GLM-5.2 vs Solar Pro 4
GLM-5.2 leads the LLM Stats Score 46.5 to 36.0. Solar Pro 4 is 2.8x cheaper per token.
Zhipu AI · Upstage · Updated for 2026
Which is better?
GLM-5.2 leads the overall LLM Stats Score 46.5 to 36.0, ranking #22 overall.
In the 3 individual benchmarks reported for both models, GLM-5.2 wins 3; this is a narrower head-to-head signal than the composite indexes.
On price, Solar Pro 4 is roughly 2.8x 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 46.5 and ranks #22 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 3 of 3 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 Solar Pro 4
- cost matters — it's about 2.8x cheaper per token
- you want the most recent training data — it shipped Aug 2026
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
19 reported for GLM-5.2 · 9 for Solar Pro 4
GLM-5.2 outperforms in 3 benchmarks (AIME 2026, GPQA, Terminal-Bench 2.1), while Solar Pro 4 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 ($0.95/1M tokens) is 3.2x more expensive than Solar Pro 4 ($0.30/1M tokens).
For output processing, GLM-5.2 ($3.00/1M tokens) is 2.5x more expensive than Solar Pro 4 ($1.20/1M tokens).
In conclusion, GLM-5.2 is more expensive than Solar Pro 4.*
* 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 Solar Pro 4's 524,288 tokens. Both models can generate responses up to 131,072 tokens.
License
Usage and distribution terms
GLM-5.2 is licensed under MIT, while Solar Pro 4 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 Solar Pro 4 was released on 2026-08-06.
Solar Pro 4 is 2 months newer than GLM-5.2.
Jun 16, 2026
2 months ago
Aug 6, 2026
3 weeks ago
1mo 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. Solar Pro 4 is available from Upstage.
GLM-5.2
Solar Pro 4
Outputs Comparison
Judge for yourself.
Run your own prompts against GLM-5.2 and Solar Pro 4 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.2 vs Solar Pro 4.