Tier A — Frontier
Runs in:CNMade in:China
Z.ai (GLM / Zhipu)

GLM-4.5V (vision)

Tier A — Frontier · 66K tokens

Tokonomix Editorial Team·Reviewed by Mes Kalkan··

GLM-4.5V is the vision-capable member of the GLM-4.5 line: it accepts images with text and reasons over both. It is a capable multimodal option anchored in the well-understood GLM-4.5 generation.

Section 01

Speed analysis

Latency measured across all benchmark runs. P50 (median) and P95 (95th percentile) give a realistic picture of response speed under normal and peak load.

P50 latency (median)P95 latency108 runs
584831316042237713150008-0909-05ms
Section 02

Quality scores

How this model compares to the rest of the field on each prompt category, from a pairwise fit over the same prompts. The raw judge score sits underneath each number.

50%
Coding
judge mean 62
8%
Creative
judge mean 54
39%
Factual
judge mean 65
6%
Reasoning
judge mean 23

Win rate per category: how often this model beats a field-average model on a prompt from that category. 50% is average, not a failing grade. It is not a percentage of correct answers.

Section 03

Pricing history

Direct provider rates per million tokens, plus a typical-conversation cost estimate.

💰
API rates — GLM-4.5V (vision)
$0.6000 per 1M input tokens
$1.80 per 1M output tokens
≈ $0.0007 per typical conversation (800 tokens)
Input vs output price (per 1M tokens)
per 1M input tokens$0.6000
per 1M output tokens$1.80

Pricing over time

Input & output per 1M tokens · step-line = price changes

$0.6000

input / 1M

— stable

$1.80

output / 1M

— stable

2026-07-122026-08-092026-08-30
Input
Output
Price change
⟳ synced weekly
Section 04

Tokens per second

Throughput in tokens per second, derived from measured P50 latency. Higher is better; fluctuations track provider-side load.

Throughput (tokens / s)252 / avg 176
33933

Estimated from P50 latency × 200 output tokens — the absolute number depends on this assumption; the trend is what matters.

Section 05

Capabilities

jsonnotes: GLM emits a non-standard reasoning_content field beside content; read content for the answer.toolsvision
Section 06

Availability

Availability

No measurements yet

We haven't recorded enough API calls to show availability stats for this model. Data appears once the model starts receiving live traffic.

Section 07

Tokonomix benchmark verdicts

⚖️
Endorsed by 1 judge
Independent LLM judges evaluated this model on our weekly intelligence tests
claude-sonnet-4-552/100 · 26 runs
10 correct2 partial14 wrong38% accuracy
● 2026-08-30

GLM-4.5V maintains multimodal capabilities with stable performance

GLM-4.5V continues to offer vision, JSON, and tools capabilities with no significant performance changes detected in the current benchmark window. The model maintains its position as a multimodal solution from Zhipu AI, supporting structured output generation and function calling alongside image understanding tasks. With no benchmark results available for either the current or previous windows, performance characteristics remain unquantified. The model's capability set has stabilized after the initial introduction of vision, JSON, and tools support in the previous period. Users should note that while the feature set is established, the absence of benchmark data means comparative performance against other vision-language models cannot be determined. The model appears to be in a maintenance phase with consistent capability offerings. Organizations evaluating GLM-4.5V for multimodal applications should conduct their own testing to validate performance for specific use cases, particularly for vision-related tasks, structured data extraction, and tool integration scenarios. The stability in capabilities suggests a mature feature set, though quantitative performance metrics would provide greater confidence for production deployments.

Quality

—

Latency p50

—

Test runs

0

✓ Stable capability set maintained✗ No benchmark data available
Section 08

Full model profile

GLM-4.5V: the GLM-4.5 vision model

GLM-4.5V is the vision-capable member of the GLM-4.5 line: it accepts images with text and reasons over both. It is a capable multimodal option anchored in the well-understood GLM-4.5 generation.

z.ai publishes GLM-4.5V at $0.60 per 1M input tokens and $1.80 per 1M output tokens.

It advertises a 64K-token context window — smaller than GLM-4.6V, but ample for typical image-plus-prompt tasks.

Architecture & training signals

GLM-4.5V is the vision variant of Zhipu AI’s GLM-4.5, adding image input to the text model. It produces text output reasoning over the supplied images, with tool and JSON support over an OpenAI-compatible endpoint. Output modality is text (image understanding, not generation). Like the rest of the GLM line, it returns a non-standard reasoning_content field alongside content in its OpenAI-compatible responses; integrations should read content for the final answer and treat reasoning_content as an optional trace.

Where it shines

  • Image understanding grounded in the mature GLM-4.5 generation.
  • Visual QA, extraction and description tasks.
  • Tool-calling and JSON for multimodal agents.

Where it falls short

  • Smaller context window than GLM-4.6V; and it reads, not generates, images.
  • No Tokonomix benchmark data yet; validate on your images.
  • Non-EU hosting.

Real-world use cases

  • Screenshot and document understanding.
  • Visual question answering.
  • Multimodal analysis pipelines.

Tokonomix benchmark snapshot

GLM-4.5V is newly registered on Tokonomix and not yet activated, so we have not run it through our weekly intelligence test or speed benchmark. There are no Tokonomix scores to report yet — and we will not invent any.

When it goes live, it enters the same weekly harness as every other model: identical prompts, an independent cross-family judge, and reproducible latency and cost measurements. Until then, treat the pricing and capability notes on this page as the vendor-published starting point, not as measured Tokonomix results.

EU privacy & data residency

GLM-4.5V is built by Zhipu AI (z.ai), a China-headquartered lab, and is served from non-EU infrastructure. This is important to state plainly: routing a prompt to this model is not an EU-data-residency or GDPR-sovereign choice, and Tokonomix will never tag it as one.

If your use case requires data to stay within the EU, pick a model whose provider is EU-hosted (for example our OVH or Azure-EU routes) rather than a GLM model. Tokonomix keeps z.ai out of every EU-only / sovereign routing set by design. Use GLM where its capability or price is the priority and cross-border processing is acceptable for that workload.

Verdict & alternatives

GLM-4.5V is a solid GLM-4.5-generation vision model. For a larger context window and a lower price, GLM-4.6V is the newer pick; for zero cost, GLM-4.6V Flash.

Last automated test
Sep 5, 2026 · 08:02 UTC · Speed benchmark
P50 latency
795 ms
P95 latency
1635 ms
Errors
0 / 6 runs
Last reviewed by Tokonomix Team·July 8, 2026