Claude Opus 4.8 vs GLM-5.2
Claude Opus 4.8 leads the LLM Stats Score 50.8 to 45.6. GLM-5.2 is 8.6x cheaper per token.
Anthropic · Zhipu AI · Updated for 2026
Which is better?
Claude Opus 4.8 leads the overall LLM Stats Score 50.8 to 45.6, ranking #15 overall.
In the 8 individual benchmarks reported for both models, Claude Opus 4.8 wins 8; this is a narrower head-to-head signal than the composite indexes.
On price, GLM-5.2 is roughly 8.6x 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 Claude Opus 4.8
- overall performance matters — it scores 50.8 and ranks #15 on LLM Stats
- your work emphasizes coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 8 of 8 exact shared results
Choose GLM-5.2
- cost matters — it's about 8.6x 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
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
27 reported for Claude Opus 4.8 · 19 for GLM-5.2
Claude Opus 4.8 outperforms in 8 benchmarks (DeepSWE 1.1, FrontierCode 1.1, FrontierSWE, GPQA, Humanity's Last Exam, MCP Atlas, SWE-Bench Pro, Toolathlon), while GLM-5.2 is better at 0 benchmarks.
Claude Opus 4.8 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, Claude Opus 4.8 ($5.00/1M tokens) is 6.7x more expensive than GLM-5.2 ($0.75/1M tokens).
For output processing, Claude Opus 4.8 ($25.00/1M tokens) is 10.4x more expensive than GLM-5.2 ($2.40/1M tokens).
In conclusion, Claude Opus 4.8 is more expensive than GLM-5.2.*
* 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 Claude Opus 4.8's 1,000,000 tokens. GLM-5.2 can generate longer responses up to 1,048,576 tokens, while Claude Opus 4.8 is limited to 128,000 tokens.
Input capabilities
Documented input modalities across available providers
Claude Opus 4.8 supports multimodal inputs, whereas GLM-5.2 does not.
Claude Opus 4.8 can handle both text and other forms of data like images, making it suitable for multimodal applications.
Claude Opus 4.8
GLM-5.2
License
Usage and distribution terms
Claude Opus 4.8 is licensed under a proprietary license, while GLM-5.2 uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
MIT
Open weights
Release Timeline
When each model was launched
Claude Opus 4.8 was released on 2026-05-28, while GLM-5.2 was released on 2026-06-16.
GLM-5.2 is 1 month newer than Claude Opus 4.8.
May 28, 2026
3 months ago
Jun 16, 2026
3 months ago
2w newerKnowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Provider Availability
Claude Opus 4.8 is available from Anthropic, DeepInfra, Vertex AI. GLM-5.2 is available from DeepInfra, Fireworks, FriendliAI, Novita, Together, ZAI.
Claude Opus 4.8
GLM-5.2
Outputs Comparison
Judge for yourself.
Run your own prompts against Claude Opus 4.8 and GLM-5.2 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Claude Opus 4.8 vs GLM-5.2.