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DeepSeek-V4.1-Flash vs GPT-5 Codex

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 26.6.

DeepSeek · OpenAI · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash leads the overall LLM Stats Score 51.8 to 26.6, ranking #13 overall.

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 #13 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • 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 Codex

  • you are already invested in the OpenAI ecosystem

At a glance

The differences that matter most.

DeepSeek-V4.1-Flash
DeepSeek
GPT-5 Codex
OpenAI
Core performance indexes
LLM Stats Score
51.8
#13
26.6
#149
Reasoning
48.9
#18
26.5
#147
Coding
44.2
#5
19.3
#107
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.22 / M
— / M
Output price
$0.66 / M
— / M
Context window
1,040,000
—

Individual benchmarks

20 reported for DeepSeek-V4.1-Flash · 1 for GPT-5 Codex

No common benchmarks found

DeepSeek-V4.1-Flash and GPT-5 Codexdon'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

Context Window

Maximum input and output token capacity

Only DeepSeek-V4.1-Flash specifies input context (1,040,000 tokens). Only DeepSeek-V4.1-Flash specifies output context (393,216 tokens).

DeepSeek
DeepSeek-V4.1-Flash
Input1,040,000 tokens
Output393,216 tokens
OpenAI
GPT-5 Codex
Input- tokens
Output- tokens
Sun Sep 20 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek-V4.1-Flash supports multimodal inputs, whereas GPT-5 Codex does not.

DeepSeek-V4.1-Flash can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V4.1-Flash

Text
Images
Audio
Video

GPT-5 Codex

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash is licensed under MIT, while GPT-5 Codex uses a proprietary license.

License differences may affect how you can use these models in commercial or open-source projects.

DeepSeek-V4.1-Flash

MIT

Open weights

GPT-5 Codex

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash was released on 2026-09-10, while GPT-5 Codex was released on 2025-09-15.

DeepSeek-V4.1-Flash is 12 months newer than GPT-5 Codex.

DeepSeek-V4.1-Flash

Sep 10, 2026

1 weeks ago

12mo newer
GPT-5 Codex

Sep 15, 2025

1.0 years ago

Knowledge Cutoff

When training data ends

GPT-5 Codex has a documented knowledge cutoff of 2024-09-30, while DeepSeek-V4.1-Flash's cutoff date is not specified.

We can confirm GPT-5 Codex's training data extends to 2024-09-30, but cannot make a direct comparison without DeepSeek-V4.1-Flash's cutoff date.

DeepSeek-V4.1-Flash

—

GPT-5 Codex

Sep 2024

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash and GPT-5 Codex side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash
✓ Preferred
GPT-5 Codex
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash vs GPT-5 Codex.

Which is better, DeepSeek-V4.1-Flash or GPT-5 Codex?

DeepSeek-V4.1-Flash leads the LLM Stats Score 51.8 to 26.6. DeepSeek-V4.1-Flash is made by DeepSeek and GPT-5 Codex is made by OpenAI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does DeepSeek-V4.1-Flash compare to GPT-5 Codex in benchmarks?

DeepSeek-V4.1-Flash scores CodeForces: 100.0%, GPQA: 90.9%, Terminal-Bench 2.1: 90.6%, BabyVision: 89.6%, CyberGym: 88.1%. GPT-5 Codex scores SWE-Bench Verified: 74.5%.

What are the context window sizes for DeepSeek-V4.1-Flash and GPT-5 Codex?

DeepSeek-V4.1-Flash supports 1.0M tokens and GPT-5 Codex supports an unknown number of tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between DeepSeek-V4.1-Flash and GPT-5 Codex?

Key differences include LLM Stats Score (51.8 vs 26.6), multimodal support (yes vs no), licensing (MIT vs Proprietary). See the full comparison above for benchmark-by-benchmark results.

Who makes DeepSeek-V4.1-Flash and GPT-5 Codex?

DeepSeek-V4.1-Flash is developed by DeepSeek and GPT-5 Codex is developed by OpenAI.

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