Model Comparison

GPT OSS 20B vs o1-preview

o1-preview significantly outperforms across most benchmarks. GPT OSS 20B is 300.0x cheaper per token.

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Performance Benchmarks

Comparative analysis across standard metrics

2 benchmarks

GPT OSS 20B outperforms in 0 benchmarks, while o1-preview is better at 2 benchmarks (GPQA, MMLU).

o1-preview significantly outperforms across most benchmarks.

Mon Apr 13 2026 • llm-stats.com

Arena Performance

Human preference votes

Pricing Analysis

Price comparison per million tokens

GPT OSS 20B costs less

For input processing, GPT OSS 20B ($0.05/1M tokens) is 300.0x cheaper than o1-preview ($15.00/1M tokens).

For output processing, GPT OSS 20B ($0.20/1M tokens) is 300.0x cheaper than o1-preview ($60.00/1M tokens).

In conclusion, o1-preview is more expensive than GPT OSS 20B.*

* Using a 3:1 ratio of input to output tokens

Lowest available price from all providers
Mon Apr 13 2026 • llm-stats.com
OpenAI
GPT OSS 20B
Input tokens$0.05
Output tokens$0.20
Best providerNovita
OpenAI
o1-preview
Input tokens$15.00
Output tokens$60.00
Best providerOpenAI
Notice missing or incorrect data?Start an Issue→

Context Window

Maximum input and output token capacity

GPT OSS 20B accepts 131,072 input tokens compared to o1-preview's 128,000 tokens. Both models can generate responses up to 32,768 tokens.

OpenAI
GPT OSS 20B
Input131,072 tokens
Output32,768 tokens
OpenAI
o1-preview
Input128,000 tokens
Output32,768 tokens
Mon Apr 13 2026 • llm-stats.com

License

Usage and distribution terms

GPT OSS 20B is licensed under Apache 2.0, while o1-preview uses a proprietary license.

License differences may affect how you can use these models in commercial or open-source projects.

GPT OSS 20B

Apache 2.0

Open weights

o1-preview

Proprietary

Closed source

Release Timeline

When each model was launched

GPT OSS 20B was released on 2025-08-05, while o1-preview was released on 2024-09-12.

GPT OSS 20B is 11 months newer than o1-preview.

GPT OSS 20B

Aug 5, 2025

8 months ago

10mo newer
o1-preview

Sep 12, 2024

1.6 years ago

Knowledge Cutoff

When training data ends

Neither model specifies a knowledge cutoff date.

Unable to compare the recency of their training data.

No cutoff dates available

Provider Availability

GPT OSS 20B is available from Novita, Fireworks, Groq, OpenAI. o1-preview is available from OpenAI, Azure.

GPT OSS 20B

novita logo
Novita
Input Price:Input: $0.05/1MOutput Price:Output: $0.20/1M
fireworks logo
Fireworks
Input Price:Input: $0.10/1MOutput Price:Output: $0.50/1M
groq logo
Groq
Input Price:Input: $0.10/1MOutput Price:Output: $0.50/1M
openai logo
OpenAI
Input Price:Input: $0.10/1MOutput Price:Output: $0.50/1M

o1-preview

openai logo
OpenAI
Input Price:Input: $15.00/1MOutput Price:Output: $60.00/1M
azure logo
Azure
Input Price:Input: $16.50/1MOutput Price:Output: $66.00/1M
* Prices shown are per million tokens

Outputs Comparison

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Key Takeaways

OpenAI
Larger context window (131,072 tokens)
Less expensive input tokens
Less expensive output tokens
Has open weights
OpenAI
Higher GPQA score (73.3% vs 71.5%)
Higher MMLU score (90.8% vs 85.3%)

Detailed Comparison

AI Model Comparison Table
Feature
OpenAI
GPT OSS 20B
OpenAI
o1-preview

FAQ

Common questions about GPT OSS 20B vs o1-preview

o1-preview significantly outperforms across most benchmarks. GPT OSS 20B is made by OpenAI and o1-preview is made by OpenAI. The best choice depends on your use case — compare their benchmark scores, pricing, and capabilities above.
GPT OSS 20B scores MMLU: 85.3%, CodeForces: 74.3%, GPQA: 71.5%, TAU-bench Retail: 54.8%, HealthBench: 42.5%. o1-preview scores MGSM: 90.8%, MMLU: 90.8%, MATH: 85.5%, GPQA: 73.3%, LiveBench: 52.3%.
GPT OSS 20B is 300.0x cheaper for input tokens. GPT OSS 20B costs $0.05/M input and $0.20/M output via novita. o1-preview costs $15.00/M input and $60.00/M output via openai.
GPT OSS 20B supports 131K tokens and o1-preview supports 128K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.
Key differences include context window (131K vs 128K), input pricing ($0.05 vs $15.00/M), licensing (Apache 2.0 vs Proprietary). See the full comparison above for benchmark-by-benchmark results.