How does glm-5v-turbo score on benchmarks?

Recorded results for glm-5v-turbo: aa_intelligence_index 37.5; arena_text 86.5. Benchmark positions are a coarse filter only — run your own prompts against the candidate models before you commit, because ranking shifts with task shape and prompt style.

How does glm-5v-turbo compare with gpt-5, and what should you compare?

glm-5v-turbo sits alongside gpt-5 , gpt-5-2025-08-07 , glm-4.7 in the catalog. Compare them on the dimensions that change your bill and your users’ experience: task quality on your own prompts, latency at your concurrency, context and output limits, and cost per completed task rather than per token.

Can you call glm-5v-turbo with the OpenAI SDK you already use?

Yes. glm-5v-turbo is reachable through an OpenAI-compatible endpoint, so an existing OpenAI SDK client works after pointing the base URL at MixRoute and setting the model parameter to glm-5v-turbo . Keep your current request and response handling.

What should you evaluate before moving production traffic to glm-5v-turbo?

Before switching production traffic to glm-5v-turbo, run a pilot on a representative slice of your traffic and check output quality, latency at peak concurrency, and cost per request. Verify the error and retry behaviour, and confirm the request limits you depend on match your plan.

GLM-5V-Turbo API: Pricing & Specs

Model specs

Model ID: glm-5v-turbo

Context length: 200K
Max output: 128K
I/O modalities
Released: 2026-04

API endpoints

One MixRoute gateway, OpenAI-compatible

OpenAI-compatible /v1/chat/completions POST

Pricing

Flat rate, unit: /1M Tokens

Input

$75.0000 /1M Tokens

Completion

$75.0000 /1M Tokens

Selection summary

Quickly judge whether it fits your workload

What is this model good for?

Z.ai multimodal coding and agent model with visual understanding and tool use

Z.ai multimodal coding and agent model with visual understanding and tool use.

What should you check before using it?

200,000 context, 128,000 output tokens

glm-5v-turbo supports reasoning, tool calling, structured output, streaming, prompt caching, vision input and the OpenAI SDK.

Why use it through MixRoute?

glm-5v-turbo runs tools and structured output here

Tool calling and structured output run on that route as well. MixRoute serves glm-5v-turbo on the OpenAI-compatible endpoint /v1/chat/completions; point your existing client at https://api.mixroute.ai/v1 with the model ID glm-5v-turbo and re-run your integration tests.

Capabilities & compatibility

Unconfirmed capabilities stay "Unknown," no guesses

Tool calling

glm-5v-turbo supports function and tool calls.

EX Send a tools definition; the response returns tool_calls to execute and feed results back.

Structured output

glm-5v-turbo can produce JSON-formatted output on demand.

EX response_format: { type: "json_schema" } forces valid JSON output.

Streaming

glm-5v-turbo supports streamed responses.

EX stream: true streams tokens incrementally, so chat UIs render as they arrive.

Prompt caching

glm-5v-turbo supports prompt caching under supported routing conditions.

EX Keep the system prompt and tool definitions at the start of the request; repeated prefixes are automatically billed at the cache-read rate.

Vision input

glm-5v-turbo can process image inputs alongside text.

EX Pass a base64-encoded image in a image_url content part alongside text messages.

OpenAI SDK

Call glm-5v-turbo through MixRoute's OpenAI-compatible endpoint.

EX Change base_url to https://api.mixroute.ai/v1; everything else follows the OpenAI style.

Token cost estimator

Live estimate from this page's pricing, not an actual bill

Input tokens Max per request 200K

Output tokens Max per request 128K

Requests / month

Cache hit rate –

This model has no cache-read price; caching is not counted

FAQ

glm-5v-turbo is a reasoning model. Reasoning effort can be tuned per request. Lower effort settings cut reasoning tokens and cost for routine work; reserve higher settings for problems that need deeper search. Measure quality at two or three settings before fixing one in production.

Get started

01

Create an API key

Generate a key in the Console; one key calls every model.
02

Set the base URL

Fully OpenAI SDK-compatible; just swap the URL to connect.

https://api.mixroute.ai/v1
03

Specify the model ID

In the request's model field, enter:

glm-5v-turbo

Create an API key

New users get $5 in free credits

Test this model and alternate routes with the same request format

Start from a real workload, then let quality, total cost, and failure conditions decide whether to send production traffic.

Create an API key View integration docs