DeepSeek-R1-0528 vs GPT OSS 120B High
DeepSeek-R1-0528 and GPT OSS 120B High are closely matched at 24.1 and 25.4 on the LLM Stats Score. GPT OSS 120B High is 4.6x cheaper per token.
DeepSeek · OpenAI · Updated for 2026
Which is better?
DeepSeek-R1-0528 and GPT OSS 120B High are closely matched on the overall LLM Stats Score at 24.1 and 25.4.
In the 3 individual benchmarks reported for both models, DeepSeek-R1-0528 wins 2; this is a narrower head-to-head signal than the composite indexes.
On price, GPT OSS 120B High is roughly 4.6x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
DeepSeek-R1-0528 also accepts a larger context window (163,840 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 DeepSeek-R1-0528
- you value its reported benchmark strengths — it wins 2 of 3 exact shared results
- you process long inputs — it offers a 163,840 token context window
Choose GPT OSS 120B High
- cost matters — it's about 4.6x cheaper per token
- you want the most recent training data — it shipped Aug 2025
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
16 reported for DeepSeek-R1-0528 · 7 for GPT OSS 120B High
DeepSeek-R1-0528 outperforms in 2 benchmarks (GPQA, MMLU-Pro), while GPT OSS 120B High is better at 1 benchmark (AIME 2025).
DeepSeek-R1-0528 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, DeepSeek-R1-0528 ($0.50/1M tokens) is 5.0x more expensive than GPT OSS 120B High ($0.10/1M tokens).
For output processing, DeepSeek-R1-0528 ($2.15/1M tokens) is 4.3x more expensive than GPT OSS 120B High ($0.50/1M tokens).
In conclusion, DeepSeek-R1-0528 is more expensive than GPT OSS 120B High.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
DeepSeek-R1-0528 has 554.2B more parameters than GPT OSS 120B High, making it 474.5% larger.
Context Window
Maximum input and output token capacity
DeepSeek-R1-0528 accepts 163,840 input tokens compared to GPT OSS 120B High's 131,072 tokens. DeepSeek-R1-0528 can generate longer responses up to 163,840 tokens, while GPT OSS 120B High is limited to 131,072 tokens.
License
Usage and distribution terms
DeepSeek-R1-0528 is licensed under MIT, while GPT OSS 120B High uses Apache 2.0.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Apache 2.0
Open weights
Release Timeline
When each model was launched
DeepSeek-R1-0528 was released on 2025-05-28, while GPT OSS 120B High was released on 2025-08-05.
GPT OSS 120B High is 2 months newer than DeepSeek-R1-0528.
May 28, 2025
1.3 years ago
Aug 5, 2025
1.1 years ago
2mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
DeepSeek-R1-0528 is available from DeepInfra, DeepSeek, Novita. GPT OSS 120B High is available from OpenAI, Fireworks.
DeepSeek-R1-0528
GPT OSS 120B High
Outputs Comparison
Judge for yourself.
Run your own prompts against DeepSeek-R1-0528 and GPT OSS 120B High side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-R1-0528 vs GPT OSS 120B High.