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OpenAI: gpt-oss-120b (exacto)

openai/gpt-oss-120b:exacto

Model weights
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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
$0.03 / $0.15per 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), or Floor (cheapest).

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 (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-AA5.4%
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 Elo898
Design ArenaGPT OSS 120B Models Arena Code Categories Elo961
Design ArenaGPT OSS 120B Models Arena Data Visualization Elo987
Design ArenaGPT OSS 120B Models Arena Game Development Elo992
Design ArenaGPT OSS 120B Models Arena UI Component Elo921
Design ArenaGPT OSS 120B Models Arena Website Elo966
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.

Available through EU in-region routing

OpenAI: gpt-oss-120b (exacto) is available through EU in-region routing. Requests sent to eu.dynamicsinfo.com are decrypted in the EU and routed only to shared provider endpoints in Europe (the EU/EEA, the UK, and Switzerland).

Providers in Europe
Amazon Bedrock
Prices in Europe
  • Amazon Bedrock: $0.15/M tokens input, $0.60/M tokens output
Base URL
https://eu.dynamicsinfo.com/api/v1
Plan
Requires Business or Enterprise. Self-serve on Business: no contract, no monthly minimum. OpenRouter Business for EU in-region routing

Fails closed: if no shared provider endpoint in Europe is available, the request errors instead of leaving the region. Requests served by your own BYOK key go to your deployment’s region, which you control. In-region routing docs

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Latency / throughput
ProviderInput /MOutput /MCache read /MLatencyThroughputUptime
$0.030$0.150$0.0150.62s45 tps
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$0.030$0.170$0.0300.29s56 tps
99.77%
$0.030$0.180$0.0300.58s38 tps
100.00%
$0.030$0.187$0.0301.04s56 tps
100.00%
$0.037$0.170--0.58s24 tps
99.60%
$0.050$0.250$0.0500.28s188 tps
99.07%
$0.050$0.250--0.64s60 tps
99.80%
$0.050$0.250--0.63s188 tps
98.61%
$0.060$0.400$0.0300.64s125 tps
100.00%
$0.060$0.420$0.0120.54s60 tps
100.00%
$0.100$0.500$0.1000.18s146 tps
99.97%
$0.100$0.500$0.1000.22s139 tps
99.94%
$0.100$0.750$0.0550.37s191 tps
99.97%
$0.140$0.950--0.65s197 tps
86.21%
$0.150$0.600--0.28s284 tps
99.29%
$0.150$0.600--0.40s383 tps
100.00%
$0.150$0.600$0.0751.12s49 tps
92.45%
$0.150$0.600--0.82s186 tps
98.08%
$0.150$0.600--0.23s78 tps
96.93%
$0.150$0.600$0.0750.31s274 tps
100.00%
$0.150$0.750--0.82s180 tps
98.87%
$0.350$0.750$0.3500.20s749 tps
100.00%
$0.090$0.360--0.57s33 tps
3.54%
Not used in Exacto routing:Why these endpoints are not used
$0.150$0.600--0.47s145 tps
100.00%
Throughput
749tok/s

P50, best across providers

Latency
0.18s

P50, best provider

AutoExacto benchmarks
GPQA DiamondTAU-BenchAmazon Bedrock77.2%--Amazon Bedrock (EU)76.9%--DekaLLM77.7%66.1%AkashML77.1%65.5%DeepInfra76.3%66.0%SambaNova76.9%65.3%DeepInfra65.9%67.2%
+18 more providers
Uptime (3d)The model was reachable. Request routed to a provider.
100.00%
Availability (3d)The model returned inference from any provider. Errors and empty responses count against it.
99.34%

Availability over the last 3 days

Last 72 hours
Availability 99.34%
3 Days Ago2 Days AgoYesterdayNow

Availability over the last 24 hours

OpenRouter Availability
99.26%
Without Routing
90.44%

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 provider routing options.

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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 costs $0.03/M input tokens and $0.15/M output tokens, with separate rates for Cache Read at $0.015/M tokens.

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

Yes. gpt-oss-120b accepts tools and tool_choice for function calling on 19 of the 23 providers serving it, and requests that send tools are routed to those providers. It also supports structured outputs via a JSON schema in response_format.

gpt-oss-120b is served by 23 providers on OpenRouter: NEAR AI, Venice, CoreWeave, DekaLLM, AkashML, DeepInfra, Crusoe, Mancer and 15 more. Requests are routed to the best available provider, with automatic failover to the others, and you can pin or exclude providers with provider routing.

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

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