GPT OSS 120B High vs o4-mini
GPT OSS 120B High and o4-mini are closely matched at 25.4 and 27.5 on the LLM Stats Score. GPT OSS 120B High is 9.6x cheaper per token.
OpenAI · OpenAI · Updated for 2026
Which is better?
GPT OSS 120B High and o4-mini are closely matched on the overall LLM Stats Score at 25.4 and 27.5.
In the 2 individual benchmarks reported for both models, o4-mini wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, GPT OSS 120B High is roughly 9.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
o4-mini also accepts a larger context window (200,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT OSS 120B High
- cost matters — it's about 9.6x cheaper per token
- you want the most recent training data — it shipped Aug 2025
- you need open weights you can self-host or fine-tune
Choose o4-mini
- you value its reported benchmark strengths — it wins 2 of 2 exact shared results
- you process long inputs — it offers a 200,000 token context window
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 · 14 for o4-mini
GPT OSS 120B High outperforms in 0 benchmarks, while o4-mini is better at 2 benchmarks (AIME 2025, GPQA).
o4-mini 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 11.0x cheaper than o4-mini ($1.10/1M tokens).
For output processing, GPT OSS 120B High ($0.50/1M tokens) is 8.8x cheaper than o4-mini ($4.40/1M tokens).
In conclusion, o4-mini is more expensive than GPT OSS 120B High.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
o4-mini accepts 200,000 input tokens compared to GPT OSS 120B High's 131,072 tokens. GPT OSS 120B High can generate longer responses up to 131,072 tokens, while o4-mini is limited to 100,000 tokens.
Input capabilities
Documented input modalities across available providers
o4-mini supports multimodal inputs, whereas GPT OSS 120B High does not.
o4-mini can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT OSS 120B High
o4-mini
License
Usage and distribution terms
GPT OSS 120B High is licensed under Apache 2.0, while o4-mini uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
GPT OSS 120B High was released on 2025-08-05, while o4-mini was released on 2025-04-16.
GPT OSS 120B High is 4 months newer than o4-mini.
Aug 5, 2025
1.1 years ago
3mo newerApr 16, 2025
1.4 years ago
Knowledge Cutoff
When training data ends
o4-mini has a documented knowledge cutoff of 2024-05-31, while GPT OSS 120B High's cutoff date is not specified.
We can confirm o4-mini's training data extends to 2024-05-31, but cannot make a direct comparison without GPT OSS 120B High's cutoff date.
—
May 2024
Provider Availability
GPT OSS 120B High is available from OpenAI, Fireworks. o4-mini is available from OpenAI.
GPT OSS 120B High
o4-mini
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT OSS 120B High and o4-mini side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT OSS 120B High vs o4-mini.