Xiaomi, released Apr 22, 2026

MiMo-V2.5price, context, benchmarks and release details

Provisional: not enough results to rank yet Open weights 88% confidence 88 percent, High confidence, 2 of 3 expected sources in
56.4
SI Score
#78 of 142 ranked models
Input, per 1M tokens
$0.14models.devFirst-party hosted API; MIT models.dev transcription. Provider documentation: https://platform.xiaomimimo.com/#/docs. Exact canonical endpoint; lowest short-context Standard USD token tier; cache/batch discounts excluded. Deprecated endpoints excluded; xiaomi/mimo-v2.5 Retrieved Oct 9, 2026 · MIT
Open source ↗
Output, per 1M tokens
$0.28models.devFirst-party hosted API; MIT models.dev transcription. Provider documentation: https://platform.xiaomimimo.com/#/docs. Exact canonical endpoint; lowest short-context Standard USD token tier; cache/batch discounts excluded. Deprecated endpoints excluded; xiaomi/mimo-v2.5 Retrieved Oct 9, 2026 · MIT
Open source ↗
Context window
1Mmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
Max output
131Kmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
Released
Apr 22, 2026models.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗

How the score breaks down

Coding (weight 40 percent) 60.9
Math (weight 15 percent) —
Preference (weight 15 percent) 75.7
Reasoning (weight 30 percent) —

Weights: reasoning 30%, math 15%, coding 40%, preference 15%. Results use fixed 0–100 scales before averaging, and thin evidence is pulled toward 50. Method si-v3-retained-evidence-2, computed Oct 9, 2026, 05:13 UTC.

Around it on the leaderboard

  1. 76 GPT-5.4 mini 56.9
  2. 77 LongCat-2.0 56.6
  3. 78 MiMo-V2.5 56.4
  4. 79 DeepSeek V4 Flash 56.2
  5. 80 Fugu 55.9

Full leaderboard

Benchmark results

3 benchmarks, 3 results

Each row shows the best published result. Where a model was tested at several settings, such as reasoning effort, open the row to see each one. Hover or tap a value for its source.

SWE-bench Procoding 56.1%Official model cards via models.devLab-reported; metric score; transcribed by MIT models.dev catalog; not independently evaluated [variant] Retrieved Oct 9, 2026 · factual citation; MIT transcription
Open source ↗
56.1
Terminal-Bench 2.0coding 65.8%Official model cards via models.devLab-reported; metric score; transcribed by MIT models.dev catalog; not independently evaluated [variant] 2.0 Retrieved Oct 9, 2026 · factual citation; MIT transcription
Open source ↗
65.8
LMArena Textpreference 1427.6 eloLMArena / ArenaPublished source fact [variant] text / overallPublished Oct 8, 2026 Retrieved Oct 9, 2026 · CC-BY-4.0
Open source ↗
75.7

Normalization uses a fixed 0–100 scale for each unit, independent of other models. Compare evaluation conditions before reading a small gap as decisive. “Lab-reported” marks the provider's own published figure.

Details and sources

Open weights
Yesmodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
License
not yet reported
Input modalities
text, image, audio, videomodels.devPublished source fact Retrieved Oct 9, 2026 · MIT
Open source ↗
First seen by SuperIndex
Oct 8, 2026
Coverage
70% of expected source weight

Reported (2)

  • Official model cards via models.devOct 8, 2026
  • LMArena / ArenaOct 8, 2026

Awaiting (1)

  • LiveBench30% of weight

Confidence rises as pending sources publish. Some sources never cover some models, so confidence reaches 100% at 80% of expected weight.

What changed

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Alerts on this device

What to be alerted about
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