The AI arena is free today

Open Superagent

DeepSeek-V4.1-Flash-1017 vs GPT-5 Codex

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.2 to 26.5.

DeepSeek · OpenAI · Updated for 2026

Which is better?

DeepSeek-V4.1-Flash-1017 leads the overall LLM Stats Score 51.2 to 26.5, ranking #15 overall.

Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.

Choose DeepSeek-V4.1-Flash-1017

  • overall performance matters — it scores 51.2 and ranks #15 on LLM Stats
  • your work emphasizes reasoning and coding — it leads those capability indexes
  • you want the most recent training data — it shipped Oct 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-1017
DeepSeek
GPT-5 Codex
OpenAI
Core performance indexes
LLM Stats Score
51.2
#15
26.5
#170
Reasoning
48.8
#18
26.4
#169
Coding
39.3
#14
19.3
#122
Cost, coverage & limits
Benchmark wins
—
—
Input price
$0.30 / M
— / M
Output price
$1.20 / M
— / M
Context window
1,048,576
—

Individual benchmarks

11 reported for DeepSeek-V4.1-Flash-1017 · 1 for GPT-5 Codex

No common benchmarks found

DeepSeek-V4.1-Flash-1017 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-1017 specifies input context (1,048,576 tokens). Only DeepSeek-V4.1-Flash-1017 specifies output context (393,216 tokens).

DeepSeek
DeepSeek-V4.1-Flash-1017
Input1,048,576 tokens
Output393,216 tokens
OpenAI
GPT-5 Codex
Input- tokens
Output- tokens
Sat Oct 24 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

DeepSeek-V4.1-Flash-1017 supports multimodal inputs, whereas GPT-5 Codex does not.

DeepSeek-V4.1-Flash-1017 can handle both text and other forms of data like images, making it suitable for multimodal applications.

DeepSeek-V4.1-Flash-1017

Text
Images
Audio
Video

GPT-5 Codex

Text
Images
Audio
Video

License

Usage and distribution terms

DeepSeek-V4.1-Flash-1017 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-1017

MIT

Open weights

GPT-5 Codex

Proprietary

Closed source

Release Timeline

When each model was launched

DeepSeek-V4.1-Flash-1017 was released on 2026-10-17, while GPT-5 Codex was released on 2025-09-15.

DeepSeek-V4.1-Flash-1017 is 13 months newer than GPT-5 Codex.

DeepSeek-V4.1-Flash-1017

Oct 17, 2026

5 days ago

1.1yr newer
GPT-5 Codex

Sep 15, 2025

1.1 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-1017'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-1017's cutoff date.

DeepSeek-V4.1-Flash-1017

—

GPT-5 Codex

Sep 2024

Outputs Comparison

Notice missing or incorrect data?

Judge for yourself.

Run your own prompts against DeepSeek-V4.1-Flash-1017 and GPT-5 Codex side-by-side, then vote on the output you prefer.

DeepSeek-V4.1-Flash-1017
✓ Preferred
GPT-5 Codex
Open in Playground

FAQ

Common questions about DeepSeek-V4.1-Flash-1017 vs GPT-5 Codex.

Which is better, DeepSeek-V4.1-Flash-1017 or GPT-5 Codex?

DeepSeek-V4.1-Flash-1017 leads the LLM Stats Score 51.2 to 26.5. DeepSeek-V4.1-Flash-1017 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-1017 compare to GPT-5 Codex in benchmarks?

DeepSeek-V4.1-Flash-1017 scores BabyVision: 92.5%, Chartography: 83.0%, DeepSWE 1.1: 77.0%, NL2Repo: 68.2%, AutomationBench: 60.5%. GPT-5 Codex scores SWE-Bench Verified: 74.5%.

What are the context window sizes for DeepSeek-V4.1-Flash-1017 and GPT-5 Codex?

DeepSeek-V4.1-Flash-1017 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-1017 and GPT-5 Codex?

Key differences include LLM Stats Score (51.2 vs 26.5), 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-1017 and GPT-5 Codex?

DeepSeek-V4.1-Flash-1017 is developed by DeepSeek and GPT-5 Codex is developed by OpenAI.

Related comparisons