GPT-6 Luna vs IBM Granite 4.2 30B
GPT-6 Luna leads the LLM Stats Score 43.1 to 23.3. GPT-6 Luna is 1.4x cheaper per token.
OpenAI · IBM · Updated for 2026
Which is better?
GPT-6 Luna leads the overall LLM Stats Score 43.1 to 23.3, ranking #55 overall.
On price, GPT-6 Luna is roughly 1.4x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-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-6 Luna
- overall performance matters — it scores 43.1 and ranks #55 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- cost matters — it's about 1.4x cheaper per token
- you process long inputs — it offers a 1,050,000 token context window
- you want the most recent training data — it shipped Sep 2026
Choose IBM Granite 4.2 30B
- 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
5 reported for GPT-6 Luna · 18 for IBM Granite 4.2 30B
GPT-6 Luna and IBM Granite 4.2 30Bdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-6 Luna ($0.10/1M tokens) is 1.6x cheaper than IBM Granite 4.2 30B ($0.16/1M tokens).
For output processing, GPT-6 Luna ($0.50/1M tokens) is 1.3x cheaper than IBM Granite 4.2 30B ($0.65/1M tokens).
In conclusion, IBM Granite 4.2 30B is more expensive than GPT-6 Luna.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-6 Luna accepts 1,050,000 input tokens compared to IBM Granite 4.2 30B's 131,072 tokens. IBM Granite 4.2 30B can generate longer responses up to 131,072 tokens, while GPT-6 Luna is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GPT-6 Luna supports multimodal inputs, whereas IBM Granite 4.2 30B does not.
GPT-6 Luna can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-6 Luna
IBM Granite 4.2 30B
License
Usage and distribution terms
GPT-6 Luna is licensed under a proprietary license, while IBM Granite 4.2 30B 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-6 Luna was released on 2026-09-22, while IBM Granite 4.2 30B was released on 2026-08-25.
GPT-6 Luna is 1 month newer than IBM Granite 4.2 30B.
Sep 22, 2026
4 weeks ago
4w newerAug 25, 2026
1 months ago
Knowledge Cutoff
When training data ends
GPT-6 Luna has a documented knowledge cutoff of 2026-05-18, while IBM Granite 4.2 30B's cutoff date is not specified.
We can confirm GPT-6 Luna's training data extends to 2026-05-18, but cannot make a direct comparison without IBM Granite 4.2 30B's cutoff date.
May 2026
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Provider Availability
GPT-6 Luna is available from OpenAI. IBM Granite 4.2 30B is available from DeepInfra.
GPT-6 Luna
IBM Granite 4.2 30B
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-6 Luna and IBM Granite 4.2 30B side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-6 Luna vs IBM Granite 4.2 30B.