Model Comparison

Comprehensive side-by-side analysis of model capabilities and performance

OpenAI

GPT-5 nano

OpenAI

GPT-5 nano is a multimodal language model developed by OpenAI. The model shows competitive results across 5 benchmarks. It excels particularly in AIME 2025 (85.2%), HMMT 2025 (75.6%), GPQA (71.2%). It supports a 528K token context window for handling large documents. The model is available through 2 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents OpenAI's latest advancement in AI technology.

Alibaba

Qwen3 235B A22B

Alibaba

Qwen3 235B A22B is a language model developed by Alibaba. It achieves strong performance with an average score of 76.2% across 23 benchmarks. It excels particularly in Arena Hard (95.6%), GSM8k (94.4%), BBH (88.9%). The model shows particular specialization in math tasks with an average performance of 83.3%. It supports a 256K token context window for handling large documents. The model is available through 4 API providers. It's licensed for commercial use, making it suitable for enterprise applications. Released in 2025, it represents Alibaba's latest advancement in AI technology.

Alibaba

Qwen3 235B A22B

Alibaba

2025-04-29

OpenAI

GPT-5 nano

OpenAI

2025-08-07

3 months newer

Pricing Comparison

Cost per million tokens (USD)

OpenAI

GPT-5 nano

Input:$0.05
Output:$0.40
Alibaba

Qwen3 235B A22B

$0.25 cheaper
Input:$0.10
Output:$0.10

Performance Metrics

Context window and performance specifications

OpenAI

GPT-5 nano

Larger context
Max Context:528.0K
Alibaba

Qwen3 235B A22B

Max Context:256.0K
Parameters:235.0B

Average performance across 2 common benchmarks

OpenAI

GPT-5 nano

+13.7%
Average Score:78.2%
Alibaba

Qwen3 235B A22B

Average Score:64.5%

Performance comparison across key benchmark categories

OpenAI

GPT-5 nano

math
9.6%
general
60.2%
Alibaba

Qwen3 235B A22B

math
+73.7%
83.3%
general
+14.6%
74.8%
Benchmark Scores - Detailed View
Side-by-side comparison of all benchmark scores
Knowledge Cutoff
Training data recency comparison

GPT-5 nano

2024-05-30

More recent knowledge cutoff means awareness of newer technologies and frameworks

Provider Availability & Performance

Available providers and their performance metrics

OpenAI

GPT-5 nano

2 providers

ZeroEval

Throughput: 500 tok/s
Latency: 0.3ms

OpenAI

Throughput: 500 tok/s
Latency: 0.3ms
Alibaba

Qwen3 235B A22B

4 providers

Together

Throughput: 23.74 tok/s
Latency: 0.79ms

DeepInfra

Throughput: 21.74 tok/s
Latency: 1.23ms

Fireworks

Throughput: 68.17 tok/s
Latency: 0.78ms

Novita

Throughput: 38.51 tok/s
Latency: 1.02ms
OpenAI

GPT-5 nano

+13.7%
Avg Score:78.2%
Providers:2
Alibaba

Qwen3 235B A22B

Avg Score:64.5%
Providers:4