Inkling-Small vs Kimi K2.6
Kimi K2.6 significantly outperforms across most benchmarks. Inkling-Small is 2.7x cheaper per token.
Thinking Machines Lab · Moonshot AI · Updated for 2026
Which is better?
Inkling-Small outperforms in 1 benchmarks (Toolathlon), while Kimi K2.6 is better at 8 benchmarks (AIME 2026, BrowseComp, CharXiv-R, GPQA, Humanity's Last Exam, MMMU-Pro, SciCode, SWE-Bench Pro). Kimi K2.6 significantly outperforms across most benchmarks.
On price, Inkling-Small is roughly 2.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Kimi K2.6 also accepts a larger context window (262,144 input tokens), making it the stronger choice for long documents and large codebases.
Based on current benchmark, pricing, and model metadata for 2026.
Choose Inkling-Small
- cost matters — it's about 2.7x cheaper per token
- you want the most recent training data — it shipped Jul 2026
Choose Kimi K2.6
- you want the strongest raw capability — it leads on 9 of 10 shared benchmarks
- you process long inputs — it offers a 262,144 token context window
At a glance
The differences that matter most.
Performance Benchmarks
Comparative analysis across standard metrics
Inkling-Small outperforms in 1 benchmarks (Toolathlon), while Kimi K2.6 is better at 8 benchmarks (AIME 2026, BrowseComp, CharXiv-R, GPQA, Humanity's Last Exam, MMMU-Pro, SciCode, SWE-Bench Pro).
Kimi K2.6 significantly outperforms across most benchmarks.
Arena Performance
Playground indexes and blind preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, Inkling-Small ($0.30/1M tokens) is 2.5x cheaper than Kimi K2.6 ($0.75/1M tokens).
For output processing, Inkling-Small ($1.20/1M tokens) is 2.9x cheaper than Kimi K2.6 ($3.50/1M tokens).
In conclusion, Kimi K2.6 is more expensive than Inkling-Small.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K2.6 has 724.0B more parameters than Inkling-Small, making it 262.3% larger.
Context Window
Maximum input and output token capacity
Kimi K2.6 accepts 262,144 input tokens compared to Inkling-Small's 256,000 tokens. Inkling-Small can generate longer responses up to 256,000 tokens, while Kimi K2.6 is limited to 131,072 tokens.
Input Capabilities
Supported data types and modalities
Both Inkling-Small and Kimi K2.6 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Inkling-Small
Kimi K2.6
License
Usage and distribution terms
Inkling-Small is licensed under Apache 2.0, while Kimi K2.6 uses Modified MIT License.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
Modified MIT License
Open weights
Release Timeline
When each model was launched
Inkling-Small was released on 2026-07-30, while Kimi K2.6 was released on 2026-04-20.
Inkling-Small is 3 months newer than Kimi K2.6.
Jul 30, 2026
3 weeks ago
3mo newerApr 20, 2026
4 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. Kimi K2.6 is available from DeepInfra, Fireworks, Moonshot AI, Novita, Together.
Inkling-Small
Kimi K2.6
Outputs Comparison
Judge for yourself.
Run your own prompts against Inkling-Small and Kimi K2.6 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Inkling-Small vs Kimi K2.6.