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GPT OSS 120B

Added Feb 3, 2026Open weights

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An open-weight, 117B-parameter Mixture-of-Experts (MoE) language model designed for high-reasoning, agentic, and general-purpose production use cases. It activates 5.1B parameters per forward pass and is optimized to run on a single H100 GPU with native MXFP4 quantization. The model supports configurable reasoning depth, full chain-of-thought access, and native tool use, including function calling, browsing, and structured output generation.

  • Reasoning
  • Tools
  • Structured output
Input
Text
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.03
Output
$0.15
Cache read
$0.03

Reference prices as published by the model provider. API example

Specifications

Context window
128K
Max output
16.4K
Average output (7 days)
1.1K tokens
Longer than 74% of 468 models

Side by side

GPT OSS 120B compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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GPT OSS 120BOpenAIThis modelGPT 6 LunaOpenAIRemove
ProviderOpenAIOpenAI
Discovery tierOpen weightsEfficient
AddedFeb 3, 2026Sep 22, 2026
Limits
Context window128K1.05MBest
Max output16.38K128KBest
Average output1.1K tokens120 tokens
Pricing, USD per 1M tokens
Input$0.03Best$0.10
Output$0.15Best$0.50
Cache read$0.03$0.01Best
Cache write—$0.13
Performance
Throughput625.0 tok/sBest301.2 tok/s
Time to first token0.8 sBest4.1 s
Request success (24h)99.8%Best99.7%
Benchmark indexes
Intelligence Index11.629.9Best
Coding Index30.4—
Math Index93.4—
Capabilities
ReasoningYesYes
ToolsYesYes
VisionNoYes
Structured outputYesYes
PDF inputNoYes
Reasoning effort—none, low, medium, high, xhigh, max

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • GPT OSS 120B
  • GPT 6 Luna

Intelligence Index

  • GPT OSS 120B11.6
  • GPT 6 Luna29.9

GPT OSS 120B tested at high reasoning effort

GPT OSS 120B: Better than 25% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • GPT OSS 120B: 30.4
    • GPT 6 Luna: —

  • Math Index

    Composite of the math evaluations

    • GPT OSS 120B: 93.4
    • GPT 6 Luna: —

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • GPT OSS 120B: 0.2%
    • GPT 6 Luna: 40.5%Top

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • GPT OSS 120B: 0.0%
    • GPT 6 Luna: 10.2%Top

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • GPT OSS 120B: —
    • GPT 6 Luna: 1,097 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • GPT OSS 120B: 608 Elo
    • GPT 6 Luna: 1,263 EloTop

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • GPT OSS 120B: 4.0%
    • GPT 6 Luna: 13.8%Top

  • AA-LCRv1.1

    Reasoning across long documents

    • GPT OSS 120B: 52.0%
    • GPT 6 Luna: 78.3%Top

  • MLCR-AA

    Long-context reasoning over medical records

    • GPT OSS 120B: 1.7%
    • GPT 6 Luna: 18.3%Top

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • GPT OSS 120B: 19.6%
    • GPT 6 Luna: 28.3%Top

  • GPQA Diamond

    Graduate-level science questions

    • GPT OSS 120B: 78.2%
    • GPT 6 Luna: —

  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • GPT OSS 120B: 80.8%
    • GPT 6 Luna: —

  • IFBench

    Following precise output instructions

    • GPT OSS 120B: 69.0%
    • GPT 6 Luna: —

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • GPT OSS 120B: 0.0%
    • GPT 6 Luna: 2.5%Top

  • SciCode

    Scientific computing in Python

    • GPT OSS 120B: 34.0%
    • GPT 6 Luna: 50.9%Top

  • LiveCodeBench

    Recent competitive programming problems

    • GPT OSS 120B: 87.8%
    • GPT 6 Luna: —

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • GPT OSS 120B: 93.4%
    • GPT 6 Luna: —

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • GPT OSS 120B: 23.5%
    • GPT 6 Luna: —

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • GPT OSS 120B: 65.8%
    • GPT 6 Luna: —

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • GPT OSS 120B: 52.0%
    • GPT 6 Luna: 78.3%Top

Scores from Artificial Analysis, updated Oct 26, 2026. GPT OSS 120B was tested at high reasoning effort; compare scores measured at the same effort.Artificial Analysis

Live routing data

Performance and reliability

Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.

Throughput
625.0 tok/s
Faster than 98% of 263 models
Time to first token
0.8 s
Quicker than 98% of 263 models
Prompt cache hits
7.1%
About $0.03 per 1M input tokens with caching
Request success (24h)
99.8%
Reliable

Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.

Hourly request success · last 72 hoursLowest hour 79.3%
  • Healthy (98% or more)
  • Degraded (90–98%)
  • Down (under 90%)
  • No requests

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "openai/gpt-oss-120b",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="openai/gpt-oss-120b",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

OpenAI

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