The AI arena is free today

Open Superagent

GPT-6 Luna vs GPT OSS 120B

GPT-6 Luna leads the LLM Stats Score 44.5 to 28.7. GPT OSS 120B is 2.8x cheaper per token.

OpenAI · OpenAI · Updated for 2026

Which is better?

GPT-6 Luna leads the overall LLM Stats Score 44.5 to 28.7, ranking #41 overall.

On price, GPT OSS 120B is roughly 2.8x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.

GPT-6 Luna also accepts a larger context window (1,050,000 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-6 Luna

  • overall performance matters — it scores 44.5 and ranks #41 on LLM Stats
  • your work emphasizes reasoning — it leads those capability indexes
  • you process long inputs — it offers a 1,050,000 token context window
  • you want the most recent training data — it shipped Sep 2026

Choose GPT OSS 120B

  • cost matters — it's about 2.8x cheaper per token
  • you need open weights you can self-host or fine-tune

At a glance

The differences that matter most.

Core performance indexes
44.5
#41
28.7
#138
40.0
#58
23.0
#172
Cost, coverage & limits
Benchmark wins
Input price
$0.10 / M
$0.04 / M
Output price
$0.50 / M
$0.17 / M
Context window
1,050,000
131,072

Individual benchmarks

5 reported for GPT-6 Luna · 7 for GPT OSS 120B

No common benchmarks found

GPT-6 Luna and GPT OSS 120Bdon't have any common benchmark datasets to compare. They may have been evaluated on different testing suites.

Human preference

Blind head-to-head votes and playground preference scores

Pricing Analysis

Price comparison per million tokens

GPT OSS 120B costs less

For input processing, GPT-6 Luna ($0.10/1M tokens) is 2.7x more expensive than GPT OSS 120B ($0.04/1M tokens).

For output processing, GPT-6 Luna ($0.50/1M tokens) is 2.9x more expensive than GPT OSS 120B ($0.17/1M tokens).

In conclusion, GPT-6 Luna is more expensive than GPT OSS 120B.*

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

Lowest available price from all providers
Tue Sep 22 2026 • llm-stats.com
OpenAI
GPT-6 Luna
Input tokens$0.10
Output tokens$0.50
Best providerOpenAI
OpenAI
GPT OSS 120B
Input tokens$0.04
Output tokens$0.17
Best providerDeepinfra
Notice missing or incorrect data?Start an Issue

Context Window

Maximum input and output token capacity

GPT-6 Luna accepts 1,050,000 input tokens compared to GPT OSS 120B's 131,072 tokens. GPT OSS 120B can generate longer responses up to 131,072 tokens, while GPT-6 Luna is limited to 128,000 tokens.

OpenAI
GPT-6 Luna
Input1,050,000 tokens
Output128,000 tokens
OpenAI
GPT OSS 120B
Input131,072 tokens
Output131,072 tokens
Tue Sep 22 2026 • llm-stats.com

Input capabilities

Documented input modalities across available providers

GPT-6 Luna supports multimodal inputs, whereas GPT OSS 120B does not.

GPT-6 Luna can handle both text and other forms of data like images, making it suitable for multimodal applications.

GPT-6 Luna

Text
Images
Audio
Video

GPT OSS 120B

Text
Images
Audio
Video

License

Usage and distribution terms

GPT-6 Luna is licensed under a proprietary license, while GPT OSS 120B uses Apache 2.0.

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

GPT-6 Luna

Proprietary

Closed source

GPT OSS 120B

Apache 2.0

Open weights

Release Timeline

When each model was launched

GPT-6 Luna was released on 2026-09-22, while GPT OSS 120B was released on 2025-08-05.

GPT-6 Luna is 14 months newer than GPT OSS 120B.

GPT-6 Luna

Sep 22, 2026

0 days ago

1.1yr newer
GPT OSS 120B

Aug 5, 2025

1.1 years ago

Knowledge Cutoff

When training data ends

GPT-6 Luna has a documented knowledge cutoff of 2026-05-18, while GPT OSS 120B's cutoff date is not specified.

We can confirm GPT-6 Luna's training data extends to 2026-05-18, but cannot make a direct comparison without GPT OSS 120B's cutoff date.

GPT-6 Luna

May 2026

GPT OSS 120B

Provider Availability

GPT-6 Luna is available from OpenAI. GPT OSS 120B is available from DeepInfra, Novita, OpenAI, Fireworks, Groq.

GPT-6 Luna

openai logo
OpenAI
Input Price:Input: $0.10/1MOutput Price:Output: $0.50/1M

GPT OSS 120B

deepinfra logo
Deepinfra
Input Price:Input: $0.04/1MOutput Price:Output: $0.17/1M
novita logo
Novita
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
fireworks logo
Fireworks
Input Price:Input: $0.15/1MOutput Price:Output: $0.60/1M
groq logo
Groq
Input Price:Input: $0.15/1MOutput Price:Output: $0.60/1M
* Prices shown are per million tokens

Outputs Comparison

Notice missing or incorrect data?Start an Issue discussion

Judge for yourself.

Run your own prompts against GPT-6 Luna and GPT OSS 120B side-by-side, then vote on the output you prefer.

GPT-6 Luna
✓ Preferred
GPT OSS 120B
Open in Playground

FAQ

Common questions about GPT-6 Luna vs GPT OSS 120B.

Which is better, GPT-6 Luna or GPT OSS 120B?

GPT-6 Luna leads the LLM Stats Score 44.5 to 28.7. GPT-6 Luna is made by OpenAI and GPT OSS 120B is made by OpenAI. The best choice depends on your use case — compare their capability indexes, individual benchmarks, pricing, and limits above.

How does GPT-6 Luna compare to GPT OSS 120B in benchmarks?

GPT-6 Luna scores DeepSWE 1.1: 66.6%, OSWorld 2.0: 52.7%, Agents' Last Exam: 50.9%, FrontierCode 1.1: 42.4%, AutomationBench v1.0.6: 20.7%. GPT OSS 120B scores MMLU: 90.0%, CodeForces: 82.1%, GPQA: 80.1%, TAU-bench Retail: 67.8%, HealthBench: 57.6%.

Is GPT-6 Luna cheaper than GPT OSS 120B?

GPT OSS 120B is 2.7x cheaper for input tokens. GPT-6 Luna costs $0.10/M input and $0.50/M output via openai. GPT OSS 120B costs $0.04/M input and $0.17/M output via deepinfra.

What are the context window sizes for GPT-6 Luna and GPT OSS 120B?

GPT-6 Luna supports 1.1M tokens and GPT OSS 120B supports 131K tokens. A larger context window lets you process longer documents, conversations, or codebases in a single request.

What are the main differences between GPT-6 Luna and GPT OSS 120B?

Key differences include LLM Stats Score (44.5 vs 28.7), context window (1.1M vs 131K), input pricing ($0.10 vs $0.04/M), multimodal support (yes vs no), licensing (Proprietary vs Apache 2.0). See the full comparison above for benchmark-by-benchmark results.