Model Comparison
GLM-5.2 vs GLM-5.1Which is better in 2026?
GLM-5.2 significantly outperforms across most benchmarks. GLM-5.2 is 1.5x cheaper per token.
Verdict: GLM-5.2 vs GLM-5.1 — which is better?
GLM-5.2 (by Zhipu AI) and GLM-5.1 (by Zhipu AI) are two of the AI models people compare most. Here is how they stack up on benchmarks, price and capabilities, and which one to pick in 2026.
GLM-5.2 outperforms in 11 benchmarks (AIME 2026, FrontierSWE, GPQA, HMMT 2025, HMMT Feb 26, Humanity's Last Exam, IMO-AnswerBench, MCP Atlas, NL2Repo, SWE-Bench Pro, Toolathlon), while GLM-5.1 is better at 0 benchmarks. GLM-5.2 significantly outperforms across most benchmarks.
On price, GLM-5.2 is roughly 1.5x 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.
Choose GLM-5.2 if…
- you want the strongest raw capability — it leads on 11 of 11 shared benchmarks
- cost matters — it's about 1.5x cheaper per token
- you process long inputs — it offers a 1,048,576 token context window
- you want the most recent training data — it shipped Jun 2026
Choose GLM-5.1 if…
- you want predictable pricing at $1.40/M input and $4.40/M output
Performance Benchmarks
Comparative analysis across standard metrics
GLM-5.2 outperforms in 11 benchmarks (AIME 2026, FrontierSWE, GPQA, HMMT 2025, HMMT Feb 26, Humanity's Last Exam, IMO-AnswerBench, MCP Atlas, NL2Repo, SWE-Bench Pro, Toolathlon), while GLM-5.1 is better at 0 benchmarks.
GLM-5.2 significantly outperforms across most benchmarks.
Arena Performance
Human preference votes
Pricing Analysis
Price comparison per million tokens
For input processing, GLM-5.2 ($0.95/1M tokens) is 1.5x cheaper than GLM-5.1 ($1.40/1M tokens).
For output processing, GLM-5.2 ($3.00/1M tokens) is 1.5x cheaper than GLM-5.1 ($4.40/1M tokens).
In conclusion, GLM-5.1 is more expensive than GLM-5.2.*
* Using a 3:1 ratio of input to output tokens
Model Size
Parameter count comparison
GLM-5.1 has 1.0B more parameters than GLM-5.2, making it 0.1% larger.
Context Window
Maximum input and output token capacity
GLM-5.2 accepts 1,048,576 input tokens compared to GLM-5.1's 200,000 tokens. GLM-5.2 can generate longer responses up to 131,072 tokens, while GLM-5.1 is limited to 128,000 tokens.
License
Usage and distribution terms
Both models are licensed under MIT.
Both models share the same licensing terms, providing consistent usage rights.
MIT
Open weights
MIT
Open weights
Release Timeline
When each model was launched
GLM-5.2 was released on 2026-06-16, while GLM-5.1 was released on 2026-04-07.
GLM-5.2 is 2 months newer than GLM-5.1.
Jun 16, 2026
1 months ago
2mo newerApr 7, 2026
3 months ago
Knowledge 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. GLM-5.1 is available from FriendliAI, ZAI.
GLM-5.2
GLM-5.1
Outputs Comparison
Key Takeaways
GLM-5.2
View detailsZhipu AI
GLM-5.1
View detailsZhipu AI
No standout differentiators in the data we have for this pair.
Detailed Comparison
Interactive Arena
Judge for yourself.
Run your own prompts against GLM-5.2 and GLM-5.1 side-by-side, then vote on the output you prefer.
FAQ
Common questions about GLM-5.2 vs GLM-5.1.