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OpenAI: gpt-oss-120b (batch)

openai/gpt-oss-120b:batch

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gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI 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.

Modalities
In / Out Price
$0.0296 / $0.136per 1M
Context
131K
Released
Aug 5, 2025
Knowledge Cutoff
Jun 2024
Compare
ProvidersPricingPerformanceUptimeBenchmarksAppsActivityFAQExplore

Providers

Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick — Balanced (price + speed), Nitro (fastest), Floor (cheapest), or Exacto (highest tool-calling accuracy).

Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Performance

Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Benchmarks

Scores on standardized evaluations and this model’s own outputs on shared benchmark prompts. Higher percentages are better — and each rank shows where this model lands among the models evaluated on that source.

Benchmark score summary for OpenAI: gpt-oss-120b (batch) (Artificial Analysis, Design Arena and Vals AI)
SourceBenchmarkScore
Artificial Analysisgpt-oss-120b (High) Intelligence Index11.6
Artificial Analysisgpt-oss-120b (High) Coding Index30.4
Artificial Analysisgpt-oss-120b (High) Math Index93.4
Artificial Analysisgpt-oss-120b (High) Agentic Index3.7
Artificial Analysisgpt-oss-120b (High) GPQA Diamond78.2%
Artificial Analysisgpt-oss-120b (High) HLE19.6%
Artificial Analysisgpt-oss-120b (High) IFBench69.0%
Artificial Analysisgpt-oss-120b (High) τ²-Bench Telecom65.8%
Artificial Analysisgpt-oss-120b (High) AA-LCR52.0%
Artificial Analysisgpt-oss-120b (High) τ-Bench Banking12.8%
Artificial Analysisgpt-oss-120b (High) GDPval-AA5.6%
Artificial Analysisgpt-oss-120b (High) CritPt1.1%
Artificial Analysisgpt-oss-120b (High) LiveCodeBench87.8%
Artificial Analysisgpt-oss-120b (High) SciCode34.0%
Artificial Analysisgpt-oss-120b (High) Terminal-Bench Hard23.5%
Artificial Analysisgpt-oss-120b (High) Terminal-Bench 4.00.0%
Artificial Analysisgpt-oss-120b (High) Terminal-Bench 2.126.2%
Artificial Analysisgpt-oss-120b (High) MMLU-Pro80.8%
Artificial Analysisgpt-oss-120b (High) AA-Omniscience Accuracy21.8%
Artificial Analysisgpt-oss-120b (High) AA-Omniscience Non-Hallucination Rate9.2%
Artificial Analysisgpt-oss-120b (High) AIME 202593.4%
Artificial Analysisgpt-oss-120b (Low) Intelligence Index10.2
Artificial Analysisgpt-oss-120b (Low) Coding Index21.2
Artificial Analysisgpt-oss-120b (Low) Math Index66.7
Artificial Analysisgpt-oss-120b (Low) GPQA Diamond67.2%
Artificial Analysisgpt-oss-120b (Low) HLE5.9%
Artificial Analysisgpt-oss-120b (Low) IFBench58.3%
Artificial Analysisgpt-oss-120b (Low) τ²-Bench Telecom45.0%
Artificial Analysisgpt-oss-120b (Low) AA-LCR46.0%
Artificial Analysisgpt-oss-120b (Low) τ-Bench Banking2.9%
Artificial Analysisgpt-oss-120b (Low) GDPval-AA0.0%
Artificial Analysisgpt-oss-120b (Low) CritPt0.0%
Artificial Analysisgpt-oss-120b (Low) LiveCodeBench70.7%
Artificial Analysisgpt-oss-120b (Low) Terminal-Bench Hard5.3%
Artificial Analysisgpt-oss-120b (Low) Terminal-Bench 2.113.9%
Artificial Analysisgpt-oss-120b (Low) MMLU-Pro77.5%
Artificial Analysisgpt-oss-120b (Low) AA-Omniscience Accuracy19.8%
Artificial Analysisgpt-oss-120b (Low) AA-Omniscience Non-Hallucination Rate8.6%
Artificial Analysisgpt-oss-120b (Low) AIME 202566.7%
Design ArenaGPT OSS 120B Models Arena 3D Elo916
Design ArenaGPT OSS 120B Models Arena Code Categories Elo969
Design ArenaGPT OSS 120B Models Arena Data Visualization Elo995
Design ArenaGPT OSS 120B Models Arena Game Development Elo1005
Design ArenaGPT OSS 120B Models Arena UI Component Elo934
Design ArenaGPT OSS 120B Models Arena Website Elo974
Vals AIGPT OSS 120B AIME92.6%
Vals AIGPT OSS 120B CaseLaw v248.8%
Vals AIGPT OSS 120B CorpFin v258.2%
Vals AIGPT OSS 120B Finance Agent v1.121.5%
Vals AIGPT OSS 120B GPQA Diamond78.5%
Vals AIGPT OSS 120B LiveCodeBench83.2%
Vals AIGPT OSS 120B LegalBench75.9%
Vals AIGPT OSS 120B MATH 50094.8%
Vals AIGPT OSS 120B MedQA91.4%
Vals AIGPT OSS 120B MGSM92.0%
Vals AIGPT OSS 120B MMLU Pro79.2%
Vals AIGPT OSS 120B SWE-bench33.6%
Vals AIGPT OSS 120B TaxEval v271.6%
Vals AIGPT OSS 120B Terminal-Bench 2.019.1%

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

Activity

Token volume and request traffic to this model over time.

API

Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.

Explore more models

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$0.0296$0.136----
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GPQA DiamondTAU-BenchBaseten79.1%--Baseten77.9%--CoreWeave77.8%--Amazon Bedrock77.4%--Amazon Bedrock75.8%--Mara74.1%--Novita73.7%--
+16 more providers

Not enough uptime data to display yet.

When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and customization options.

Not enough data for apps using this model yet.

Frequently asked questions

gpt-oss-120b is an open-weight, 117B-parameter Mixture-of-Experts (MoE) language model from OpenAI 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.

gpt-oss-120b (batch) costs $0.0296/M input tokens and $0.136/M output tokens.

gpt-oss-120b (batch) has a 131,072 token context window. It supports up to 131,072 completion tokens.

Yes. gpt-oss-120b (batch) accepts tools and tool_choice for function calling. It also supports structured outputs via a JSON schema in response_format.

GPT-6.1 Sol Pro, GPT-6.1 Sol, GPT-6 Luna Pro and 61 more are other text models from OpenAI.

gpt-oss-120b (batch) was released on August 5, 2025. Its knowledge cutoff is June 30, 2024.

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GPT-6.1 Sol Pro is the same underlying model as GPT-6.1 Sol, served with reasoning.mode set to pro for higher-quality responses on complex tasks.

Cost note: pro mode spends far more reasoning tokens per request, so a typical request costs several times more than the same request on GPT-6.1 Sol and takes much longer to complete. It is intended for hard, high-stakes problems where the extra accuracy justifies the cost. For everyday coding, agentic, and chat workloads, use GPT-6.1 Sol instead.

Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode

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GPT-6.1 Sol is an upgrade to GPT-6 Sol from OpenAI, positioned below the flagship GPT-6 Astra in the GPT-6 series. It is suited for agentic coding, computer use, document-heavy professional work, and multi-step business workflow automation, and approaches Astra-level results on these tasks at a much lower cost. Compared with GPT-6 Sol, it makes fewer factual errors and is more reliable at respecting explicit restrictions and user intent during agentic tasks.

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GPT-6 Luna Pro

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Cost note: pro mode spends far more reasoning tokens per request, so a typical request costs several times more than the same request on GPT-6 Luna and takes much longer to complete. It is intended for hard, high-stakes problems where the extra accuracy justifies the cost. For everyday coding, agentic, and chat workloads, use GPT-6 Luna instead.

Learn more in OpenAI's docs: https://developers.openai.com/api/docs/guides/reasoning#reasoning-mode

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GPT-6 Luna Pro

GPT-6 Luna Pro is the same underlying model as GPT-6 Luna, served with reasoning.mode set to pro for higher-quality responses on complex tasks.

Cost note: pro mode spends far more reasoning tokens per request, so a typical request costs several times more than the same request on GPT-6 Luna and takes much longer to complete. It is intended for hard, high-stakes problems where the extra accuracy justifies the cost. For everyday coding, agentic, and chat workloads, use GPT-6 Luna instead.

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