Quick answer
“Claude” isn’t one model, so this comparison names the specific Claude option: Claude Opus 5.5, Anthropic’s Opus model. If lower listed API prices matter for your workload, GLM 5.2 is the less expensive option for uncached input and output tokens. Opus 5.5 is another candidate for complex coding and agent work, but the sources cited here do not establish that it outperforms GLM 5.2 on your tasks. Run the same workload through both before routing production traffic.
One update for readers choosing a model now: Z.ai identifies GLM 5.3 as its latest flagship. This article compares GLM 5.2 and Opus 5.5 as named; consider including GLM 5.3 in a new-model evaluation too. (Z.ai GLM-5.3 documentation)
Current-information scope: November 10, 2026. Model availability and prices can change.
GLM 5.2 vs Claude Opus 5.5 at a glance
| Decision point | GLM 5.2 | Claude Opus 5.5 |
|---|---|---|
| Provider | Z.ai |
Anthropic |
| API model ID | glm-5.2 |
claude-opus-5-5 |
| Listed input price | $1.40 per 1M tokens | $4 per 1M tokens |
| Listed output price | $4.40 per 1M tokens | $20 per 1M tokens |
| Cached-input / cache-read price | $0.26 per 1M tokens | $0.20 per 1M tokens for cache reads |
| Context and output | Z.ai lists 1M-token context and 128K maximum output |
Anthropic lists 1M-token context and 128K maximum output |
| Documented tool support | GLM 5.2 model page lists function calling and MCP | Anthropic documents tool use through the Messages API |
These are provider-listed USD rates per million tokens, not subscription fees. Z.ai lists GLM 5.2 at $1.40 input, $0.26 cached input, and $4.40 output; Anthropic lists Opus 5.5 at $4 input, $0.20 per million cache reads, and $20 output. The caching categories and terms are provider-specific, so confirm how your workload qualifies before comparing cached-token totals. (Z.ai API pricing; Anthropic Opus 5.5 model documentation)
The context and output limits are model specifications, not evidence that either model will work better on a large repository. Limits and features can also depend on the serving route. (Z.ai GLM-5.2 documentation; Anthropic Opus 5.5 model documentation)
Which model should you choose?
Start with GLM 5.2 if API token cost is a major factor
GLM 5.2 has lower listed uncached input and output prices than Opus 5.5. That can make it worth evaluating for high-volume text or coding tasks—provided its results meet your quality requirements. Z.ai describes GLM 5.2 as supporting function calls and context caching. (Z.ai GLM-5.2 documentation)
Lower token rates do not automatically mean lower production cost. A run that needs several retries or substantial human correction may cost more overall than a more expensive call that finishes reliably. Measure cost per accepted task, not just price per million tokens.
Evaluate Opus 5.5 for complex, open-ended agent work
Anthropic positions Opus 5.5 for long-running agentic coding and knowledge work. That makes it a candidate to evaluate where sustained execution or tool use matters. This is Anthropic’s product positioning—not a head-to-head finding that Opus 5.5 will outperform GLM 5.2 on your codebase. (Anthropic Opus 5.5 documentation)
Don’t treat “Claude” as a single comparison target
Opus 5.5 is the named Claude model used here. Anthropic offers other Claude models with different prices and capabilities. A comparison against another Claude model would be a different decision; don’t carry Opus-specific prices or conclusions across to another version. (Anthropic model overview)
API cost example: compare a real token mix
Suppose one completed task uses 10 million uncached input tokens and 1 million output tokens. Using the listed provider rates:
- GLM 5.2: (10 × $1.40) + (1 × $4.40) = $18.40
- Claude Opus 5.5: (10 × $4) + (1 × $20) = $60.00
On this hypothetical token mix, GLM 5.2’s listed API cost is $41.60 lower, before caching, retries, tools, taxes, or human review. This is arithmetic from listed rates, not a measured production result. Actual spend depends on token volume, cache eligibility, and how many attempts each model needs. (Z.ai API pricing; Anthropic Opus 5.5 model documentation)
A notable wrinkle: Opus 5.5’s listed cache-read rate is lower than GLM 5.2’s listed cached-input rate. Don’t assume GLM remains cheaper for every prompt mix; compare equivalent cache use and billing rules. (Z.ai API pricing; Anthropic Opus 5.5 model documentation)
Production API access and tool support
For a direct, provider-native API comparison, the documented routes are:
Z.ai GLM 5.2 |
Anthropic Claude Opus 5.5 | |
|---|---|---|
| Interface and endpoint | Chat Completions: POST https://api.z.ai/api/paas/v4/chat/completions |
Messages API: POST https://api.anthropic.com/v1/messages |
| Model ID | glm-5.2 |
claude-opus-5-5 |
| Authentication | Standard Z.ai API key in Authorization: Bearer … |
Claude Console API key; send the required API authentication and anthropic-version headers. Anthropic documents API-key authentication and the Messages endpoint. |
| Tool-using evaluation | Z.ai lists function calling for GLM 5.2; the chat-completion interface supports tool use. |
Anthropic documents tool use with Claude through Messages; the model returns tool calls for your application to handle. |
Z.ai’s general API endpoint is for its standard API product. Its documentation says GLM Coding Plan users should configure a dedicated endpoint instead, so don’t assume the standard endpoint applies to that plan. The GLM 5.2 model page lists glm-5.2 and function calling; Z.ai’s API reference documents the general chat-completions route and Bearer authentication. (Z.ai API introduction; Z.ai GLM-5.2 documentation; Z.ai Chat Completions reference)
Anthropic documents the native Messages API at /v1/messages, and its Opus 5.5 model page gives the API model ID claude-opus-5-5. Anthropic’s API overview describes Console API-key authentication, while its versioning documentation requires the anthropic-version request header for direct API requests. Anthropic’s tool-use documentation describes how an application supplies tools and handles returned tool calls. (Anthropic Messages API; Anthropic API overview; Anthropic API versioning; Anthropic tool-use documentation)
This identifies the documented routes and tool support, not a guarantee that every parameter, limit, or feature is identical between services. Before rollout, verify the exact model ID, authentication setup, rate limits, logging and data-retention terms, and regional availability for the route you will use. If you use a gateway or cloud platform rather than either provider’s native API, check that route’s own model ID, pricing, and feature support.
How to test GLM 5.2 and Opus 5.5 fairly
Run both against a small set of real tasks before choosing a default:
- Select representative work: for example, answer questions about a repository, fix a failing test without changing public behavior, or review a pull request for consequential defects.
- Keep conditions the same: use the same repository snapshot, prompt, tools, permissions, timeout, and success criteria. Record the exact model IDs and API routes.
- Score the finished task: check correctness, tests passed, missed issues, tool-call success and recovery, retries, latency, and human correction time.
- Calculate cost per accepted result: include input, output, and cached tokens, plus retries. Apply the same pass/fail criteria to both models.
- Route gradually: if one model does better on a particular task category, begin with a limited rollout for that category and keep a fallback for failed or high-value tasks.
This is a proposed evaluation, not a test performed for this article. The sources cited here do not provide a comparable, independently verified GLM 5.2-versus-Opus 5.5 result on a shared test set. Z.ai’s descriptions of GLM and Anthropic’s descriptions of Opus are provider claims, not a controlled comparison between these versions. (Z.ai GLM-5.2 documentation; Anthropic Opus 5.5 documentation)
Bottom line
Evaluate GLM 5.2 first when lower listed uncached-token rates matter and its output quality meets your requirements. Evaluate Claude Opus 5.5 for complex, long-running agent work where Anthropic’s documented API and tool-use support fit your integration. The evidence cited here does not establish a universal winner.
If you’re adopting a model now, don’t stop at this pair: Z.ai identifies GLM 5.3 as its latest flagship, so consider benchmarking it alongside GLM 5.2 and Opus 5.5 before setting a production default. (Z.ai GLM-5.3 documentation)
Sources
Z.AI API Reference: Introduction
Chat Completion — Z.AI Developer Documentation
GLM-5.2 — Z.AI Developer Documentation
Function Calling — Z.AI Developer Documentation
GLM-5.3 — Z.AI Developer Documentation
Claude Opus 5.5 — Claude Platform Docs
Messages — Claude API Reference
API overview — Claude Platform Docs