GPT-5.6 Terra vs Mercury 3
GPT-5.6 Terra leads the LLM Stats Score 49.3 to 36.1. Mercury 3 is 27.7x cheaper per token.
OpenAI · Inception · Updated for 2026
Which is better?
GPT-5.6 Terra leads the overall LLM Stats Score 49.3 to 36.1, ranking #25 overall.
In the 1 individual benchmarks reported for both models, GPT-5.6 Terra wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Mercury 3 is roughly 27.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GPT-5.6 Terra also accepts a larger context window (1,050,000 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-5.6 Terra
- overall performance matters — it scores 49.3 and ranks #25 on LLM Stats
- your work emphasizes reasoning and agents — 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 1,050,000 token context window
Choose Mercury 3
- cost matters — it's about 27.7x cheaper per token
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
45 reported for GPT-5.6 Terra · 12 for Mercury 3
GPT-5.6 Terra outperforms in 1 benchmarks (GPQA), while Mercury 3 is better at 0 benchmarks.
GPT-5.6 Terra 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-5.6 Terra ($2.00/1M tokens) is 20.0x more expensive than Mercury 3 ($0.10/1M tokens).
For output processing, GPT-5.6 Terra ($12.00/1M tokens) is 34.3x more expensive than Mercury 3 ($0.35/1M tokens).
In conclusion, GPT-5.6 Terra is more expensive than Mercury 3.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GPT-5.6 Terra accepts 1,050,000 input tokens compared to Mercury 3's 1,000,000 tokens. Mercury 3 can generate longer responses up to 131,072 tokens, while GPT-5.6 Terra is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
GPT-5.6 Terra supports multimodal inputs, whereas Mercury 3 does not.
GPT-5.6 Terra can handle both text and other forms of data like images, making it suitable for multimodal applications.
GPT-5.6 Terra
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-5.6 Terra was released on 2026-07-09, while Mercury 3 was released on 2026-10-19.
Mercury 3 is 3 months newer than GPT-5.6 Terra.
Jul 9, 2026
3 months ago
Oct 19, 2026
0 days ago
3mo newerKnowledge Cutoff
When training data ends
GPT-5.6 Terra has a documented knowledge cutoff of 2026-02-16, while Mercury 3's cutoff date is not specified.
We can confirm GPT-5.6 Terra's training data extends to 2026-02-16, but cannot make a direct comparison without Mercury 3's cutoff date.
Feb 2026
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Provider Availability
GPT-5.6 Terra is available from OpenAI. Mercury 3 is available from Inception.
GPT-5.6 Terra
Mercury 3
Outputs Comparison
Judge for yourself.
Run your own prompts against GPT-5.6 Terra and Mercury 3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GPT-5.6 Terra vs Mercury 3.