GPT OSS 120B vs Mercury 3
Mercury 3 leads the LLM Stats Score 36.1 to 28.1. GPT OSS 120B is 2.3x cheaper per token.
OpenAI · Inception · Updated for 2026
Which is better?
Mercury 3 leads the overall LLM Stats Score 36.1 to 28.1, ranking #98 overall.
In the 1 individual benchmarks reported for both models, Mercury 3 wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, GPT OSS 120B is roughly 2.3x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Mercury 3 also accepts a larger context window (1,000,000 input tokens), making it the stronger choice for long documents and large codebases.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose GPT OSS 120B
- cost matters — it's about 2.3x cheaper per token
- you need open weights you can self-host or fine-tune
Choose Mercury 3
- overall performance matters — it scores 36.1 and ranks #98 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- you process long inputs — it offers a 1,000,000 token context window
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Individual benchmarks
7 reported for GPT OSS 120B · 12 for Mercury 3
GPT OSS 120B outperforms in 0 benchmarks, while Mercury 3 is better at 1 benchmark (GPQA).
Mercury 3 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Pricing Analysis
Price comparison per million tokens
For input processing, GPT OSS 120B ($0.04/1M tokens) is 2.7x cheaper than Mercury 3 ($0.10/1M tokens).
For output processing, GPT OSS 120B ($0.17/1M tokens) is 2.1x cheaper than Mercury 3 ($0.35/1M tokens).
In conclusion, Mercury 3 is more expensive than GPT OSS 120B.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Mercury 3 accepts 1,000,000 input tokens compared to GPT OSS 120B's 131,072 tokens. Both models can generate responses up to 131,072 tokens.
License
Usage and distribution terms
GPT OSS 120B is licensed under Apache 2.0, while Mercury 3 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
Apache 2.0
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
GPT OSS 120B was released on 2025-08-05, while Mercury 3 was released on 2026-10-19.
Mercury 3 is 15 months newer than GPT OSS 120B.
Aug 5, 2025
1.2 years ago
Oct 19, 2026
1 days ago
1.2yr newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GPT OSS 120B is available from DeepInfra, Novita, OpenAI, Fireworks, Groq. Mercury 3 is available from Inception.
GPT OSS 120B
Mercury 3
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT OSS 120B and Mercury 3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT OSS 120B vs Mercury 3.