Mercury 2 vs Particle-1
Particle-1 leads the LLM Stats Score 31.9 to 23.2. Mercury 2 is 1.2x cheaper per token.
Inception · Particle AI · Updated for 2026
Which is better?
Particle-1 leads the overall LLM Stats Score 31.9 to 23.2, ranking #133 overall.
In the 1 individual benchmarks reported for both models, Particle-1 wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Mercury 2 is roughly 1.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Particle-1 also accepts a larger context window (1,048,576 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 Mercury 2
- cost matters — it's about 1.2x cheaper per token
Choose Particle-1
- overall performance matters — it scores 31.9 and ranks #133 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 1,048,576 token context window
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Individual benchmarks
6 reported for Mercury 2 · 3 for Particle-1
Mercury 2 outperforms in 0 benchmarks, while Particle-1 is better at 1 benchmark (GPQA).
Particle-1 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, Mercury 2 ($0.25/1M tokens) costs the same as Particle-1 ($0.25/1M tokens).
For output processing, Mercury 2 ($0.75/1M tokens) is 1.3x cheaper than Particle-1 ($1.00/1M tokens).
In conclusion, Particle-1 is more expensive than Mercury 2.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Particle-1 accepts 1,048,576 input tokens compared to Mercury 2's 128,000 tokens. Particle-1 can generate longer responses up to 131,072 tokens, while Mercury 2 is limited to 8,192 tokens.
Input capabilities
Documented input modalities across available providers
Particle-1 supports multimodal inputs, whereas Mercury 2 does not.
Particle-1 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Mercury 2
Particle-1
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
Mercury 2 was released on 2026-02-24, while Particle-1 was released on 2026-10-28.
Particle-1 is 8 months newer than Mercury 2.
Feb 24, 2026
8 months ago
Oct 28, 2026
-3 days ago
8mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Mercury 2 is available from Inception. Particle-1 is available from Particle AI.
Mercury 2
Particle-1
Outputs Comparison
Judge for yourself.
Run your own prompts against Mercury 2 and Particle-1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Mercury 2 vs Particle-1.