Model Comparison

GPT-5.3 Codex vs Qwen3-Coder

Comparing GPT-5.3 Codex and Qwen3-Coder across benchmarks, pricing, and capabilities.

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Performance Benchmarks

Comparative analysis across standard metrics

No common benchmarks found

GPT-5.3 Codex and Qwen3-Coder don't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

Qwen3-Coder costs less

For input processing, GPT-5.3 Codex ($1.75/1M tokens) is 9.7x more expensive than Qwen3-Coder ($0.18/1M tokens).

For output processing, GPT-5.3 Codex ($14.00/1M tokens) is 77.8x more expensive than Qwen3-Coder ($0.18/1M tokens).

In conclusion, GPT-5.3 Codex is more expensive than Qwen3-Coder.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers

Mon May 18 2026 • llm-stats.com

GPT-5.3 Codex

Input tokens$1.75

Output tokens$14.00

Best providerOpenAI

Qwen3-Coder

Input tokens$0.18

Output tokens$0.18

Best providerDeepinfra

Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

GPT-5.3 Codex accepts 400,000 input tokens compared to Qwen3-Coder's 256,000 tokens. Qwen3-Coder can generate longer responses up to 256,000 tokens, while GPT-5.3 Codex is limited to 128,000 tokens.

GPT-5.3 Codex

Input400,000 tokens

Output128,000 tokens

Qwen3-Coder

Input256,000 tokens

Output256,000 tokens

Mon May 18 2026 • llm-stats.com

Input Capabilities

Supported data types and modalities

GPT-5.3 Codex supports multimodal inputs, whereas Qwen3-Coder does not.

GPT-5.3 Codex can handle both text and other forms of data like images, making it suitable for multimodal applications.

GPT-5.3 Codex

Text

Images

Audio

Video

Qwen3-Coder

Text

Images

Audio

Video

License

Usage and distribution terms

GPT-5.3 Codex is licensed under a proprietary license, while Qwen3-Coder uses Apache 2.0.

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

GPT-5.3 Codex

Proprietary

Closed source

Qwen3-Coder

Apache 2.0

Open weights

Release Timeline

When each model was launched

GPT-5.3 Codex was released on 2026-02-05, while Qwen3-Coder was released on 2025-01-01.

GPT-5.3 Codex is 13 months newer than Qwen3-Coder.

GPT-5.3 Codex

Feb 5, 2026

3 months ago

1.1yr newer

Qwen3-Coder

Jan 1, 2025

1.4 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

GPT-5.3 Codex is available from OpenAI. Qwen3-Coder is available from DeepInfra, Fireworks.

GPT-5.3 Codex

OpenAI

Input Price:Input: $1.75/1MOutput Price:Output: $14.00/1M

Qwen3-Coder

Deepinfra

Input Price:Input: $0.18/1MOutput Price:Output: $0.18/1M

Fireworks

Input Price:Input: $0.25/1MOutput Price:Output: $0.25/1M

* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

GPT-5.3 Codex

View details

OpenAI

Larger context window (400,000 tokens)

Supports multimodal inputs

Qwen3-Coder

View details

Alibaba Cloud / Qwen Team

Less expensive input tokens

Less expensive output tokens

Has open weights

Detailed Comparison

AI Model Comparison Table
Feature	GPT-5.3 Codex	Qwen3-Coder

FAQ

Common questions about GPT-5.3 Codex vs Qwen3-Coder.

Which is better, GPT-5.3 Codex or Qwen3-Coder?

GPT-5.3 Codex (OpenAI) and Qwen3-Coder (Alibaba Cloud / Qwen Team) each have strengths in different areas. Compare their benchmark scores, pricing, context windows, and capabilities above to determine which fits your needs.

How does GPT-5.3 Codex compare to Qwen3-Coder in benchmarks?

GPT-5.3 Codex scores SWE-Lancer (IC-Diamond subset): 81.4%, Cybersecurity CTFs: 77.6%, Terminal-Bench 2.0: 77.3%, OSWorld-Verified: 64.7%, SWE-Bench Pro: 56.8%.

Is GPT-5.3 Codex cheaper than Qwen3-Coder?

Qwen3-Coder is 9.7x cheaper for input tokens. GPT-5.3 Codex costs $1.75/M input and $14.00/M output via openai. Qwen3-Coder costs $0.18/M input and $0.18/M output via deepinfra.

What are the context window sizes for GPT-5.3 Codex and Qwen3-Coder?

GPT-5.3 Codex supports 400K tokens and Qwen3-Coder supports 256K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GPT-5.3 Codex and Qwen3-Coder?

Key differences include context window (400K vs 256K), input pricing ($1.75 vs $0.18/M), multimodal support (yes vs no), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.

Who makes GPT-5.3 Codex and Qwen3-Coder?

GPT-5.3 Codex is developed by OpenAI and Qwen3-Coder is developed by Alibaba Cloud / Qwen Team.