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gpt-oss-120b vs Mistral Nemo

How do these models stack up? Below is an expert side-by-side comparison of specifications, context window capacity, live pricing per million tokens, and standardized benchmark scores for gpt-oss-120b and Mistral Nemo.

OpenAI

gpt-oss-120b

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...

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Mistral

Mistral Nemo

A 12B parameter model with a 128k token context length built by Mistral in collaboration with NVIDIA. The model is multilingual, supporting English, French, German, Spanish, Italian, Portuguese, Chinese, Japanese,...

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Technical Specifications

Specificationgpt-oss-120bMistral Nemo
ProviderOpenAIMistral
Context Window131,072 tokens131,072 tokens
Agent SuitabilityN/AN/A
Time to First Token (TTFT)N/AN/A
Deployment Modelmanaged apiself hostable
Production Stabilitystablestable
API AvailableYesYes
Released Date2025-08-052024-07-19

API Pricing Comparison

Input Price per Million Tokens

gpt-oss-120b

$0.03

Mistral Nemo

$0.02

Output Price per Million Tokens

gpt-oss-120b

$0.15

Mistral Nemo

$0.03

Want to test both models live?

Run side-by-side prompt prompts in our dynamic Sandbox. Check execution speeds, latency metrics, and compute actual costs in real-time.

Benchmark Performance Metrics

Scores show the raw performance percentages verified across key evaluation suites. Higher bars indicate superior accuracy and capability in that domain.

gpt-oss-120b Quirks & Gotchas

No developer gotchas reported.

Mistral Nemo Quirks & Gotchas

No developer gotchas reported.