MiMo-V2.6-Pro-UltraSpeed model profile

Evidence snapshot:

MiMo-V2.6-Pro-UltraSpeed is a Xiaomi model profile with a 1,048,576-token context window. The dated catalog snapshot records text, image, video, audio modalities and interfaces for audio input, prompt caching, reasoning controls, structured output, text generation.

MiMo-V2.6-Pro-UltraSpeed is the fast speed edition of Xiaomi's flagship foundation model, MiMo-V2.6-Pro. Built from the same 1T MiMo-V2.6-Pro checkpoint, it matches the original model in quality while delivering roughly 10x the output speed. The model features a 1M-token context window and native multimodal capabilities. Optimized for agentic workflows, it delivers top-tier performance across coding, visual, general, and research scenarios, excelling at complex, long-horizon tasks with robust generalization across a diverse range of agent harnesses.

MiMo-V2.6-Pro-UltraSpeed is a reference profile: Xiaomi publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call.

MiMo-V2.6-Pro-UltraSpeed is an independent knowledge profile. It does not claim that Kendr hosts the model, quote a Kendr customer price, promise API availability, or advertise a Kendr routing receipt.

MiMo-V2.6-Pro-UltraSpeed accepts text, image, video, and audio and returns text. The snapshot records audio input, prompt caching, reasoning controls, structured output, text generation, tool calling, video input, and vision as capabilities or interfaces.

The dated reference snapshot lists $4.35 input and $8.7 output per million tokens. Cached input is $0.036 per million tokens.

No comparable third-party benchmark value is present in the 2026-10-13 snapshot. Missing values are not estimated.

MiMo-V2.6-Pro-UltraSpeed ranked #77 in the cited trailing-7-day third-party catalog usage dataset as of 2026-10-13. Observed within the cited trailing-7-day third-party catalog usage dataset; this is not global AI market share.

Profile data was reviewed for the 2026-10-13 snapshot. Claims retain their source dates, and unavailable fields are shown as unavailable instead of estimated.

Profile facts

Profile type
Model research profile
Provider or publisher
Xiaomi
Context window
1,048,576 tokens
Snapshot date
2026-10-13
Knowledge cutoff
Not disclosed
Reference catalog ID
xiaomi/mimo-v2.6-pro-ultraspeed

When to pick MiMo-V2.6-Pro-UltraSpeed

MiMo-V2.6-Pro-UltraSpeed is a reference profile: Xiaomi publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call.

Each condition below is derived from this model's own values in the 2026-10-13 snapshot, compared only against models publishing the same field.

  • Reach for it when a whole corpus has to fit in one prompt. The 1.05M-token context window is in the top quarter of the 167 models publishing a limit here, so long documents can go in whole rather than chunked.
  • Reach for it when the input includes images. The snapshot records image input, so screenshots, scans, and diagrams can be sent directly instead of described.
  • Reach for it when the input is speech. The snapshot records audio input, so recordings can go to this route rather than being transcribed first.
  • Reach for it when the model has to call tools. Tool calling is recorded in the snapshot, so this route can drive an agent loop rather than only answer in prose.
  • Look elsewhere when you need to call it through Kendr today. This is a research reference profile with no Kendr alias. The facts and evidence here are published for comparison; the model is not routable on Kendr.
  • Look elsewhere when the work does not justify the rate. At $4.35 in and $8.7 out per 1M tokens, this is in the most expensive tenth of the 149 models publishing both rates. Route routine or high-volume traffic to a cheaper model and keep this one for work that needs it.

Context, modalities, and identity

MiMo-V2.6-Pro-UltraSpeed accepts text, image, video, and audio and returns text. The snapshot records audio input, prompt caching, reasoning controls, structured output, text generation, tool calling, video input, and vision as capabilities or interfaces.

Provider or publisher
Xiaomi
Context window
1,048,576 tokens
Maximum output
131,072 tokens
Input modalities
text, image, video, and audio
Output modalities
text
Knowledge cutoff
Not disclosed

Model overview

MiMo-V2.6-Pro-UltraSpeed is the fast speed edition of Xiaomi's flagship foundation model, MiMo-V2.6-Pro. Built from the same 1T MiMo-V2.6-Pro checkpoint, it matches the original model in quality while delivering roughly 10x the output speed. The model features a 1M-token context window and native multimodal capabilities. Optimized for agentic workflows, it delivers top-tier performance across coding, visual, general, and research scenarios, excelling at complex, long-horizon tasks with robust generalization across a diverse range of agent harnesses.

Reference model ID
xiaomi/mimo-v2.6-pro-ultraspeed
Canonical version
xiaomi/mimo-v2.6-pro-ultraspeed-20260921
Hugging Face ID
Not separately documented

Capabilities and supported controls

Capabilities and parameters are reported from the dated catalog and source records; their presence does not guarantee identical behavior across every provider route.

Supported parameters
frequency_penalty, include_reasoning, max_tokens, presence_penalty, reasoning, response_format, stop, structured_outputs, temperature, tool_choice, tools, top_p
  • audio input
  • prompt caching
  • reasoning controls
  • structured output
  • text generation
  • tool calling
  • video input
  • vision

Dated pricing snapshot

The dated reference snapshot lists $4.35 input and $8.7 output per million tokens. Cached input is $0.036 per million tokens.

These are dated third-party reference prices, not Kendr prices or an availability offer. Routes, tiers, caching, region, and provider policy can change the landed price.

Price date
2026-10-13
Input
$4.35 per 1M tokens
Cached input
$0.036 per 1M tokens
Output
$8.7 per 1M tokens

Provider routes, performance, and uptime

The snapshot retains 1 provider endpoint. Provider prices, context limits, p50 performance, and uptime can differ by route and are not Kendr guarantees.

Active provider endpoints
1
Best p50 latency
3.79 s
Best p50 throughput
112 tok/s
Availability with routing
97.90% over the sampled window
Availability without routing
97.87% over the sampled window
Performance date
2026-10-13
ProviderQuantizationInput / 1MOutput / 1MCache read / 1MContextp50 latencyp50 throughputUptime (1d)
Xiaomifp8$4.35 / 1M$8.7 / 1M$0.036 / 1M1,048,576 tokens3.79 s112 tok/s96.54%

Benchmark evidence and limitations

No comparable third-party benchmark value is present in the 2026-10-13 snapshot. Missing values are not estimated.

Third-party catalog fields normalized from the cited model dataset; benchmark methodology and coverage differ by source.

Popularity and market context

MiMo-V2.6-Pro-UltraSpeed ranked #77 in the cited trailing-7-day third-party catalog usage dataset as of 2026-10-13. Observed within the cited trailing-7-day third-party catalog usage dataset; this is not global AI market share.

Third-party catalog rank
#77
Global market share
Not inferred
Observation date
2026-10-13

Frequently asked questions

When should I use MiMo-V2.6-Pro-UltraSpeed?

MiMo-V2.6-Pro-UltraSpeed is a reference profile: Xiaomi publishes it, Kendr documents it for comparison, and it carries no Kendr alias to call. Reach for it when a whole corpus has to fit in one prompt: The 1.05M-token context window is in the top quarter of the 167 models publishing a limit here, so long documents can go in whole rather than chunked. Reach for it when the input includes images: The snapshot records image input, so screenshots, scans, and diagrams can be sent directly instead of described. Reach for it when the input is speech: The snapshot records audio input, so recordings can go to this route rather than being transcribed first. Reach for it when the model has to call tools: Tool calling is recorded in the snapshot, so this route can drive an agent loop rather than only answer in prose. Look elsewhere when you need to call it through Kendr today: This is a research reference profile with no Kendr alias. The facts and evidence here are published for comparison; the model is not routable on Kendr. Look elsewhere when the work does not justify the rate: At $4.35 in and $8.7 out per 1M tokens, this is in the most expensive tenth of the 149 models publishing both rates. Route routine or high-volume traffic to a cheaper model and keep this one for work that needs it.

What is MiMo-V2.6-Pro-UltraSpeed?

MiMo-V2.6-Pro-UltraSpeed is a Xiaomi model profile with a 1,048,576-token context window. The dated catalog snapshot records text, image, video, audio modalities and interfaces for audio input, prompt caching, reasoning controls, structured output, text generation.

What context window does MiMo-V2.6-Pro-UltraSpeed have?

The dated profile lists 1,048,576 tokens of context and up to 131,072 output tokens. Provider routes, variants, and runtime configuration can impose lower effective limits.

What benchmark evidence is available for MiMo-V2.6-Pro-UltraSpeed?

No comparable third-party benchmark value is present in the 2026-10-13 snapshot. Missing values are not estimated. Third-party catalog fields normalized from the cited model dataset; benchmark methodology and coverage differ by source.

Is MiMo-V2.6-Pro-UltraSpeed available through Kendr?

This is an independent knowledge profile, not a Kendr-hosted availability claim. Check Kendr's live public model API for currently enabled Kendr aliases.

Does the popularity rank represent MiMo-V2.6-Pro-UltraSpeed's global market share?

MiMo-V2.6-Pro-UltraSpeed ranked #77 in the cited trailing-7-day third-party catalog usage dataset as of 2026-10-13. Observed within the cited trailing-7-day third-party catalog usage dataset; this is not global AI market share. No global market-share percentage is inferred when the source does not publish one.

Sources and evidence dates

  1. MiMo-V2.6-Pro-UltraSpeed third-party catalog record (catalog, checked 2026-10-13)
  2. Third-party model catalog methodology (methodology, checked 2026-10-13)