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GPT-5 Codex vs GPT-6 Astra

GPT-6 Astra leads the LLM Stats Score 60.7 to 26.8.

OpenAI · OpenAI · Updated for 2026

Which is better?

GPT-6 Astra leads the overall LLM Stats Score 60.7 to 26.8, ranking #1 overall.

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

Choose GPT-5 Codex

  • you are already invested in the OpenAI ecosystem

Choose GPT-6 Astra

  • overall performance matters — it scores 60.7 and ranks #1 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

At a glance

The differences that matter most.

GPT-5 Codex
OpenAI
GPT-6 Astra
OpenAI
Core performance indexes
LLM Stats Score
26.8
#138
60.7
#1
Reasoning
26.7
#137
58.7
#1
Coding
19.4
#99
49.0
#1
Cost, coverage & limits
Benchmark wins
—
—
Input price
— / M
$10.00 / M
Output price
— / M
$50.00 / M
Context window
—
1,050,000

Individual benchmarks

1 reported for GPT-5 Codex · 22 for GPT-6 Astra

No common benchmarks found

GPT-5 Codex and GPT-6 Astradon'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 GPT-6 Astra specifies input context (1,050,000 tokens). Only GPT-6 Astra specifies output context (128,000 tokens).

OpenAI
GPT-5 Codex
Input- tokens
Output- tokens
OpenAI
GPT-6 Astra
Input1,050,000 tokens
Output128,000 tokens
Sat Sep 05 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

GPT-6 Astra supports multimodal inputs, whereas GPT-5 Codex does not.

GPT-6 Astra can handle both text and other forms of data like images, making it suitable for multimodal applications.

GPT-5 Codex

Text
Images
Audio
Video

GPT-6 Astra

Text
Images
Audio
Video

License

Usage and distribution terms

Both models are licensed under proprietary licenses.

Both models have usage restrictions defined by their respective organizations.

GPT-5 Codex

Proprietary

Closed source

GPT-6 Astra

Proprietary

Closed source

Release Timeline

When each model was launched

GPT-5 Codex was released on 2025-09-15, while GPT-6 Astra was released on 2026-09-04.

GPT-6 Astra is 12 months newer than GPT-5 Codex.

GPT-5 Codex

Sep 15, 2025

11 months ago

GPT-6 Astra

Sep 4, 2026

1 days ago

11mo newer

Knowledge Cutoff

When training data ends

GPT-5 Codex has a knowledge cutoff of 2024-09-30, while GPT-6 Astra has a cutoff of 2026-04-30.

GPT-6 Astra has more recent training data (up to 2026-04-30), making it potentially better informed about events through that date compared to GPT-5 Codex (2024-09-30).

GPT-5 Codex

Sep 2024

GPT-6 Astra

Apr 2026

1.6 yr newer

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion→

Judge for yourself.

Run your own prompts against GPT-5 Codex and GPT-6 Astra side-by-side, then vote on the output you prefer.

GPT-5 Codex
✓ Preferred
GPT-6 Astra
Open in Playground

FAQ

Common questions about GPT-5 Codex vs GPT-6 Astra.

Which is better, GPT-5 Codex or GPT-6 Astra?

GPT-6 Astra leads the LLM Stats Score 60.7 to 26.8. GPT-5 Codex is made by OpenAI and GPT-6 Astra is made by OpenAI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GPT-5 Codex compare to GPT-6 Astra in benchmarks?

GPT-5 Codex scores SWE-Bench Verified: 74.5%. GPT-6 Astra scores ExploitBench: 100.0%, ARC-AGI-3: 99.9%, ARC-AGI: 98.5%, FrontierMath Tier 4 (v2): 97.6%, GPQA: 96.0%.

What are the context window sizes for GPT-5 Codex and GPT-6 Astra?

GPT-5 Codex supports an unknown number of tokens and GPT-6 Astra supports 1.1M tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GPT-5 Codex and GPT-6 Astra?

Key differences include LLM Stats Score (26.8 vs 60.7), multimodal support (no vs yes). See the full comparison above for benchmark-by-benchmark results.

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