GPT OSS 120B High vs Qwen3 VL 30B A3B Instruct
GPT OSS 120B High leads the LLM Stats Score 25.5 to 16.5. GPT OSS 120B High is 1.6x cheaper per token.
OpenAI · Alibaba Cloud / Qwen Team · Updated for 2026
Which is better?
GPT OSS 120B High leads the overall LLM Stats Score 25.5 to 16.5, ranking #148 overall.
In the 4 individual benchmarks reported for both models, GPT OSS 120B High wins 4; this is a narrower head-to-head signal than the composite indexes.
On price, GPT OSS 120B High is roughly 1.6x 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 120B High
- overall performance matters — it scores 25.5 and ranks #148 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 4 of 4 exact shared results
- cost matters — it's about 1.6x cheaper per token
Choose Qwen3 VL 30B A3B Instruct
- you want the most recent training data — it shipped Sep 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
7 reported for GPT OSS 120B High · 50 for Qwen3 VL 30B A3B Instruct
GPT OSS 120B High outperforms in 4 benchmarks (AIME 2025, GPQA, LiveCodeBench v6, MMLU-Pro), while Qwen3 VL 30B A3B Instruct is better at 0 benchmarks.
GPT OSS 120B High significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT OSS 120B High ($0.10/1M tokens) is 2.0x cheaper than Qwen3 VL 30B A3B Instruct ($0.20/1M tokens).
For output processing, GPT OSS 120B High ($0.50/1M tokens) is 1.4x cheaper than Qwen3 VL 30B A3B Instruct ($0.70/1M tokens).
In conclusion, Qwen3 VL 30B A3B Instruct is more expensive than GPT OSS 120B High.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GPT OSS 120B High has 85.8B more parameters than Qwen3 VL 30B A3B Instruct, making it 276.8% larger.
Context Window
Maximum input and output token capacity
Both models have the same input context window of 131,072 tokens. GPT OSS 120B High can generate longer responses up to 131,072 tokens, while Qwen3 VL 30B A3B Instruct is limited to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
Qwen3 VL 30B A3B Instruct supports multimodal inputs, whereas GPT OSS 120B High does not.
Qwen3 VL 30B A3B Instruct can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT OSS 120B High
Qwen3 VL 30B A3B Instruct
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 120B High was released on 2025-08-05, while Qwen3 VL 30B A3B Instruct was released on 2025-09-22.
Qwen3 VL 30B A3B Instruct is 2 months newer than GPT OSS 120B High.
Aug 5, 2025
1.1 years ago
Sep 22, 2025
11 months 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 120B High is available from OpenAI, Fireworks. Qwen3 VL 30B A3B Instruct is available from Novita, DeepInfra.
GPT OSS 120B High
Qwen3 VL 30B A3B Instruct
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT OSS 120B High and Qwen3 VL 30B A3B Instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT OSS 120B High vs Qwen3 VL 30B A3B Instruct.