Inkling-Small vs MiMo-V2.5-Pro
Inkling-Small leads the LLM Stats Score 38.3 to 25.7. Inkling-Small is 1.0x cheaper per token.
Thinking Machines Lab · Xiaomi · Updated for 2026
Which is better?
Inkling-Small leads the overall LLM Stats Score 38.3 to 25.7, ranking #72 overall.
The models split the 4 individual benchmarks reported for both models evenly.
MiMo-V2.5-Pro also accepts a larger context window (1,048,576 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Inkling-Small
- overall performance matters — it scores 38.3 and ranks #72 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you want the most recent training data — it shipped Jul 2026
Choose MiMo-V2.5-Pro
- you process long inputs — it offers a 1,048,576 token context window
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
24 reported for Inkling-Small · 31 for MiMo-V2.5-Pro
Inkling-Small outperforms in 2 benchmarks (GPQA, SWE-Bench Verified), while MiMo-V2.5-Pro is better at 2 benchmarks (Humanity's Last Exam, SWE-Bench Pro).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Inkling-Small ($0.30/1M tokens) is 1.4x cheaper than MiMo-V2.5-Pro ($0.43/1M tokens).
For output processing, Inkling-Small ($1.20/1M tokens) is 1.4x more expensive than MiMo-V2.5-Pro ($0.87/1M tokens).
In conclusion, MiMo-V2.5-Pro is more expensive than Inkling-Small.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiMo-V2.5-Pro has 747.2B more parameters than Inkling-Small, making it 270.7% larger.
Context Window
Maximum input and output token capacity
MiMo-V2.5-Pro accepts 1,048,576 input tokens compared to Inkling-Small's 256,000 tokens. Inkling-Small can generate longer responses up to 256,000 tokens, while MiMo-V2.5-Pro is limited to 131,072 tokens.
Input capabilities
Documented input modalities across available providers
Inkling-Small supports multimodal inputs, whereas MiMo-V2.5-Pro does not.
Inkling-Small can handle both text and other forms of data like images, making it suitable for multimodal applications.
Inkling-Small
MiMo-V2.5-Pro
License
Usage and distribution terms
Inkling-Small is licensed under Apache 2.0, while MiMo-V2.5-Pro uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
MIT
Open weights
Release Timeline
When each model was launched
Inkling-Small was released on 2026-07-30, while MiMo-V2.5-Pro was released on 2026-04-27.
Inkling-Small is 3 months newer than MiMo-V2.5-Pro.
Jul 30, 2026
2 months ago
3mo newerApr 27, 2026
5 months ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Inkling-Small is available from Thinking Machines Lab, DeepInfra. MiMo-V2.5-Pro is available from Xiaomi, DeepInfra, Novita.
Inkling-Small
MiMo-V2.5-Pro
Outputs Comparison
Judge for yourself.
Run your own prompts against Inkling-Small and MiMo-V2.5-Pro side-by-side, then vote on the output you prefer.
FAQ
Common questions about Inkling-Small vs MiMo-V2.5-Pro.