us Models LLM MiniMax M3 NEW MiniMax M2.7 MiniMax M2.5 VIDEO MiniMax H3 NEW SPEECH & MUSIC MiniMax Speech 2.8 NEW MiniMax Music 3.0 NEW
View sourceLarge language models (LLMs) and agentic systems have shown promise for clinical decision support, but existing works largely assume that evidence has already been curated and handed to the model. Real-world clinical workflows instead require agents to actively seek, iteratively plan, and synthesize multimodal evidence from heterogeneous sources. In this paper, we introduce ClinSeekAgent, an automated agentic framework for dynamic multimodal evidence seeking that shifts the paradigm from passive evidence consumption to active evidence acquisition. Given only a clinical query and access to raw data sources, ClinSeekAgent gathers evidence by querying medical knowledge bases, navigating raw EHRs, and invoking medical imaging tools; refines its hypotheses as new information emerges; and integrates the collected evidence into grounded clinical decisions. ClinSeekAgent serves both as an inference-time agent for frontier LLMs and as a training-time pipeline for distilling high-quality agent trajectories into compact open-source models. To validate its inference-time effectiveness, we construct ClinSeek-Bench, which pairs Curated Input reasoning from fixed pre-selected evidence with Automated Evidence-Seeking over raw clinical data. On text-only EHR tasks, ClinSeekAgent improves Claude Opus 4.6 from 60.0 to 63.2 overall F1 and MiniMax M2.5 from 43.1 to 47.3, with positive risk-prediction gains in 7 out of 9 evaluated host models. On multimodal tasks, ClinSeekAgent improves Claude Opus 4.6 from 47.5 to 62.6 (+15.1); all evaluated models improve across the three CXR-related task groups. We further validate ClinSeekAgent as a training pipeline by distilling agentic evidence-seeking trajectories into ClinSeek-35B-A3B, which achieves 34.0 average F1 on existing AgentEHR-Bench, improving over its Qwen3.5-35B-A3B baseline by +11.9 points and approaching Claude Opus 4.6.
We study parallel test-time scaling for long-horizon agentic tasks such as agentic search and deep research, where multiple rollouts are generated in parallel and aggregated into a final response. While such scaling has proven effective for chain-of-thought reasoning, agentic tasks pose unique challenges: trajectories are long, multi-turn, and tool-augmented, and outputs are often open-ended. Aggregating only final answers discards rich information from trajectories, while concatenating all trajectories exceeds the model's context window. To address this, we propose AggAgent, an aggregation agent that treats parallel trajectories as an environment. We equip it with lightweight tools to inspect candidate solutions and search across trajectories, enabling it to navigate and synthesize information on demand. Across six benchmarks and three model families (GLM-4.7, Qwen3.5, MiniMax-M2.5), AggAgent outperforms all existing aggregation methods-by up to 5.3% absolute on average and 10.3% on two deep research tasks-while adding minimal overhead, as the aggregation cost remains bounded by a single agentic rollout. Our findings establish agentic aggregation as an effective and cost-efficient approach to parallel test-time scaling.
Designed for high-throughput, low-latency production environments. M2.5 delivers industry-leading coding and reasoning capabilities at a fraction of the cost.
MiniMax says the M2 family is open-sourced with official self-host guidance for private deployment using runtimes like vLLM and SGLang.
SWE-Bench Verified resolved rate 75.8
MiniMax M2.5 - SOTA in Coding and Agent, Designed for Agent Universe | MiniMax Models LLM MiniMax M3 MiniMax M2.7 MiniMax M2.5 VIDEO MiniMax H3 SPEECH & MUSIC MiniMax Speech 2.8 MiniMax Music 3.0 Product MiniMax Code MiniMax Design Audio Talkie API Plan Research Company Intelligence with everyone About News Investor Relations Contact Us Models LLM MiniMax M3 NEW MiniMax M2.7 MiniMax M2.5 VIDEO MiniMax H3 NEW SPEECH & MUSIC MiniMax Speech 2.8 NEW MiniMax Music 3.0 NEW
MiniMax M2.5 - SOTA in Coding and Agent, Designed for Agent Universe | MiniMax Models LLM MiniMax M3 MiniMax M2.7 MiniMax M2.5 VIDEO MiniMax H3 SPEECH & MUSIC MiniMax Speech 2.8 MiniMax Music 3.0 Product MiniMax Code MiniMax Design Audio Talkie API Plan Research Company Intelligence with everyone About News Investor Relations Contact Us Models LLM MiniMax M3 NEW MiniMax M2.7 MiniMax M2.5 VIDEO MiniMax H3 NEW SPEECH & MUSIC MiniMax Speech 2.8 NEW MiniMax Music 3.0 NEW
MiniMax M2.5 - SOTA in Coding and Agent, Designed for Agent Universe | MiniMax Models LLM MiniMax M3 MiniMax M2.7 MiniMax M2.5 VIDEO MiniMax H3 SPEECH & MUSIC MiniMax Speech 2.8 MiniMax Music 3.0 Product MiniMax Code MiniMax Design Audio Talkie API Plan Research Company Intelligence with everyone About News Investor Relations Contact Us Models LLM MiniMax M3 NEW MiniMax M2.7 MiniMax M2.5 VIDEO MiniMax H3 NEW SPEECH & MUSIC MiniMax Speech 2.8 NEW MiniMax Music 3.0 NEW
MiniMax M2.5 - SOTA in Coding and Agent, Designed for Agent Universe | MiniMax Models LLM MiniMax M3 MiniMax M2.7 MiniMax M2.5 VIDEO MiniMax H3 SPEECH & MUSIC MiniMax Speech 2.8 MiniMax Music 3.0 Product MiniMax Code MiniMax Design Audio Talkie API Plan Research Company Intelligence with everyone About News Investor Relations Contact Us Models LLM MiniMax M3 NEW MiniMax M2.7 MiniMax M2.5 VIDEO MiniMax H3 NEW SPEECH & MUSIC MiniMax Speech 2.8 NEW MiniMax Music 3.0 NEW
MiniMax M2.5 - SOTA in Coding and Agent, Designed for Agent Universe | MiniMax Models LLM MiniMax M3 MiniMax M2.7 MiniMax M2.5 VIDEO MiniMax H3 SPEECH & MUSIC MiniMax Speech 2.8 MiniMax Music 3.0 Product MiniMax Code MiniMax Design Audio Talkie API Plan Research Company Intelligence with everyone About News Investor Relations Contact Us Models LLM MiniMax M3 NEW MiniMax M2.7 MiniMax M2.5 VIDEO MiniMax H3 NEW SPEECH & MUSIC MiniMax Speech 2.8 NEW MiniMax Music 3.0 NEW
MiniMax-M2.5 is now available through Ollama Cloud. 198K context window listed. MiniMax-M2.5 is a state-of-the-art large language model designed for real-world productivity and coding tasks.
SWE-Bench Verified resolved rate 75.8
MiniMax 开源新评测集：定义Coding Agent 的生产级标准 - MiniMax News | MiniMax 模型 语言模型 MiniMax M3 MiniMax M2.7 MiniMax M2.5 视频生成 MiniMax H3 语音&音乐 MiniMax Speech 2.8 MiniMax Music 3.0 产品 MiniMax Code MiniMax Design 语音 星野 API 订阅 研究 关于我们 与所有人共创智能 公司介绍 新闻 投资者关系 加入我们 EN 模型 语言模型 MiniMax M3 NEW MiniMax M2.7 MiniMax M2.5 视频生成 MiniMax H3 NEW 语音&音乐 MiniMax Speech 2.8 NEW MiniMax Music 3.0 NEW 产品 MiniMax Code NEW MiniMax Design 语音 星野 API 订阅 研究 关于我们 与所有人共创智能 公司介绍 新闻 投资者关系 加入我们 English 2026.1.15 M
M2.1-Coding 多语言/多任务与泛化性 - MiniMax News | MiniMax 模型 语言模型 MiniMax M3 MiniMax M2.7 MiniMax M2.5 视频生成 MiniMax H3 语音&音乐 MiniMax Speech 2.8 MiniMax Music 3.0 产品 MiniMax Code MiniMax Design 语音 星野 API 订阅 研究 关于我们 与所有人共创智能 公司介绍 新闻 投资者关系 加入我们 EN 模型 语言模型 MiniMax M3 NEW MiniMax M2.7 MiniMax M2.5 视频生成 MiniMax H3 NEW 语音&音乐 MiniMax Speech 2.8 NEW MiniMax Music 3.0 NEW 产品 MiniMax Code NEW MiniMax Design 语音 星野 API 订阅 研究 关于我们 与所有人共创智能 公司介绍 新闻 投资者关系 加入我们 English 2026.01.04 M2.1-Coding 多