SWE-Pro
56.1 score
LLM Leaderboard · Proprietary
MiMo-V2.5 benchmarks, pricing, and LLM comparison.
Compare MiMo-V2.5 vs GPT, Claude, Gemini, DeepSeek, open-weight, and frontier AI models using public benchmark scores, token pricing, context window, and access details.
Rank #39AskClash overall score: 15.9
— / —Input and output token price, when published. Context: 1M.
APIBilling and access path cached for this model row.
MiMo-V2.5 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.
Overall15.9
Benchmark cells4
Context1M
CreatorXiaomi
MiMo-V2.5 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.
Terminal-Bench
65.8 score
CharXiv
81.0 score
MMMU-Pro
77.9 score
MiMo-V2.5 vs other AI models
Use these comparison links to evaluate MiMo-V2.5 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.
Xiaomi claims MiMo-V2.5-Pro-UltraSpeed tops 1K tokens/second, a first at the 1T-parameter scale, using a standard 8-GPU commodity node; API trial starts June 9 (Jose Antonio Lanz/Decrypt)
Techmeme
SGLang — RadixAttention Inference Server v0.5.11 Release Notes
- **CUDA 13 + Torch 2.11**: Default CUDA version moves to 13.0 across SGLang, sgl-kernel, and Docker images, and PyTorch is upgraded from 2.9 to 2.11 — modernizing the build matrix and unlocking newer kernels: #21247, #24162, #24183, #23593 ([tracking issue #21498](https://github.com/sgl-project/sglang/issues/21498)) - **Day-0 / New Model Support**: Gemma 4, GLM-5.1, Qwen3.6, MiMo-V2.5 / V2.5-Pro, Ling-2.6-Flash, Mistral Medium 3.5, and Kimi-K2.6 — with cookbook recipes for tuned deployment comm
Xiaomi releases MiMo Code V0.1.0, an open-source AI coding assistant that it says outperforms Claude Code on agentic coding and software engineering benchmarks (Carl Franzen/VentureBeat)
Techmeme
Shifting to AI model customization is an architectural imperative
In the early days of large language models (LLMs), we grew accustomed to massive 10x jumps in reasoning and coding capability with every new model iteration. Today, those jumps have flattened into incremental gains. The exception is domain-specialized intelligence, where true step-function improvements are still the norm. When a model is fused with an organization’s…
Last cached leaderboard date: June 9, 2026. This model page is generated from the AskClash LLM Leaderboard cache and linked from the live leaderboard.