Inkling vs MAI-Code-1.1-Flash
Inkling and MAI-Code-1.1-Flash are closely matched at 37.2 and 27.8 on the LLM Stats Score. MAI-Code-1.1-Flash is 3.8x cheaper per token.
Thinking Machines Lab · Microsoft · Updated for 2026
Which is better?
Inkling and MAI-Code-1.1-Flash are closely matched on the overall LLM Stats Score at 37.2 and 27.8.
In the 2 individual benchmarks reported for both models, Inkling wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, MAI-Code-1.1-Flash is roughly 3.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Inkling also accepts a larger context window (524,288 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
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- you process long inputs — it offers a 524,288 token context window
- you need open weights you can self-host or fine-tune
Choose MAI-Code-1.1-Flash
- cost matters — it's about 3.8x cheaper per token
- you want the most recent training data — it shipped Aug 2026
At a glance
The differences that matter most.
Individual benchmarks
16 reported for Inkling · 2 for MAI-Code-1.1-Flash
Inkling outperforms in 2 benchmarks (SWE-Bench Verified, Terminal-Bench 2.1), while MAI-Code-1.1-Flash is better at 0 benchmarks.
Inkling 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 4.7x more expensive than MAI-Code-1.1-Flash ($0.20/1M tokens).
For output processing, Inkling ($4.05/1M tokens) is 3.4x more expensive than MAI-Code-1.1-Flash ($1.20/1M tokens).
In conclusion, Inkling is more expensive than MAI-Code-1.1-Flash.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Inkling has 837.0B more parameters than MAI-Code-1.1-Flash, making it 606.5% larger.
Context Window
Maximum input and output token capacity
Inkling accepts 524,288 input tokens compared to MAI-Code-1.1-Flash's 256,000 tokens. Only Inkling specifies output context (524,288 tokens).
Input capabilities
Documented input modalities across available providers
Both Inkling and MAI-Code-1.1-Flash support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
Inkling
MAI-Code-1.1-Flash
License
Usage and distribution terms
Inkling is licensed under Apache 2.0, while MAI-Code-1.1-Flash uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
Inkling was released on 2026-07-21, while MAI-Code-1.1-Flash was released on 2026-08-11.
MAI-Code-1.1-Flash is 1 month newer than Inkling.
Jul 21, 2026
2 months ago
Aug 11, 2026
1 months ago
3w 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 is available from DeepInfra. MAI-Code-1.1-Flash is available from GitHub Copilot.
Inkling
MAI-Code-1.1-Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against Inkling and MAI-Code-1.1-Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about Inkling vs MAI-Code-1.1-Flash.