GPT-4o vs Qwen3 30B A3B
Qwen3 30B A3B leads the LLM Stats Score 17.3 to 14.1. Qwen3 30B A3B is 29.2x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
Qwen3 30B A3B leads the overall LLM Stats Score 17.3 to 14.1, ranking #216 overall.
In the 3 individual benchmarks reported for both models, Qwen3 30B A3B wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, Qwen3 30B A3B is roughly 29.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT-4o
- you want predictable pricing at $2.50/M input and $10.00/M output
Choose Qwen3 30B A3B
- overall performance matters — it scores 17.3 and ranks #216 on LLM Stats
- your work emphasizes coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 2 of 3 exact shared results
- cost matters — it's about 29.2x cheaper per token
- you want the most recent training data — it shipped Apr 2025
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
38 reported for GPT-4o · 8 for Qwen3 30B A3B
GPT-4o outperforms in 1 benchmarks (GPQA), while Qwen3 30B A3B is better at 2 benchmarks (AIME 2024, Multi-IF).
Qwen3 30B A3B shows notably better performance in the majority of benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT-4o ($2.50/1M tokens) is 25.0x more expensive than Qwen3 30B A3B ($0.10/1M tokens).
For output processing, GPT-4o ($10.00/1M tokens) is 33.3x more expensive than Qwen3 30B A3B ($0.30/1M tokens).
In conclusion, GPT-4o is more expensive than Qwen3 30B A3B.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Both models have the same input context window of 128,000 tokens. Qwen3 30B A3B can generate longer responses up to 128,000 tokens, while GPT-4o is limited to 16,384 tokens.
Input capabilities
Documented input modalities across available providers
GPT-4o supports multimodal inputs, whereas Qwen3 30B A3B does not.
GPT-4o can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-4o
Qwen3 30B A3B
License
Usage and distribution terms
GPT-4o is licensed under a proprietary license, while Qwen3 30B A3B uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
Apache 2.0
Open weights
Release Timeline
When each model was launched
GPT-4o was released on 2024-08-06, while Qwen3 30B A3B was released on 2025-04-29.
Qwen3 30B A3B is 9 months newer than GPT-4o.
Aug 6, 2024
2.1 years ago
Apr 29, 2025
1.4 years ago
8mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GPT-4o is available from Azure, OpenAI. Qwen3 30B A3B is available from DeepInfra, Novita, Fireworks.
GPT-4o
Qwen3 30B A3B
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-4o and Qwen3 30B A3B side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-4o vs Qwen3 30B A3B.