THE MODEL, IN DETAIL / zai

glm-5v-turbo

z-ai/glm-5v-turboProprietaryReasoning

GLM-5V-Turbo is Z.ai’s first native multimodal agent foundation model, built for vision-based coding and agent-driven tasks. It natively handles image, video, and text inputs, excels at long-horizon planning, complex coding,...

OpenRouter
Source-linked model intelligenceCatalog added 1 Apr 2026Specifications observed 17 Oct 2026

Text models

#82

Arena rating

Context window

202.8K

131.1K max output tokens

Input price

$1.2

USD / million input tokens

Output price

$4

USD / million output tokens

Inference providers

1

1 provider routes observed

Measured output speed

—

No model-level measurement

01 / PERFORMANCE

A clearer view of capability.

Read the score, understand the context, and explore where this model sits among its peers.

In good company

Text models · Arena · official dataset

1,532.3
Google
1,515.8
Anthropic
1,511.6
Anthropic
1,507.6
Anthropic
1,502.5
Anthropic
1,501.7
Anthropic
1,501
Meta
1,498.9
Google
1,497.5
Anthropic
1,491.2
Anthropic

416 models in the source cohort. Showing selected nearby models. Evaluation settings can differ.

Evidence, by task.

Coverage is not a capability score.

0published results
0 evaluation sources
ReasoningAwaiting evidence
CodingAwaiting evidence
MathematicsAwaiting evidence
VisionAwaiting evidence
AgenticAwaiting evidence
Long contextAwaiting evidence

Documented features, task evaluations, and preference rankings describe different things. Missing coverage does not imply a model cannot perform a task.

Explore our methodology

02 / BENCHMARK EXPLORER

The numbers behind the model.

Original results, exact versions, and a direct path to the evidence behind every score.

0 published results

Percentage-based evaluations will appear here when published.

0 percentage-based evaluations. Each benchmark measures a different task; compare results within the same evaluation and protocol.

Artificial Analysis indices

Published in the OpenRouter catalog · source-defined index values

Intelligence Index23.5

Catalog observation: 17 Oct 2026. Index versions and evaluation settings are not supplied in this feed. These are not Singularity composite scores.

Artificial Analysis

Design Arena

Source-reported Elo across individual design categories

Agenticgamedev1,102
agents arena · Rank #23 · 42.5% win rate
Agentichtmlslides1,134
agents arena · Rank #7 · 41.7% win rate
Agenticslides1,171
agents arena · Rank #5 · 51.6% win rate
Agenticslides(Html)1,137
agents arena · Rank #7 · 41.8% win rate
Agenticslides(Python-Pptx)1,183
agents arena · Rank #5 · 53.9% win rate
Androidnative1,267
agents arena · Rank #4 · 54.8% win rate
Fullstack1,149
agents arena · Rank #26 · 52% win rate
Godotgamedev957
agents arena · Rank #35 · 26.9% win rate
Htmlslides1,120
agents arena · Rank #21 · 44.6% win rate
Mobileapps1,132
agents arena · Rank #33 · 50.4% win rate
Pptxslides1,164
agents arena · Rank #5 · 52.1% win rate
Python-Pptxslides1,165
agents arena · Rank #20 · 51.9% win rate
Webapps1,116
agents arena · Rank #32 · 44.7% win rate
3d1,210
models arena · Rank #44 · 52.3% win rate
Asciiart1,120
models arena · Rank #55 · 42.8% win rate
Codecategories1,230
models arena · Rank #50 · 49.6% win rate
Dataviz1,202
models arena · Rank #57 · 47.6% win rate
Gamedev1,220
models arena · Rank #45 · 50% win rate
Svg1,149
models arena · Rank #43 · 48.8% win rate
Uicomponent1,212
models arena · Rank #52 · 48.2% win rate
Website1,231
models arena · Rank #50 · 48.9% win rate

Catalog observation: 17 Oct 2026. Category ratings have separate comparison pools.

03 / COST & VALUE

Know what your workload costs.

Explore token prices, see where the spend goes, and model a workload of your own.

Input$1.2per million tokens
Output$4per million tokens
Cache read$0.24per million tokens
Cache write—per million tokens

Workload cost calculator

Change the numbers. See the trade-offs.

Token estimate only. Excludes cache writes, tools, and other provider fees. Actual token usage and provider limits vary.

Your estimated spend

1,000 requests · 11M tokens

$16estimated total
Uncached input$12
Cached input$0
Output$4
Per request$0.016
Without cache discount$16
Estimated cache savings$0

04 / INFERENCE NETWORK

One model. Different ways to run it.

Compare inference routes by price, context, quantization, and reported availability.

1 providers · 1 routes
Provider routes for glm-5v-turbo, observed 17 Oct 2026
Provider / routeInput / MOutput / MCache / MContextOutput limitSpeedLatencyAvailability · 1dRates
ZZ.AIFP8$1.2$4$0.24202.8K131.1K——99.36%

Snapshot observed 17 Oct 2026. Speed and latency are the reported 30-minute median when available. This is a dated snapshot, not live monitoring.

Provider price comparison

USD per million tokens · input and output rates

InputOutput
Z.AIfp8
Input
$1.2
Output
$4

Reported availability

Provider availability over the selected observation window

Z.AI · FP899.36%

Output speed

Reported 30-minute p50 · tokens per second

No provider throughput measurements were returned in this snapshot.

Response latency

Reported 30-minute p50 · seconds

No provider latency measurements were returned in this snapshot.

Context by provider

Actual route limits can differ from the catalog maximum

Z.AI · FP8202.8K

05 / CAPABILITIES & MODALITIES

What goes in. What comes out.

A map of documented interfaces and API features, separate from benchmark performance.

INPUT MODALITIES

ImageTextVideo
glm-5v-turboReasoning supported

OUTPUT MODALITIES

Text

Feature support

Listed catalog API parameters and documented pricing features

ReasoningSupported
Tool callingSupported
Tool choiceSupported
Structured outputsNot listed
Response formatSupported
Reasoning detailsSupported
Seed controlNot listed
Stop sequencesNot listed
Prompt cachingSupported
TemperatureSupported

Room to work

Context capacity and completion limits

202.8Ktotal context tokens
Context window
131.1Kmax output

Output tokens share the total context budget. The maximum completion length is a separate limit, and individual provider routes may have smaller limits.

Catalog context
202,752 tokens
Maximum output
131,072 tokens
Top-provider context
202,752 tokens

Features vary by route

Check the provider before depending on a specific API feature.

API feature support by provider
Provider routeReasoningToolsStructured outputResponse formatImplicit caching
Z.AI · FP8SupportedSupportedNot listedSupportedSupported

06 / UNDER THE HOOD

The complete specification sheet.

Exact identities, model architecture, limits, and the defaults that shape a request.

Identity & architecture

Developer
zai
Exact identity
glm-5v-turbo
Subject
Model Configuration
Access
proprietary
License
Proprietary
Parameters
Not disclosed
Tokenizer
Other
Instruction format
Not disclosed

Reasoning & controls

Reasoning
Supported
Mandatory reasoning
No
Reasoning by default
Enabled
Published configuration
Not disclosed
Supported reasoning efforts
Not documented
Default reasoning effort
Not disclosed
API parameters
9
Provider moderation
No
Quantization variants
fp8

Dates & limits

Catalog added
1 Apr 2026
Knowledge cutoff
Not disclosed
Catalog expiration
Not documented
Specifications observed
17 Oct 2026
Providers observed
17 Oct 2026
Request limits
Provider-specific / not supplied
Canonical catalog ID
z-ai/glm-5v-turbo-20260401

API parameters & defaults

Availability is catalog-wide. Defaults can vary across providers.

include_reasoningSupported · default not supplied
max_tokensSupported · default not supplied
reasoningSupported · default not supplied
response_formatSupported · default not supplied
temperatureDefault: 1
tool_choiceSupported · default not supplied
toolsSupported · default not supplied
top_kSupported · default not supplied
top_pDefault: 0.95
presence_penaltyDefault setting
frequency_penaltyDefault setting
repetition_penaltyDefault setting

07 / BUILD WITH THIS MODEL

From exploration to your first request.

Use the documented catalog identifier and keep your API key in an environment variable.

Make an API request

const response = await fetch(
  "https://openrouter.ai/api/v1/chat/completions",
  {
    method: "POST",
    headers: {
      Authorization: `Bearer ${process.env.OPENROUTER_API_KEY}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({
      "model": "z-ai/glm-5v-turbo",
      "messages": [
        {
          "role": "user",
          "content": "Explain the trade-offs in this design."
        }
      ]
    }),
  },
);
if (!response.ok) throw new Error(`HTTP ${response.status}`);
const data = await response.json();
console.log(data.choices[0].message.content);

08 / PROVENANCE & HISTORY

Every number has a story.

Follow the source, check the observation date, and distinguish published results from model specifications.

The source register

Direct links to the underlying records

01
OpenRouter model catalog

Architecture, modalities, parameters, and starting prices

Observed 17 Oct 2026
02
OpenRouter provider routes

Provider limits, prices, availability, and reported measurements

Observed 17 Oct 2026
03
Text models ranking

Arena rating · source-reported ranking

Observed 15 Oct 2026
04
Web development ranking

Arena rating · source-reported ranking

Observed 13 Oct 2026
05
Vision ranking

Arena rating · source-reported ranking

Observed 9 Oct 2026

The observation trail

Recorded events, in chronological order

Added to the model catalog

Catalog creation date, as recorded by OpenRouter.

Model specifications observed

Catalog pricing, limits, and supported parameters captured.

Provider routes observed

1 inference routes in this snapshot.

Observation dates describe when data was captured. They do not represent newly run evaluations or continuous performance monitoring.

Published observation ledger

Historical evidence, with source and version preserved.

No published benchmark observations for this selection. Published preference rankings appear separately above.

09 / A FEW MORE DETAILS

Questions worth asking.

Quick answers, drawn from this model’s connected specifications.

How much does glm-5v-turbo cost?

Catalog starting rates are $1.2 per million input tokens and $4 per million output tokens. Cache-read pricing is $0.24 per million tokens. Compare provider routes and service tiers above for their specific prices.

How much context can it handle?

202,752 tokens in the catalog context window. The catalog lists a maximum of 131,072 completion tokens. Provider limits can differ.

Does it support tools and structured output?

Tool calling: listed as supported. Structured outputs: not listed. See the provider feature matrix for route-specific differences.

How should I interpret these benchmark results?

Read the benchmark name, exact version, metric, source, and model configuration together. Different evaluation settings can change the result. Preference ratings and source-defined composite indices remain separate from task accuracy.

Are these prices and provider measurements live?

This page uses dated source snapshots. Catalog data was observed on 17 Oct 2026. Provider routes were observed on 17 Oct 2026. Missing measurements are not estimated or treated as zero.

KEEP EXPLORING

More from zai.

Explore related identities from the same developer, or take them into a side-by-side comparison.

THE RIGHT MODEL STARTS WITH THE RIGHT CONTEXT.

Put the details side by side.

Explore the trade-offs in a direct model comparison.

Compare glm-5v-turbo