DeepSeek-V4.1-Flash vs GPT-5.6 Luna
DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 45.1. DeepSeek-V4.1-Flash is 1.4x cheaper per token.
DeepSeek · OpenAI · Updated for 2026
Which is better?
DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to 45.1, ranking #12 overall.
In the 8 individual benchmarks reported for both models, DeepSeek-V4.1-Flash wins 6; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V4.1-Flash is roughly 1.4x 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 DeepSeek-V4.1-Flash
- overall performance matters — it scores 51.8 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 6 of 8 exact shared results
- cost matters — it's about 1.4x 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
Choose GPT-5.6 Luna
- you process long inputs — it offers a 1,050,000 token context window
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
20 reported for DeepSeek-V4.1-Flash · 45 for GPT-5.6 Luna
DeepSeek-V4.1-Flash outperforms in 6 benchmarks (AutomationBench, DeepSWE 1.1, ExploitGym, SEC-bench Pro, Terminal-Bench 2.1, Terminal-Bench 4.0), while GPT-5.6 Luna is better at 2 benchmarks (Agents' Last Exam, GPQA).
DeepSeek-V4.1-Flash shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, DeepSeek-V4.1-Flash ($0.22/1M tokens) is 1.1x more expensive than GPT-5.6 Luna ($0.20/1M tokens).
For output processing, DeepSeek-V4.1-Flash ($0.66/1M tokens) is 1.8x cheaper than GPT-5.6 Luna ($1.20/1M tokens).
In conclusion, GPT-5.6 Luna is more expensive than DeepSeek-V4.1-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 DeepSeek-V4.1-Flash's 1,040,000 tokens. DeepSeek-V4.1-Flash can generate longer responses up to 393,216 tokens, while GPT-5.6 Luna is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Both DeepSeek-V4.1-Flash and GPT-5.6 Luna support multimodal inputs.
They are both capable of processing various types of data, offering versatility in application.
DeepSeek-V4.1-Flash
GPT-5.6 Luna
License
Usage and distribution terms
DeepSeek-V4.1-Flash is licensed under MIT, while GPT-5.6 Luna uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
DeepSeek-V4.1-Flash was released on 2026-09-10, while GPT-5.6 Luna was released on 2026-07-09.
DeepSeek-V4.1-Flash is 2 months newer than GPT-5.6 Luna.
Sep 10, 2026
4 days ago
2mo newerJul 9, 2026
2 months ago
Knowledge Cutoff
When training data ends
GPT-5.6 Luna has a documented knowledge cutoff of 2026-02-16, while DeepSeek-V4.1-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 DeepSeek-V4.1-Flash's cutoff date.
—
Feb 2026
Provider Availability
DeepSeek-V4.1-Flash is available from Fireworks, DeepInfra, DeepSeek, Novita. GPT-5.6 Luna is available from OpenAI.
DeepSeek-V4.1-Flash
GPT-5.6 Luna
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4.1-Flash and GPT-5.6 Luna side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4.1-Flash vs GPT-5.6 Luna.