GPT-4 vs Mercury 3
Mercury 3 leads the LLM Stats Score 36.1 to 2.5. Mercury 3 is 230.8x cheaper per token.
OpenAI · Inception · Updated for 2026
Which is better?
Mercury 3 leads the overall LLM Stats Score 36.1 to 2.5, 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, Mercury 3 is roughly 230.8x 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-4
- you want predictable pricing at $30.00/M input and $60.00/M output
Choose Mercury 3
- overall performance matters — it scores 36.1 and ranks #98 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 1 of 1 exact shared results
- cost matters — it's about 230.8x cheaper per token
- 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
12 reported for GPT-4 · 12 for Mercury 3
GPT-4 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-4 ($30.00/1M tokens) is 300.0x more expensive than Mercury 3 ($0.10/1M tokens).
For output processing, GPT-4 ($60.00/1M tokens) is 171.4x more expensive than Mercury 3 ($0.35/1M tokens).
In conclusion, GPT-4 is more expensive than Mercury 3.*
* 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-4's 32,768 tokens. Mercury 3 can generate longer responses up to 131,072 tokens, while GPT-4 is limited to 32,768 tokens.
Input capabilities
Documented input modalities across available providers
GPT-4 supports multimodal inputs, whereas Mercury 3 does not.
GPT-4 can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-4
Mercury 3
License
Usage and distribution terms
Both models are licensed under proprietary licenses.
Both models have usage restrictions defined by their respective organizations.
Proprietary
Closed source
Proprietary
Closed source
Release Timeline
When each model was launched
GPT-4 was released on 2023-06-13, while Mercury 3 was released on 2026-10-19.
Mercury 3 is 41 months newer than GPT-4.
Jun 13, 2023
3.4 years ago
Oct 19, 2026
0 days ago
3.4yr newerKnowledge Cutoff
When training data ends
GPT-4 has a documented knowledge cutoff of 2022-12-31, while Mercury 3's cutoff date is not specified.
We can confirm GPT-4's training data extends to 2022-12-31, but cannot make a direct comparison without Mercury 3's cutoff date.
Dec 2022
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Provider Availability
GPT-4 is available from Azure, OpenAI. Mercury 3 is available from Inception.
GPT-4
Mercury 3
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-4 and Mercury 3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-4 vs Mercury 3.