Tabbit
ResourcesBlogModels
Tabbit LogoTabbit

Tabbit — The AI Browser that Works for You

Topics

  • AI Browser Resources
  • Agentic Browser Resources
  • Browser Downloads and Install Guides
  • Browser Comparisons
  • AI Browser Alternatives
  • Browser Productivity Resources

Popular Guides

  • AI Browser
  • Agentic Browser Download
  • Best AI Browser 2026: Top 9 Tested & Ranked
  • AI Browser Download
  • Free AI Browser
  • Best AI Browser 2026
  • AI Browser Comparison 2026
  • AI Browser for Windows
  • AI Browser for Mac
  • Chrome Alternative 2026

Events

  • Tabbit Skill Competition
  • KPOP SBTI Fandom Personality Test
  • Tabbit Campus Creator Program
  • fifi's Picks: AI Skills for Research Papers
  • User Survey

About

  • Tabbit Blog
  • Press & Media
English
简体中文English
Reviews and evidence

MiMo-V2.6-Pro · Community source · Personal experience

Reddit Field Test: MiMo-V2.6-Pro Gets Stuck in a grep Infinite Loop During a UI/UX Terminal Modification Task

In a real website UI/UX modification task, the poster said that both MiMo-V2.6-Pro and MiMo-V2.6-Flash triggered a grep-related infinite loop in the terminal and failed to fix the code after approximately 30 minutes; when the same modification was assigned to DeepSeek V4.1 Flash, it continued as expected and output a complete terminal work history.

Community sourcePersonal experienceEdited 2026-09-22

Test conditions

Source-specific observation
In a real website UI/UX modification task, the poster said that both MiMo-V2.6-Pro and MiMo-V2.6-Flash triggered a grep-related infinite loop in the terminal and failed to fix the code after approximately 30 minutes; when the same modification was assigned to DeepSeek V4.1 Flash, it continued as expected and output a complete terminal work history.
Published conditions
It cannot be used to assess benchmark scores, price, speed, code quality, or long-horizon Agent capability, and it cannot replace a controlled retest.

Key data and applicable tasks

One-sentence conclusion

In a real website UI/UX modification task, the poster said that both MiMo-V2.6-Pro and MiMo-V2.6-Flash triggered a grep-related infinite loop in the terminal and failed to fix the code after approximately 30 minutes; when the same modification was assigned to DeepSeek V4.1 Flash, it continued as expected and output a complete terminal work history.

Suitable use cases

  • Suitable tasks: This material only shows that frontend maintenance tasks requiring terminal tool calls, code changes, and observable execution can carry a risk of failure; it cannot establish that the model is suitable or unsuitable for all coding tasks.

  • Unsuitable tasks: It cannot be used to assess benchmark scores, price, speed, code quality, or long-horizon Agent capability, and it cannot replace a controlled retest.

  • Applicable model version: The original post explicitly names Mimo v2.6 Pro; it also tests Mimo v2.6 Flash, and the two must be kept separate. The post does not mention MiMo-V2.6-Pro-RL or Ultraspeed.

  • Applicable client, Agent, or API: The body explicitly mentions only a terminal and a website UI/UX modification; it does not disclose the specific client, Agent, provider, or API.

  • Recommended reasoning level and parameters: Not disclosed and cannot be inferred.

Test method

  1. The poster requested a UI/UX update for a website they were operating.

  2. The same modification task was assigned separately to MiMo v2.6 Flash and MiMo v2.6 Pro.

  3. The poster observed the execution process in the terminal and reported that both models entered a grep-related infinite loop after making some progress.

  4. After waiting approximately 30 minutes, the poster still could not confirm that the task was progressing, and the code had not been fixed.

  5. The same modification task was assigned to DeepSeek V4.1 Flash as a comparison; the poster said it progressed as expected and output the complete work history to the terminal.

Original evidence and data

  • Task: Update the UI/UX of a website in operation.

  • Model samples: MiMo v2.6 Flash and MiMo v2.6 Pro; the comparison model was DeepSeek V4.1 Flash.

  • Tool/environment: Terminal; the specific Agent, provider, operating system, repository, tool version, and parameters were not disclosed.

  • Observed failure: After making some progress, both MiMo versions entered a grep-related infinite loop; no code was fixed after approximately 30 minutes.

  • Comparison result: The poster said DeepSeek V4.1 Flash faithfully executed the same modification and output the complete work history to the terminal.

  • Visible artifacts: The original post provides no code diff, execution log, screenshot, repository link, or downloadable build artifact; “output the complete work history” is the poster's description, and the page does not display that log.

  • Public sample size: 1 UI/UX modification task from the same poster, attempted with multiple models; this is not a controlled benchmark.

Scope and limitations

  • This is one user's account of one frontend maintenance task and cannot be generalized into a conclusion about MiMo-V2.6-Pro's overall capability.

  • The original post does not disclose the complete prompt, codebase, reproduction steps, provider, model parameters, tool version, or logs, so the “grep infinite loop” cannot be reproduced.

  • The behavior of MiMo-V2.6-Flash is recorded separately from MiMo-V2.6-Pro; this piece's core conclusion covers only the post's direct description of Pro.

  • DeepSeek V4.1 Flash's success is also the same user's comparison observation and should not be treated as an independent evaluation result.

Source excerpts or observations (short excerpts for compliance only)

“an infinite loop related to grep started occurring in the terminal.”

“for 30 minutes no code was fixed.”

“DS 4.1 Flash is still much better..”

What this supports

  • This material only shows that frontend maintenance tasks requiring terminal tool calls, code changes, and observable execution can carry a risk of failure; it cannot establish that the model is suitable or unsuitable for all coding tasks.

What this does not support

  • It cannot be used to assess benchmark scores, price, speed, code quality, or long-horizon Agent capability, and it cannot replace a controlled retest.

Method, limits, and reproduction

The figures, task set, reasoning tier, and client conditions apply only to the listed source and collection snapshot. Different versions, harnesses, or providers must not be compared directly; undisclosed parameters remain unknown.

For a reproduction, fix the model version, provider or client, reasoning tier, tools, task-set version, sample count, and collection date, and record failures, retries, and human corrections. Full steps are in the source notes below.

Original source

Reddit, r/CommandCode · u/choiyoh · Original publication date 2026-09-22 · Site edit date 2026-09-22

Open original source

MiMo-V2.6-Pro

Compare MiMo-V2.6-Pro in Tabbit

Download the Tabbit client to check model access

Read the full analysis

Full review · English

MiMo-V2.6-Pro Review: The Smartest Open Model Makes You Wait

A public-evidence review of MiMo-V2.6-Pro: what it does well, where it bites, real user reports, and a workload verdict on Xiaomi's open flagship.

Pricing · English

MiMo-V2.6-Pro Pricing: Official Rate Card, Cache Levers, and Cost per Task

A practical decision guide to MiMo-V2.6-Pro pricing: official API rates, prompt cache economics, reasoning token overhead, UltraSpeed mode, and worked task budgets.

Alternatives · English

MiMo-V2.6-Pro Alternatives: Choose by Task and Budget

Compare five MiMo-V2.6-Pro alternatives by completed-task cost, agentic reliability, open weights, and deployment fit, with prices checked on September 22, 2026.

Comparison · English

MiMo-V2.6-Pro vs MiMo-V2.6-Flash: Which Xiaomi MoE Model Fits Your Workload?

A head-to-head comparison of MiMo-V2.6-Pro and Flash: 1.02T vs 309B MoE architecture, 3.1x pricing delta, reasoning token overhead, agent benchmarks, and decision matrix.

Related reviews

MiMo-V2.6-Pro Official X Release Thread: Task Positioning, Public Benchmarks, and Open-Source Entry PointsThis official thread positions MiMo-V2.6-Pro as an openly built native omnimodal agent model focused on coding, computer use, 3D, design, research, and tool workflows; its rankings and examples help identify promising task directions, but they remain vendor-reported and cannot replace an independent rerun under the same harness.Xiaomi MiMo Official Release: MiMo-V2.6-Pro Benchmark Signals and Native Omnimodal PositioningXiaomi positions MiMo-V2.6-Pro as a native omnimodal open-source model for agents, coding, vision, and computer use, and reports an Artificial Analysis Intelligence Index score of 46 along with several RL/agent results; these figures remain the vendor's own reporting and cannot replace an independent rerun under the same harness.MiMo-V2.6-Pro Official Technical Report: Architecture, Scaled RL, and Evaluation ConditionsThe official report defines MiMo-V2.6-Pro as a native multimodal sparse MoE with 1.02T total parameters and approximately 42B active parameters, and reports strong agent benchmark results from large-batch, multi-environment RL training with multiple harnesses and groupwise graders; however, most figures in the tables are vendor-reported。Arena Code Arena: MiMo-V2.6-Pro WebDev AutoEval RecordArena's Code Arena | WebDev overall leaderboard includes mimo-v2.6-pro with an AutoEval score of 1628 (+18/-18), but it does not publish a vote count or rank, so this only shows that it was included in the WebDev automated evaluation leaderboard; 1628 must not be treated as a blind-test ranking.Xiaomi MiMo-V2.6-Pro Official API Integration and Reasoning ConfigurationThis official configuration can be used to connect to mimo-v2.6-pro through the OpenAI-compatible protocol, with deep thinking, streaming output, and multi-turn tool calls enabled as needed.Hugging Face Official MiMo-V2.6-Pro-RL Local Deployment and Chat Template ConfigurationThe official model card provides SGLang and vLLM service commands for MiMo-V2.6-Pro-RL and defines chat-template behavior for text, image, video, audio, thinking, and tool calls in the repository tokenizer configuration; local deployment must use the checkpoint name and must not treat it as the same model identifier as the hosted API's mimo-v2.6-pro.Xiaomi MiMo-V2.6-Pro Omnimodal Input and Visual Task Workflowmimo-v2.6-pro can read publicly accessible URLs or properly formatted Base64 images, videos, and audio through the OpenAI Chat Completions API, but it cannot directly upload local files, and the combined media and text tokens remain subject to the 1M context limit.Xiaomi MiMo-V2.6-Pro Official Function Calling and Multi-Turn Agent WorkflowFor mimo-v2.6-pro, the official workflow is “the model returns a complete assistant message, including reasoning_content and tool_calls → the client executes the tools → appends the role: tool results → requests the model again,” repeating until the current turn produces no more tool calls.