GPT-5.6 Luna vs Inkling-Small
GPT-5.6 Luna leads the LLM Stats Score 46.5 to 39.3. GPT-5.6 Luna is 1.2x cheaper per token.
OpenAI · Thinking Machines Lab · Updated for 2026
Which is better?
GPT-5.6 Luna leads the overall LLM Stats Score 46.5 to 39.3, ranking #21 overall.
In the 7 individual benchmarks reported for both models, GPT-5.6 Luna wins 6; this is a narrower head-to-head signal than the composite indexes.
On price, GPT-5.6 Luna is roughly 1.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-5.6 Luna also accepts a larger context window (1,050,000 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 GPT-5.6 Luna
- overall performance matters — it scores 46.5 and ranks #21 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 6 of 7 exact shared results
- cost matters — it's about 1.2x cheaper per token
- you process long inputs — it offers a 1,050,000 token context window
Choose Inkling-Small
- you want the most recent training data — it shipped Jul 2026
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
44 reported for GPT-5.6 Luna · 24 for Inkling-Small
GPT-5.6 Luna outperforms in 6 benchmarks (Artificial Analysis, BrowseComp, GPQA, MMMU-Pro, SWE-Bench Pro, Terminal-Bench 2.1), while Inkling-Small is better at 1 benchmark (Toolathlon).
GPT-5.6 Luna 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, GPT-5.6 Luna ($0.20/1M tokens) is 1.5x cheaper than Inkling-Small ($0.30/1M tokens).
For output processing, GPT-5.6 Luna ($1.20/1M tokens) costs the same as Inkling-Small ($1.20/1M tokens).
In conclusion, Inkling-Small is more expensive than GPT-5.6 Luna.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-5.6 Luna accepts 1,050,000 input tokens compared to Inkling-Small's 256,000 tokens. Inkling-Small can generate longer responses up to 256,000 tokens, while GPT-5.6 Luna is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both GPT-5.6 Luna and Inkling-Small support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-5.6 Luna
Inkling-Small
License
Usage and distribution terms
GPT-5.6 Luna is licensed under a proprietary license, while Inkling-Small uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
GPT-5.6 Luna was released on 2026-07-09, while Inkling-Small was released on 2026-07-30.
Inkling-Small is 1 month newer than GPT-5.6 Luna.
Jul 9, 2026
1 months ago
Jul 30, 2026
4 weeks ago
3w newerKnowledge Cutoff
When training data ends
GPT-5.6 Luna has a documented knowledge cutoff of 2026-02-16, while Inkling-Small's cutoff date is not specified.
We can confirm GPT-5.6 Luna's training data extends to 2026-02-16, but cannot make a direct comparison without Inkling-Small's cutoff date.
Feb 2026
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Provider Availability
GPT-5.6 Luna is available from OpenAI. Inkling-Small is available from Thinking Machines Lab.
GPT-5.6 Luna
Inkling-Small
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5.6 Luna and Inkling-Small side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5.6 Luna vs Inkling-Small.