GLM-5.2 vs Mercury 3
GLM-5.2 leads the LLM Stats Score 45.0 to 36.1. Mercury 3 is 7.2x cheaper per token.
Zhipu AI · Inception · Updated for 2026
Which is better?
GLM-5.2 leads the overall LLM Stats Score 45.0 to 36.1, ranking #44 overall.
In the 1 individual benchmarks reported for both models, GLM-5.2 wins 1; this is a narrower head-to-head signal than the composite indexes.
On price, Mercury 3 is roughly 7.2x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
GLM-5.2 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 GLM-5.2
- overall performance matters — it scores 45.0 and ranks #44 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 need open weights you can self-host or fine-tune
Choose Mercury 3
- cost matters — it's about 7.2x cheaper per token
- you want the most recent training data — it shipped Oct 2026
At a glance
The differences that matter most.
Individual benchmarks
19 reported for GLM-5.2 · 12 for Mercury 3
GLM-5.2 outperforms in 1 benchmarks (GPQA), while Mercury 3 is better at 0 benchmarks.
GLM-5.2 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, GLM-5.2 ($0.75/1M tokens) is 7.5x more expensive than Mercury 3 ($0.10/1M tokens).
For output processing, GLM-5.2 ($2.40/1M tokens) is 6.9x more expensive than Mercury 3 ($0.35/1M tokens).
In conclusion, GLM-5.2 is more expensive than Mercury 3.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
GLM-5.2 accepts 1,048,576 input tokens compared to Mercury 3's 1,000,000 tokens. GLM-5.2 can generate longer responses up to 1,048,576 tokens, while Mercury 3 is limited to 131,072 tokens.
License
Usage and distribution terms
GLM-5.2 is licensed under MIT, while Mercury 3 uses a proprietary license.
License differences may affect how you can use these models in commercial or open-source projects.
MIT
Open weights
Proprietary
Closed source
Release Timeline
When each model was launched
GLM-5.2 was released on 2026-06-16, while Mercury 3 was released on 2026-10-19.
Mercury 3 is 4 months newer than GLM-5.2.
Jun 16, 2026
4 months ago
Oct 19, 2026
1 days ago
4mo newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
GLM-5.2 is available from DeepInfra, Fireworks, FriendliAI, Novita, Together, ZAI. Mercury 3 is available from Inception.
GLM-5.2
Mercury 3
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.2 and Mercury 3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.2 vs Mercury 3.