Inkling-Small vs MiMo-V2.6-Pro
MiMo-V2.6-Pro leads the LLM Stats Score 49.8 to 38.4. Inkling-Small is 1.0x cheaper per token.
Thinking Machines Lab · Xiaomi · Updated for 2026
Which is better?
MiMo-V2.6-Pro leads the overall LLM Stats Score 49.8 to 38.4, ranking #19 overall.
In the 1 individual benchmarks reported for both models, MiMo-V2.6-Pro wins 1; this is a narrower head-to-head signal than the composite indexes.
MiMo-V2.6-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
- you want predictable pricing at $0.30/M input and $1.20/M output
Choose MiMo-V2.6-Pro
- overall performance matters — it scores 49.8 and ranks #19 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Sep 2026
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 · 18 for MiMo-V2.6-Pro
Inkling-Small outperforms in 0 benchmarks, while MiMo-V2.6-Pro is better at 1 benchmark (Terminal-Bench 2.1).
MiMo-V2.6-Pro significantly outperforms across most 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-V2.6-Pro ($0.43/1M tokens).
For output processing, Inkling-Small ($1.20/1M tokens) is 1.4x more expensive than MiMo-V2.6-Pro ($0.87/1M tokens).
In conclusion, MiMo-V2.6-Pro is more expensive than Inkling-Small.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
MiMo-V2.6-Pro has 744.0B more parameters than Inkling-Small, making it 269.6% larger.
Context Window
Maximum input and output token capacity
MiMo-V2.6-Pro accepts 1,048,576 input tokens compared to Inkling-Small's 256,000 tokens. Only Inkling-Small specifies output context (256,000 tokens).
Input capabilities
Documented input modalities across available providers
Both Inkling-Small and MiMo-V2.6-Pro support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Inkling-Small
MiMo-V2.6-Pro
License
Usage and distribution terms
Inkling-Small is licensed under Apache 2.0, while MiMo-V2.6-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-V2.6-Pro was released on 2026-09-22.
MiMo-V2.6-Pro is 2 months newer than Inkling-Small.
Jul 30, 2026
1 months ago
Sep 22, 2026
0 days ago
1mo newerKnowledge 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-V2.6-Pro is available from Xiaomi.
Inkling-Small
MiMo-V2.6-Pro
Outputs Comparison
Judge for yourself.
Run your own prompts against Inkling-Small and MiMo-V2.6-Pro side-by-side, then vote on the output you prefer.
FAQ
Common questions about Inkling-Small vs MiMo-V2.6-Pro.