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MiniMax M2.5 leaderboard — benchmarks, pricing, and comparisons.

Compare MiniMax M2.5 vs GPT, Claude, Gemini, DeepSeek, open-weight, and frontier AI models using public benchmark scores, token pricing, context window, and access details.

Rank #28AskClash overall score: 44.2
$0.30 / $1.20Input and output token price, when published. Context: 128K.
Visit websiteVisit the model provider's website.

MiniMax M2.5 benchmark snapshot

AskClash combines public LLM benchmark cells into a weighted percentile score and penalizes missing coverage so narrow rows do not dominate better-measured models.

Overall44.2
Benchmark cells7
Context128K
CreatorMiniMax

MiniMax M2.5 public benchmark scores

Cached benchmark values can include HLE, GPQA, SWE-bench, SWE-Pro, SWE-Atlas, Terminal-Bench, MCP Atlas, MMMU-Pro, ARC-AGI-2, Tau2, and model-specific coding or agent scores.

HLE

19.1 score

GPQA

84.8 score

IFEval

71.6 score

SWE-bench

80.2 score

SWE-Pro

55.4 score

Tau2

95.3 score

MiniMax M2.5 vs other AI models

Use these comparison links to evaluate MiniMax M2.5 against nearby LLMs by benchmark score, price, context window, and provider.

Related AI and tech coverage

Cached AskClash article matches that can provide release, provider, benchmark, pricing, or market context around this model.

Alibaba Stock Sink on Explosive Anthropic AI Theft Allegations

Anthropic said the activity amounted to distillation, a method in which a smaller model is trained on the outputs of a larger one. The company alleged the effort involved operators linked to Alibaba and Alibaba Qwen, its AI lab, and said it had identified a similar campaign earlier this year involving other Chinese AI groups, including DeepSeek, Moonshot AI and MiniMax. The weakness spread across Chinese AI names, with Xiaomi (XIACF) and Baidu (BIDU) both falling more than 3%. The episode adds t

vLLM Inference Engine v0.23.0 Release Notes

* **DeepSeek-V4 matures across backends**: Following its introduction in v0.22.0, DeepSeek-V4 received another large hardening and optimization pass. Its sparse MLA metadata is now decoupled from DeepSeek-V3.2 (#44699), it gained a TRTLLM-gen attention kernel (#43827), EPLB support for the Mega-MoE (#43339), selective prefix-cache retention for sliding-window KV cache (#43447), and an index-share feature for DSA MTP (#44420). The model was also detached from `torch.compile` (#43746, #43891), its

Last cached leaderboard date: July 8, 2026. This model page is generated from the AskClash LLM Leaderboard cache and linked from the live leaderboard.