MiMo-V2.6-Pro and MiMo-V2.6-Flash released
Xiaomi · Model release
Source confirmed
Data as of October 6, 2026 · How the score is built
CurrentOpen WeightReasoning
Released Sep 22, 20261M contextXiaomi MiMo-V2.6-Pro-RL model card
MiMo-V2.6-Pro
Decision readingMiMo-V2.6-Pro scores 74.2 out of 100 and ranks #11 of 214. This profile shows 14 source-displayable benchmark rows; its strongest eligible category is Coding at #12. API pricing is $0.435 input and $0.87 output per million tokens, with cached input at $0.0036.
Released Sep 22, 2026 — see all recent releases
MiMo-V2.6-Pro will be repriced, updated or retired. Get each notice with its source and date. Follow model changes
Decision snapshot
Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.
Capability
74.2/100
field median 52#11 of 214 ranked models
Public
#11of 214
Verified —
Price
$0.43input / $0.87 output
input median $0.95cached $0.004 · blended $0.65
Speed
47tok/s
field median 98 tok/sFirst token 48.45 s
Context
1Mtokens
field median 256,000Maximum output length is tracked separately
Strongest published evidence
Coding ranks #12. Particularly well-suited for software development and code generation tasks.
Validate before choosing
14 published rows leave some tracked benchmark slots empty. Agentic is its lowest eligible category at #13.
Source-linked · 14 displayable benchmark rows
Follow model changesCategory score record
Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank #13 of 120Percentile 90thWeight 22%9 benchmarksVerified | 66.8 | 9 benchmarks | Verified | |||
| CodingRank #12 of 144Percentile 92ndWeight 20%3 benchmarksVerified | 63.9 | 3 benchmarks | Verified | |||
| ReasoningWeight 17%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MultimodalWeight 12%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| KnowledgeWeight 12%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MathWeight 5%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured |
14 of 655 tracked benchmark slots have displayable evidence · bars run 0–100
Coverage detailsHow much of this is verified
Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.
- Agentic9/9 verified
- Coding3/3 verified
- ReasoningNot measured
- MultimodalNot measured
- KnowledgeNot measured
- MultilingualNot measured
- Inst. FollowingNot measured
- MathNot measured
Verified sourceProvisionalNot measured
Capability shape
Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.
MiMo-V2.6-Pro category percentile values
- Agentic90th percentile
- Coding92nd percentile
- ReasoningNot eligible
- MultimodalNot eligible
- KnowledgeNot eligible
- MultilingualNot eligible
- Instruction followingNot eligible
- MathNot eligible
The dashed outline is median of 6 nearest peers.
Eligible category ranks
- Agentic#13/120
- Coding#12/144
- ReasoningNot ranked
- MultimodalNot ranked
- KnowledgeNot ranked
- MultilingualNot ranked
- Inst. FollowingNot ranked
- MathNot ranked
Top decileTop quartileMid-fieldNot eligible
Benchmark ledger
Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.
Coding3 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| DeepSWE | Score71.9% | Versus best verified row Best verified: Gemini 4 Argon · 77.9% | Gap6 behind | Weight15% ref. weight | Provider exact |
| Terminal-Bench 2.1 | Score89.9% | Versus best verified row Best verified: SWE-2 · 92.8% | Gap2.9 behind | WeightScored in Agentic | Provider exact |
| ProgramBenchProgramBench: Can Language Models Rebuild Programs From Scratch? | Score26.5% | Versus best verified row Best verified: Claude Opus 5 · 93.0% | Gap66.5 behind | WeightDisplay only | Provider exact |
Agentic9 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Terminal-Bench 4.0 | Score34.90% | Versus best verified row Best verified: Claude Sonnet 5.5 · 70.60% | Gap35.7 behind | Weight8% ref. weight | Provider exact |
| Terminal-Bench 2.1 | Score89.9% | Versus best verified row Best verified: SWE-2 · 92.8% | Gap2.9 behind | Weight8% ref. weight | Provider exact |
| OSWorld-Verified | Score82% | Versus best verified row Best verified: Qwen3.8 Max · 86.1% | Gap4.1 behind | Weight6% ref. weight | Provider exact |
| AutomationBench | Score53.1% | Versus best verified row Best verified: DeepSeek V4.1 Flash · 54.8% | Gap1.7 behind | Weight5% ref. weight | Provider exact |
| JobBench | Score62.0% | Versus best verified row Best verified: Muse Spark 1.3 · 64.9% | Gap2.9 behind | Weight5% ref. weight | Provider exact |
| Toolathlon-Verified | Score76.9% | Versus best verified row Best verified: Claude Opus 5 · 80.6% | Gap3.7 behind | Weight3% ref. weight | Provider exact |
| Agents' Last Exam | Score31.6% | Versus best verified row Best verified: GPT-6 Astra · 59.3% | Gap27.7 behind | Weight3% ref. weight | Provider exact |
| CyberGym | Score94.0% | Versus best verified row Best verified: MiMo-V2.6-Flash · 95.1% | Gap1.1 behind | WeightDisplay only | Provider exact |
| ExploitGym | Score17.8% | Versus best verified row Best verified: GPT-6 Astra · 42.4% | Gap24.6 behind | WeightDisplay only | Provider exact |
External signals2 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| ExploitBenchExploitBench v8-bench | Score48% | Versus best verified row Best verified: GPT-6 Astra · 100% | Gap52.1 behind | WeightDisplay only | Provider exact |
| SEC-Bench Pro | Score66.3% | Versus best verified row Best verified: GPT-6 Astra · 85.4% | Gap19.1 behind | WeightDisplay only | Provider exact |
What it costs to get this score
Published API price against the public score. The x-axis uses a log scale; the dashed path marks models that are not beaten by a cheaper, higher-scoring option. Price uses average of published input and output rates.
Current modelExplore all models
MiMo-V2.6-Pro · 74.2 score · $0.65 blended per million tokens
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Horizontal: blended price per million tokens, log scale · Vertical: public score
Lineage
The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Radar
Full release historyMiMo-V2.6-Pro release history
Radar confirmed these at the source. Use MiMo-V2.6-Pro in your work? Explore Radar to follow supported changes and choose your alerts.
Radar
Spec sheet
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
- API model ID
- Not publishedXiaomi MiMo-V2.6 launch
- Context window
- 1MXiaomi MiMo-V2.6 launch
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- Not sourced yet
- Output modalities
- Not sourced yet
- Parameters
- Not sourced yet
- Availability
- Open-weight checkpoint and hosted API are available at launch. Xiaomi lists text, image, video, and audio input modalities.
- Cloud regions
- Not tracked yet
- Lifecycle
- Current
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Published at $0.004 per million cached input tokensXiaomi MiMo-V2.6 launch
- Self-host
- Open weights available; hardware estimate not sourced
- Rate limits
- Not tracked yet
How to read this profile
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
MiMo-V2.6-Pro ranks #11 of 214 on the public leaderboard with a score of 74.17/100. It does not yet have enough sourced coverage for a verified position.
MiMo-V2.6-Pro is a open weight model with a 1M context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.
Open-weight checkpoint and hosted API are available at launch. Xiaomi lists text, image, video, and audio input modalities.
Official exact-value snapshot from Xiaomi's September 22, 2026 MiMo-V2.6 launch page and technical report. Xiaomi releases the MIT-licensed MiMo-V2.6-Pro-RL checkpoint as a natively omnimodal model. BenchLM maps only directly comparable public benchmarks and keeps the provider-run row non-ranked because weighted benchmark coverage remains sparse. MiMo Code Bench, MiMo Visual Coding, and MiMo Cyber Bench are in-house evaluations and remain outside the shared benchmark schema.
MiMo-V2.6-Pro sits in the MiMo-V2.6 family with MiMo-V2.6-Flash. Its explicit predecessor is MiMo-V2.5-Pro. 14 of 655 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Coding at #12, while its lowest eligible position is Agentic at #13. particularly well-suited for software development and code generation tasks.
Last updated October 6, 2026. Runtime fields remain blank until a sourced snapshot exists.
Deployment options
Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.
Published weights are available, but BenchLM does not yet have a sourced parameter and VRAM profile for this exact model. Hardware cost estimates stay unavailable until that sizing record is complete.
Estimate VRAM from known parametersQuestions
How does MiMo-V2.6-Pro perform overall in AI benchmarks?
MiMo-V2.6-Pro ranks #11 out of 214 models on the public BenchAlign leaderboard, with a score of 74.17/100. Its evidence status is Estimated, and this profile shows 14 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
Is MiMo-V2.6-Pro good for coding and programming?
MiMo-V2.6-Pro ranks #12 out of 144 eligible models for coding and programming, with a public category score of 63.9/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Is MiMo-V2.6-Pro good for agentic tool use and computer tasks?
MiMo-V2.6-Pro ranks #13 out of 120 eligible models for agentic tool use and computer tasks, with a public category score of 66.8/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Is MiMo-V2.6-Pro open source?
MiMo-V2.6-Pro is an open-weight model from Xiaomi. Its weights can be downloaded for local or hosted deployment, subject to the published license. Open weight does not automatically mean open source: training data and training code may remain private, and commercial restrictions can still apply.
Which sibling models are related to MiMo-V2.6-Pro?
MiMo-V2.6-Pro belongs to the MiMo-V2.6 family. Related tracked variants include MiMo-V2.6-Flash. A sibling link indicates shared lineage or a documented configuration relationship; it does not mean the variants have identical pricing, context limits, benchmark evidence, or deployment behavior. Compare before switching.
Does MiMo-V2.6-Pro have full benchmark coverage on BenchLM?
No. MiMo-V2.6-Pro currently has 30 source-displayable rows across 655 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.
What is the context window size of MiMo-V2.6-Pro?
MiMo-V2.6-Pro has a documented context window of 1M. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.