Atlas / Models / OpenAI / OpenAI: gpt-oss-20b (batch)

OpenAI: gpt-oss-20b (batch)✓ Catalog verified

openai/gpt-oss-20b:batch

gpt-oss-20b is an open-weight 21B parameter model released by OpenAI under the Apache 2.0 license. It uses a Mixture-of-Experts (MoE) architecture with 3.6B active parameters per forward pass, optimized for...

Input price
$0.05 /1M
Output price
$0.20 /1M
Context
131K
Modalities
text
Released
Aug 5, 2025
Tool calling
Atlas signal
84/100
01

Overview

gpt-oss-20b is an open-weight 21B parameter model released by OpenAI under the Apache 2.0 license. It uses a Mixture-of-Experts (MoE) architecture with 3.6B active parameters per forward pass, optimized for...

Access: available through the official OpenAI API. Context window: 131K.

Pricing and metadata from the ModelsAtlas catalog.Last refreshed Sep 2, 2026
02

Specifications

API identifieropenai/gpt-oss-20b:batch
ProviderOpenAI
Model typeText LLM
Context window131K catalog
Input modalitiestext
Output modalitiestext
ReleasedAug 5, 2025
TokenizerGPT
ModeratedNo
Architecture modalitytext->text
Supported parameters
frequency_penaltyinclude_reasoninglogit_biasmax_tokensmin_ppresence_penaltyreasoningreasoning_effortrepetition_penaltyresponse_formatstopstructured_outputstemperaturetop_ktop_p
Source: provider documentation + catalog feedMethodology →

API defaults

Default parameters
{
  "top_p": null,
  "temperature": null,
  "frequency_penalty": null
}
03

Pricing

Live pricing components for openai/gpt-oss-20b:batch as published in the catalog.

$0.05
Input /1M
$0.20
Output /1M
Per request
Per image
Pricing componentRaw unit priceNormalizedUnit
Prompt tokens$5e-8$0.05 / 1MPer input token
Completion tokens$2e-7$0.20 / 1MPer output token
Request feeN/AN/APer request
Image feeN/AN/APer image unit
Web search feeN/AN/APer search request
Source: catalog pricing feedCompare all pricing →Cheapest models →
04

Cost calculator

Estimate monthly spend from your own token volumes.

Scale / Volume

Estimated Total Cost

$0.07Calculated from current list pricing in the ModelsAtlas catalog.
05

Capabilities

CapabilityStatusWhat it means
Visual UnderstandingNot advertisedImage and document analysis support
Audio ProcessingNot advertisedSpeech and voice aligned flows
Tool CallingNot advertisedSupports tools / function calling
Self-HostingNot advertisedDeploy outside managed APIs
Derived from catalog capability tags and supported parameters
06

Capability signals

Directional signals derived from model metadata and capability tags — not official benchmark submissions.

OpenAI: gpt-oss-20b (batch)
MMLU Signal (Reasoning)
91signal
Coding Signal (HumanEval proxy)
82signal
Math Signal (GSM8K proxy)
83signal
Science Signal (GPQA proxy)
79signal
Estimated from metadata — not an official benchmark runAll benchmarks →Methodology →
07

Quick start

Call OpenAI: gpt-oss-20b (batch) through an OpenAI-compatible client.

from openai import OpenAI

client = OpenAI(
    base_url="https://openrouter.ai/api/v1",
    api_key="YOUR_API_KEY"
)

response = client.chat.completions.create(
    model="openai/gpt-oss-20b:batch",
    messages=[{"role": "user", "content": "Explain quantum physics."}]
)

print(response.choices[0].message.content)
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Alternatives

Closest models by context window from a different provider.

09

Sources & attribution

Pricing and metadata are maintained in the ModelsAtlas catalog.

Capability bars use metadata tags — directional estimates onlyHow we source and verify data →
10

Frequently asked questions

How much does OpenAI: gpt-oss-20b (batch) cost?

$0.05 per 1M input tokens and $0.20 per 1M output tokens on the official OpenAI API.

What is the context window of OpenAI: gpt-oss-20b (batch)?

OpenAI: gpt-oss-20b (batch) supports up to 131K tokens of context.

Does OpenAI: gpt-oss-20b (batch) support tool / function calling?

OpenAI: gpt-oss-20b (batch) does not advertise first-class tool/function calling. Check vendor docs for the latest capabilities.

How do I access OpenAI: gpt-oss-20b (batch)?

Use the official OpenAI API with the model id `openai/gpt-oss-20b:batch`. See the Quick start section above for code examples.