xiaomiListed Apr 22, 2026

Xiaomi: MiMo-V2.5

MiMo-V2.5 is a native omnimodal model by Xiaomi. It delivers Pro-level agentic performance at roughly half the inference cost, while surpassing MiMo-V2-Omni in multimodal perception across image and video understanding...

Context window1.1M
Max output131.1K
Provider endpoints9
Benchmark results0
Measured performance

Benchmark results

All leaderboards ↗
—

No published results in this index yet

Scores appear here when an evaluation matches this exact model.

Access & cost

Prices across providers

9 quotes

Your token mix

USD · listed token rates

Xiaomi · via OpenRouterxiaomi/fp8 · quantization=fp8
$0.21
Novita · via OpenRouternovita/fp8 · quantization=fp8
$0.252
Venice · via OpenRoutervenice/fp8 · quantization=fp8
$0.90

OpenRouter

Catalog quote
Input
$0.14
Output
$0.28
Cached input
$0.0028
USD / 1M tokens
1.1M context131.1K max outputPrice source ↗Checked Oct 18, 2026
Endpoint IDxiaomi/mimo-v2.5

novita

via Hugging Face
Input
$0.168
Output
$0.336
USD / 1M tokens
1M contextPrice source ↗Checked Oct 18, 2026
Endpoint IDXiaomiMiMo/MiMo-V2.5

deepinfra

via Hugging Face
Input
$0.14
Output
$0.28
USD / 1M tokens
262.1K contextPrice source ↗Checked Oct 18, 2026
Endpoint IDXiaomiMiMo/MiMo-V2.5

GMICloud

via OpenRouter

gmicloud/fp8 · quantization=fp8

Provider degraded
Input
$0.119
Output
$0.238
Cached input
$0.00255
USD / 1M tokens

Endpoint degraded (status -2) · Source discount 15%; rates as published

1.1M context945K max outputPrice source ↗Checked Oct 18, 2026
Endpoint IDxiaomi/mimo-v2.5::gmicloud/fp8

Xiaomi

via OpenRouter

xiaomi/fp8 · quantization=fp8

Input
$0.14
Output
$0.28
Cached input
$0.0028
USD / 1M tokens
1M context131.1K max outputPrice source ↗Checked Oct 18, 2026
Endpoint IDxiaomi/mimo-v2.5::xiaomi/fp8

StreamLake

via OpenRouter

streamlake

Provider degraded
Input
$0.168
Output
$0.336
Cached input
$0.00336
USD / 1M tokens

Endpoint degraded (status -2)

1M context128K max outputPrice source ↗Checked Oct 18, 2026
Endpoint IDxiaomi/mimo-v2.5::streamlake

Novita

via OpenRouter

novita/fp8 · quantization=fp8

Input
$0.168
Output
$0.336
Cached input
$0.0034
USD / 1M tokens
1M context131.1K max outputPrice source ↗Checked Oct 18, 2026
Endpoint IDxiaomi/mimo-v2.5::novita/fp8

Venice

via OpenRouter

venice/fp8 · quantization=fp8

Input
$0.40
Output
$2.00
Cached input
$0.08
USD / 1M tokens
1M context65.5K max outputPrice source ↗Checked Oct 18, 2026
Endpoint IDxiaomi/mimo-v2.5::venice/fp8

Model specifications

Developer
xiaomi
Modality
Language
Context
1,050,000 tokens
Maximum output
131,072 tokens
Weights
Open weights
Provider listed
Apr 22, 2026
First discovered
Oct 16, 2026

Exact identities

  • openrouterxiaomi/mimo-v2.5
  • huggingfaceXiaomiMiMo/MiMo-V2.5

Sources

Updated Oct 18, 2026

More from xiaomi

View all ↗
xiaomiListed 26 days ago

Xiaomi: MiMo-V2.6-Pro-UltraSpeed

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…

1M contextImage inputAudio inputNo reported score
No reported score
$4.35in$8.70out/ 1M tokens · USDXiaomi · via OpenRouter · 2 endpointsxiaomi/fp8 · quantization=fp8
xiaomiListed 26 days ago

Xiaomi: MiMo-V2.6-Flash

MiMo-V2.6-Flash is an open-source foundation model developed by Xiaomi. Built on a Mixture-of-Experts architecture with 309B total parameters and 15B activated per token, it employs a hybrid attention…

1.1M contextImage inputAudio inputNo reported score
No reported score
$0.10in$0.28out/ 1M tokens · USDDarkbloom · via OpenRouter · 10 endpointsdarkbloom/fp4 · quantization=fp4
xiaomiListed Apr 22

Xiaomi: MiMo-V2.5-Pro

MiMo-V2.5-Pro is Xiaomi’s flagship model, delivering strong performance in general agentic capabilities, complex software engineering, and long-horizon tasks, with top rankings on benchmarks such as…

1.1M contextTool callingStructured outputNo reported score
No reported score
$0.3045in$0.609out/ 1M tokens · USDGMICloud · via OpenRouter · 9 endpointsgmicloud/bf16 · quantization=bf16