DeepSeek-V4-Flash-0731 vs GPT-5.6 Luna
DeepSeek-V4-Flash-0731 and GPT-5.6 Luna are closely matched at 44.7 and 45.1 on the LLM Stats Score. DeepSeek-V4-Flash-0731 is 5.0x cheaper per token.
DeepSeek · OpenAI · Updated for 2026
Which is better?
DeepSeek-V4-Flash-0731 and GPT-5.6 Luna are closely matched on the overall LLM Stats Score at 44.7 and 45.1.
In the 5 individual benchmarks reported for both models, GPT-5.6 Luna wins 3; this is a narrower head-to-head signal than the composite indexes.
On price, DeepSeek-V4-Flash-0731 is roughly 5.0x 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-Flash-0731
- cost matters — it's about 5.0x cheaper per token
- you want the most recent training data — it shipped Jul 2026
- you need open weights you can self-host or fine-tune
Choose GPT-5.6 Luna
- you value its reported benchmark strengths — it wins 3 of 5 exact shared results
- 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
9 reported for DeepSeek-V4-Flash-0731 · 45 for GPT-5.6 Luna
DeepSeek-V4-Flash-0731 outperforms in 2 benchmarks (AutomationBench, Toolathlon), while GPT-5.6 Luna is better at 3 benchmarks (Agents' Last Exam, DeepSWE, Terminal-Bench 2.1).
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, DeepSeek-V4-Flash-0731 ($0.06/1M tokens) is 3.3x cheaper than GPT-5.6 Luna ($0.20/1M tokens).
For output processing, DeepSeek-V4-Flash-0731 ($0.18/1M tokens) is 6.7x cheaper than GPT-5.6 Luna ($1.20/1M tokens).
In conclusion, GPT-5.6 Luna is more expensive than DeepSeek-V4-Flash-0731.*
* 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-Flash-0731's 1,048,576 tokens. DeepSeek-V4-Flash-0731 can generate longer responses up to 1,048,576 tokens, while GPT-5.6 Luna is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GPT-5.6 Luna supports multimodal inputs, whereas DeepSeek-V4-Flash-0731 does not.
GPT-5.6 Luna can handle both text and other forms of data like images, making it suitable for multimodal applications.
DeepSeek-V4-Flash-0731
GPT-5.6 Luna
License
Usage and distribution terms
DeepSeek-V4-Flash-0731 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-Flash-0731 was released on 2026-07-31, while GPT-5.6 Luna was released on 2026-07-09.
DeepSeek-V4-Flash-0731 is 1 month newer than GPT-5.6 Luna.
Jul 31, 2026
1 months ago
3w 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-Flash-0731'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-Flash-0731's cutoff date.
—
Feb 2026
Provider Availability
DeepSeek-V4-Flash-0731 is available from DeepInfra, Novita, Fireworks. GPT-5.6 Luna is available from OpenAI.
DeepSeek-V4-Flash-0731
GPT-5.6 Luna
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-V4-Flash-0731 and GPT-5.6 Luna side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V4-Flash-0731 vs GPT-5.6 Luna.