Inkling vs Kimi K3
Kimi K3 leads the LLM Stats Score 52.1 to 37.1. Inkling is 3.3x cheaper per token.
Thinking Machines Lab · Moonshot AI · Updated for 2026
Which is better?
Kimi K3 leads the overall LLM Stats Score 52.1 to 37.1, ranking #12 overall.
In the 4 individual benchmarks reported for both models, Kimi K3 wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, Inkling is roughly 3.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Kimi K3 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
- cost matters — it's about 3.3x cheaper per token
- you want the most recent training data — it shipped Jul 2026
Choose Kimi K3
- overall performance matters — it scores 52.1 and ranks #12 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 4 of 4 exact shared results
- 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
16 reported for Inkling · 31 for Kimi K3
Inkling outperforms in 0 benchmarks, while Kimi K3 is better at 4 benchmarks (CharXiv-R, MCP Atlas, MMMU-Pro, Terminal-Bench 2.1).
Kimi K3 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 ($0.95/1M tokens) is 3.0x cheaper than Kimi K3 ($2.85/1M tokens).
For output processing, Inkling ($4.05/1M tokens) is 3.5x cheaper than Kimi K3 ($14.25/1M tokens).
In conclusion, Kimi K3 is more expensive than Inkling.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Kimi K3 has 1825.0B more parameters than Inkling, making it 187.2% larger.
Context Window
Maximum input and output token capacity
Kimi K3 accepts 1,048,576 input tokens compared to Inkling's 524,288 tokens. Kimi K3 can generate longer responses up to 1,048,576 tokens, while Inkling is limited to 524,288 tokens.
Input capabilities
Documented input modalities across available providers
Both Inkling and Kimi K3 support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Inkling
Kimi K3
License
Usage and distribution terms
Inkling is licensed under Apache 2.0, while Kimi K3 uses Kimi K3 License.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
Kimi K3 License
Open weights
Release Timeline
When each model was launched
Inkling was released on 2026-07-21, while Kimi K3 was released on 2026-07-16.
Inkling is 0 month newer than Kimi K3.
Jul 21, 2026
2 months ago
5d newerJul 16, 2026
2 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 is available from DeepInfra. Kimi K3 is available from DeepInfra, Fireworks, Moonshot AI, Novita, Together.
Inkling
Kimi K3
Outputs Comparison
Judge for yourself.
Run your own prompts against Inkling and Kimi K3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Inkling vs Kimi K3.