GPT OSS 20B High vs Qwen3 VL 30B A3B Thinking
GPT OSS 20B High leads the LLM Stats Score 27.6 to 18.2. GPT OSS 20B High is 2.0x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GPT OSS 20B High leads the overall LLM Stats Score 27.6 to 18.2, ranking #156 overall.
The models split the 2 individual benchmarks reported for both models evenly.
On price, GPT OSS 20B High is roughly 2.0x 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 OSS 20B High
- overall performance matters — it scores 27.6 and ranks #156 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- cost matters — it's about 2.0x cheaper per token
Choose Qwen3 VL 30B A3B Thinking
- you want the most recent training data — it shipped Sep 2025
At a glance
The differences that matter most.
Individual benchmarks
2 reported for GPT OSS 20B High · 50 for Qwen3 VL 30B A3B Thinking
GPT OSS 20B High outperforms in 1 benchmarks (AIME 2025), while Qwen3 VL 30B A3B Thinking is better at 1 benchmark (GPQA).
Both models are evenly matched across the benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT OSS 20B High ($0.10/1M tokens) is 2.0x cheaper than Qwen3 VL 30B A3B Thinking ($0.20/1M tokens).
For output processing, GPT OSS 20B High ($0.50/1M tokens) is 2.0x cheaper than Qwen3 VL 30B A3B Thinking ($0.99/1M tokens).
In conclusion, Qwen3 VL 30B A3B Thinking is more expensive than GPT OSS 20B High.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
Qwen3 VL 30B A3B Thinking has 10.1B more parameters than GPT OSS 20B High, making it 48.3% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 131,072 tokens. GPT OSS 20B High can generate longer responses up to 131,072 tokens, while Qwen3 VL 30B A3B Thinking is limited to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
Qwen3 VL 30B A3B Thinking supports multimodal inputs, whereas GPT OSS 20B High does not.
Qwen3 VL 30B A3B Thinking can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT OSS 20B High
Qwen3 VL 30B A3B Thinking
License
Usage and distribution terms
Both models are licensed under Apache 2.0.
Both models share the same licensing terms, providing consistent usage rights.
Apache 2.0
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
GPT OSS 20B High was released on 2025-08-05, while Qwen3 VL 30B A3B Thinking was released on 2025-09-22.
Qwen3 VL 30B A3B Thinking is 2 months newer than GPT OSS 20B High.
Aug 5, 2025
1.2 years ago
Sep 22, 2025
1.0 years ago
1mo 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 OSS 20B High is available from OpenAI. Qwen3 VL 30B A3B Thinking is available from Novita, DeepInfra.
GPT OSS 20B High
Qwen3 VL 30B A3B Thinking
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT OSS 20B High and Qwen3 VL 30B A3B Thinking side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT OSS 20B High vs Qwen3 VL 30B A3B Thinking.