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ModelCap

GLM 5V Turbo

Arena #110No linked weights6.9d #61 → #63

Z.ai·#63 of 352 on the current board·cheaper than #54 Grok 4.7

GLM 5V Turbo is a language model from Z.ai. It ranks #63 of 352 on ModelCap's current board, with an Index score of 65.5, measured on 2 public benchmarks. Its score range of 60.3–70.7 spans positions #43–#83. It is listed at $1.20 per million input tokens and $4.00 per million output tokens from one provider. It reads up to 203K tokens of context, with no downloadable weights linked in the current source data.

Figures as of 6 Nov 2026, 20:32 UTC · download the public dataset · methodology

ModelCap Index · Current board
65.5#63
Measured on 2 public benchmarks · range 60.3–70.7
Evidence as of 28 Oct 2026, 00:00 UTC
Market Gravity
21.8Decreased by 0.2
Secondary market signal
Input
$1.20
per 1M tokens
Output
$4.00
per 1M tokens
Context
203K
tokens
Providers
1
endpoint

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
Z.AIfp8$1.20$4.00203Kfp8—

ModelCap Index · Current board

Methodology
65.5
Measured on 2 public benchmarks
Current board
#63 of 352
Score range
60.3–70.7
Rank range
#43–#83
Evidence as of
28 Oct 2026, 00:00 UTC
Benchmarks used
Arena Coding, Arena Overall
Technical details
Public rank basis
Measured (measured)
Evidence label
Measured · 2 public benchmark observations across 2 boards
Index support
60.6% · strong
Identity binding
Exact catalogue product · z-ai/z-ai/glm-5v-turbo · aggregates disclosed benchmark configurations · endpoint configuration not claimed
Index observations used
2
Qualified Index evidence point
65.5
Bayesian Evidence Score · measured evidence input only

BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.

Observed capability
65.5
Evidence status
confirmed · 76% mass
General preference
65.3
Coding
66.8
Agents & tools
—
Reasoning
—
Evidence breadth
92%
Evidence coverage
61%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
6.4
Liquidity (providers × uptime)
34.4
Open reach (HF downloads)
—
Surface (context / tools / modalities)
88.4
Freshness
43.4
  • · OpenRouter popularity #233
  • · 1 live provider
  • · Catalogue: context 202752, reasoning, tools, modalities Image/Text/Video
  • · First seen 2026-04-01

These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.

BES evidence selected · measured input only

The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.

Deployment readiness

Metadata index
40.4
limited · 56% metadata coverage
Not capability
Artifact reproducibility
0.0
Access & legal clarity
30.3
Deployability
80.0
Evaluation provenance
51.8

Not yet published: a pinned repository revision, the architecture and model type, a parameter count, safetensors weight metadata, the base model it derives from, a declared licence, a link to the licence terms, pinned evaluation dataset versions.

A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.

Market activity

Venue coverage
Market Gravity
21.8
OpenRouter weekly popularity
#233 of 339

Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.

Arena preference

Status
Ranked
Source
LMArena
Official rank
#110 of 419
Rating
1434.0
95% confidence interval
1428–1440
Votes
10K
Source published at
28 Oct 2026, 00:00 UTC
Category
overall
Identity match confidence
100%

Market Gravity breakdown

Usage55%
6.4

OpenRouter weekly popularity across the full model catalogue.

Liquidity25%
34.4

Independent providers versus the model's open or closed cohort, weighted by uptime.

Open reach15%
50.0

Hugging Face 30-day downloads for open models; neutral for closed models.

Freshness5%
43.4

Time since first public availability, on a six-month half-life.

Specification

Model ID
z-ai/glm-5v-turbo
Context window
203K tokens
Declared output cap
131K tokens

OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata

Inputs
Image, Text, Video
Outputs
Text
Tokenizer
Other
Cached input tokens
$0.24 / 1M
First seen on OpenRouter
1 Apr 2026

Capabilities

  • Supported: Reasoning
  • Supported: Tool use
  • Not supported: Structured output
  • Supported: Response format
  • Not supported: Moderated

Compare GLM 5V Turbo with

Pick any model

Benchmark leaderboards featuring GLM 5V Turbo

All leaderboards
Public benchmark boards on which GLM 5V Turbo has a published result
LeaderboardScoreSource rankConfigurationPublished
Arena text leaderboardArena (LMArena)14341428–1440#110 of 419Not reported28 Oct 2026
Arena coding leaderboardArena (LMArena)14881477–1499#103 of 414Default28 Oct 2026

Alternatives to GLM 5V Turbo, by the numbers

Ranked neighbours

Models within 3 places of #63 on the ModelCap Index.

Cheaper at a similar or higher Index

Index score within 3 points of, or above, this model's, with a lower listed blended price (3:1 input:output).

Other ranked Z.ai models

The same publisher's other current models with a public Index position.

GLM 5V Turbo: common questions

How does GLM 5V Turbo rank among AI models?

GLM 5V Turbo holds ModelCap Index position #63 of 352 ranked language models as of 6 November 2026, with an Index score of 65.5 (interval 60.3–70.7); evidence: measured. The Index combines public benchmark boards with published uncertainty; the methodology page explains the weighting.

How much does GLM 5V Turbo cost per 1M tokens?

GLM 5V Turbo is listed at $1.20 per 1M input tokens and $4.00 per 1M output tokens as of 6 November 2026. Prices come from the OpenRouter catalogue and re-observe on every refresh. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $4.40 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.

What is the context window of GLM 5V Turbo?

GLM 5V Turbo has a published context window of 203K tokens (202,752). The snapshot lists a 131,072 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context limit.

Is GLM 5V Turbo open-weight?

No linked weights. No downloadable model weights are linked in the current source data. This does not identify every API or chat product that offers the model.

Which API providers serve GLM 5V Turbo?

One provider serves GLM 5V Turbo through OpenRouter as of 6 November 2026: Z.AI. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has GLM 5V Turbo been evaluated on?

GLM 5V Turbo has published results on 2 public boards tracked by ModelCap as of 6 November 2026: Arena text 1434 (#110 of 419) and Arena coding 1488 (#103 of 414). Each board page ranks every tracked model on that benchmark. The ModelCap Index scores the results its methodology admits, with published uncertainty, and shows reference boards without scoring them.

How does GLM 5V Turbo compare with GLM 5.3 Flash?

GLM 5V Turbo ranks #63 (Index 65.5) and GLM 5.3 Flash ranks #22 (Index 78.2) on the ModelCap Index as of 6 November 2026. The head-to-head page lines up their benchmarks, listed prices, context windows and provider counts side by side.

When was GLM 5V Turbo released?

GLM 5V Turbo first appeared in the catalogue on 1 Apr 2026. It is the current version in its family. Rank and price movements since then are recorded on the site's changes feed.