GPT-5.6 Luna vs MiMo-V2.6-Flash
GPT-5.6 Luna and MiMo-V2.6-Flash are closely matched at 45.3 and 45.6 on the LLM Stats Score. MiMo-V2.6-Flash is 2.6x cheaper per token.
OpenAI · Xiaomi · Updated for 2026
Which is better?
GPT-5.6 Luna and MiMo-V2.6-Flash are closely matched on the overall LLM Stats Score at 45.3 and 45.6.
In the 7 individual benchmarks reported for both models, GPT-5.6 Luna wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, MiMo-V2.6-Flash is roughly 2.6x 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
- you value its reported benchmark strengths — it wins 4 of 7 exact shared results
- you process long inputs — it offers a 1,050,000 token context window
Choose MiMo-V2.6-Flash
- cost matters — it's about 2.6x cheaper per token
- you want the most recent training data — it shipped Sep 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
45 reported for GPT-5.6 Luna · 16 for MiMo-V2.6-Flash
GPT-5.6 Luna outperforms in 4 benchmarks (Agents' Last Exam, ExploitBench, ExploitGym, SEC-bench Pro), while MiMo-V2.6-Flash is better at 3 benchmarks (DeepSWE 1.1, Terminal-Bench 2.1, Terminal-Bench 4.0).
GPT-5.6 Luna has a slight edge in benchmark performance.
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 1.4x more expensive than MiMo-V2.6-Flash ($0.14/1M tokens).
For output processing, GPT-5.6 Luna ($1.20/1M tokens) is 4.3x more expensive than MiMo-V2.6-Flash ($0.28/1M tokens).
In conclusion, GPT-5.6 Luna is more expensive than MiMo-V2.6-Flash.*
* 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 MiMo-V2.6-Flash's 1,048,576 tokens. Only GPT-5.6 Luna specifies output context (128,000 tokens).
Input capabilities
Documented input modalities across available providers
Both GPT-5.6 Luna and MiMo-V2.6-Flash support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
GPT-5.6 Luna
MiMo-V2.6-Flash
License
Usage and distribution terms
GPT-5.6 Luna is licensed under a proprietary license, while MiMo-V2.6-Flash uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
MIT
Open weights
Release Timeline
When each model was launched
GPT-5.6 Luna was released on 2026-07-09, while MiMo-V2.6-Flash was released on 2026-09-22.
MiMo-V2.6-Flash is 3 months newer than GPT-5.6 Luna.
Jul 9, 2026
2 months ago
Sep 22, 2026
0 days ago
2mo newerKnowledge Cutoff
When training data ends
GPT-5.6 Luna has a documented knowledge cutoff of 2026-02-16, while MiMo-V2.6-Flash'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 MiMo-V2.6-Flash's cutoff date.
Feb 2026
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Provider Availability
GPT-5.6 Luna is available from OpenAI. MiMo-V2.6-Flash is available from Xiaomi.
GPT-5.6 Luna
MiMo-V2.6-Flash
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5.6 Luna and MiMo-V2.6-Flash side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5.6 Luna vs MiMo-V2.6-Flash.