Claude Opus 4.8 vs GLM-5.3
Claude Opus 4.8 and GLM-5.3 are closely matched at 51.1 and 53.6 on the LLM Stats Score. GLM-5.3 is 4.7x cheaper per token.
Anthropic · Zhipu AI · Updated for 2026
Which is better?
Claude Opus 4.8 and GLM-5.3 are closely matched on the overall LLM Stats Score at 51.1 and 53.6.
In the 6 individual benchmarks reported for both models, GLM-5.3 wins 6; this is a narrower head-to-head signal than the composite indexes.
On price, GLM-5.3 is roughly 4.7x cheaper per token on a blended 3:1 input/output basis, which adds up quickly at production volume.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose Claude Opus 4.8
- you want predictable pricing at $5.00/M input and $25.00/M output
Choose GLM-5.3
- you value its reported benchmark strengths — it wins 6 of 6 exact shared results
- cost matters — it's about 4.7x cheaper per token
- you want the most recent training data — it shipped Aug 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 · 17 for GLM-5.3
Claude Opus 4.8 outperforms in 0 benchmarks, while GLM-5.3 is better at 6 benchmarks (CyberGym, DeepSWE 1.1, FrontierSWE, Humanity's Last Exam, Terminal-Bench 4.0, Toolathlon).
GLM-5.3 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 3.6x more expensive than GLM-5.3 ($1.40/1M tokens).
For output processing, Claude Opus 4.8 ($25.00/1M tokens) is 5.7x more expensive than GLM-5.3 ($4.40/1M tokens).
In conclusion, Claude Opus 4.8 is more expensive than GLM-5.3.*
* Using a 3:1 ratio of input to output tokens
Context Window
Maximum input and output token capacity
Both models have the same input context window of 1,000,000 tokens. GLM-5.3 can generate longer responses up to 131,072 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-5.3 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-5.3
License
Usage and distribution terms
Claude Opus 4.8 is licensed under a proprietary license, while GLM-5.3 uses GLM-5.3 License.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
GLM-5.3 License
Open weights
Release Timeline
When each model was launched
Claude Opus 4.8 was released on 2026-05-28, while GLM-5.3 was released on 2026-08-14.
GLM-5.3 is 3 months newer than Claude Opus 4.8.
May 28, 2026
3 months ago
Aug 14, 2026
3 weeks ago
2mo 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, Vertex AI. GLM-5.3 is available from FriendliAI, Novita, ZAI.
Claude Opus 4.8
GLM-5.3
Outputs Comparison
Judge for yourself.
Run your own prompts against Claude Opus 4.8 and GLM-5.3 side-by-side, then vote on the output you prefer.
FAQ
Common questions about Claude Opus 4.8 vs GLM-5.3.