MiMo V2.6 Pro Intelligence, Performance and Price Analysis

TL;DR

MiMo V2.6 Pro achieves an Intelligence Index score of 46, placing it near the top of the Artificial Analysis leaderboard while delivering the lowest cost per Intelligence‑Index task among the models examined; however, its raw generation speed trails leading competitors.

Intelligence Index Overview

MiMo V2.6 Pro’s Intelligence Index (v4.3.2) = 46 – higher scores indicate better overall capability across ten benchmark suites (AA‑Briefcase, GDPval‑AA, AutomationBench, Terminal‑Bench 4.0, SciCode, Humanity’s Last Exam, GDP.pdf, CritPt, AA‑Omniscience, AA‑LCR). The index aggregates rubric pass rate, analytical quality Elo, presentation Elo, and hallucination penalties into a single figure.

"Artificial Analysis Intelligence Index v4.3.2 incorporates 10 evaluations… Higher is better" – Artificial Analysis methodology.

The score puts MiMo V2.6 Pro ahead of DeepSeek‑V4.1 (39) and close to Claude Opus 5 (66.9) in raw intelligence, but below the very top models such as GPT‑6 Astra (57.9) and Claude Fable 5 (46.7).

Cost Efficiency

Weighted average cost per Intelligence‑Index task = $0.0036 per M tokens (cache‑hit price). This is the cheapest among all models in the comparison, driven by low input/output token pricing and modest token consumption per benchmark.

"MiMo v2.6 training run cost $3.47 M, far lower than the $100 M+ estimates for the Big 5" – comment by @ignoramous.

The total cost to run the entire Intelligence Index suite is therefore minimal, making MiMo V2.6 Pro attractive for high‑volume or budget‑constrained deployments.

Speed and Latency

Output speed: MiMo V2.6 Pro generates ~X tokens/s (exact figure not disclosed in the source). Independent testing by a community member (@dom96) reports it is faster than DeepSeek but still slower than leading models such as Claude Opus 5.
Time‑to‑first‑token (TTFT): Comparable to other MoE models; the exact seconds are not listed.
End‑to‑end 500‑token response: Higher than the fastest competitors, indicating longer overall latency despite reasonable TTFT.

"It is an impressive model… but still much slower than leading models" – @dom96.

Context Window

MiMo V2.6 Pro offers a large context window (exact token limit not specified), which benefits Retrieval‑Augmented Generation (RAG) workflows that require processing of extensive documents.

Openness and Licensing

The model is marked "Commercial Use Restricted" – commercial deployment is allowed under specific conditions, while non‑commercial use is unrestricted. No open‑weight version is provided.

Community Feedback Highlights

Positive: Users appreciate the price‑performance trade‑off and note that MiMo V2.6 Pro is a "top model worth exploring" for those who have not tried it before (comment by @segmondy).
Criticism: Some observers question the discrepancy between the headline ranking (#1/114) and the actual plotted scores, suggesting possible UI inconsistencies (comment by @deanc).
Comparison doubts: A user points out that DeepSeek‑V4.1 sometimes outperforms MiMo in specific tasks, despite a lower overall index score (comment by @egeres).
Speed concerns: While the model is cheaper, its generation speed does not match the fastest alternatives (comment by @dom96).

Bottom Line

MiMo V2.6 Pro delivers high intelligence (46 on the AI Index) at an exceptionally low cost, making it a compelling choice for cost‑sensitive applications that can tolerate modest latency. Its large context window and strong performance on agentic knowledge work further broaden its utility, though users seeking the fastest raw throughput may prefer other top‑tier models.