GLM-4.6V: Benchmarks, Pricing & Comparison

No published category-wide ranking is available for this model.

Entries 1-12 of 42. Page 1 of 4.

Measurements without matching peer values

These measurements have no matching peer values under the same test conditions. Their original values and sources remain available here.

MMBench V1.1 (Show measurement, test conditions, and source)

Source value: 88.8
Score: 88.8
Metric: percent
Unit: %
Category: multimodal
Direction: Higher is better
Comparison cohort: research:glm-4.6v:0
Source type: vendor-reported
Evaluator: GLM-4.6V benchmark image
Status: active
Retrieved at: 2026-09-08
Methodology: Vendor-reported result. GLM-4.6V column; image labels model scales and comparator settings

Source GLM-4.6V benchmark image

MMBench V1.1 CN (Show measurement, test conditions, and source)

Source value: 88.2
Score: 88.2
Metric: percent
Unit: %
Category: multimodal
Direction: Higher is better
Comparison cohort: research:glm-4.6v:1
Source type: vendor-reported
Evaluator: GLM-4.6V benchmark image
Status: active
Retrieved at: 2026-09-08
Methodology: Vendor-reported result. GLM-4.6V column; image labels model scales and comparator settings

Source GLM-4.6V benchmark image

MMStar (Show measurement, test conditions, and source)

Source value: 75.9
Score: 75.9
Metric: percent
Unit: %
Category: multimodal
Direction: Higher is better
Comparison cohort: research:glm-4.6v:2
Source type: vendor-reported
Evaluator: GLM-4.6V benchmark image
Status: active
Retrieved at: 2026-09-08
Methodology: Vendor-reported result. GLM-4.6V column; image labels model scales and comparator settings

Source GLM-4.6V benchmark image

BLINK Val (Show measurement, test conditions, and source)

Source value: 65.5
Score: 65.5
Metric: percent
Unit: %
Category: multimodal
Direction: Higher is better
Comparison cohort: research:glm-4.6v:3
Source type: vendor-reported
Evaluator: GLM-4.6V benchmark image
Status: active
Retrieved at: 2026-09-08
Methodology: Vendor-reported result. GLM-4.6V column; image labels model scales and comparator settings

Source GLM-4.6V benchmark image

MUIRBench (Show measurement, test conditions, and source)

Source value: 77.1
Score: 77.1
Metric: percent
Unit: %
Category: multimodal
Direction: Higher is better
Comparison cohort: research:glm-4.6v:4
Source type: vendor-reported
Evaluator: GLM-4.6V benchmark image
Status: active
Retrieved at: 2026-09-08
Methodology: Vendor-reported result. GLM-4.6V column; image labels model scales and comparator settings

Source GLM-4.6V benchmark image

MMMU Val (Show measurement, test conditions, and source)

Source value: 76
Score: 76
Metric: percent
Unit: %
Category: multimodal
Direction: Higher is better
Comparison cohort: research:glm-4.6v:5
Source type: vendor-reported
Evaluator: GLM-4.6V benchmark image
Status: active
Retrieved at: 2026-09-08
Methodology: Vendor-reported result. GLM-4.6V column; image labels model scales and comparator settings

Source GLM-4.6V benchmark image

MMMU Pro (Show measurement, test conditions, and source)

Source value: 66
Score: 66
Metric: percent
Unit: %
Category: multimodal
Direction: Higher is better
Comparison cohort: research:glm-4.6v:6
Source type: vendor-reported
Evaluator: GLM-4.6V benchmark image
Status: active
Retrieved at: 2026-09-08
Methodology: Vendor-reported result. GLM-4.6V column; image labels model scales and comparator settings

Source GLM-4.6V benchmark image

VideoMMMU (Show measurement, test conditions, and source)

Source value: 74.7
Score: 74.7
Metric: percent
Unit: %
Category: multimodal
Direction: Higher is better
Comparison cohort: research:glm-4.6v:7
Source type: vendor-reported
Evaluator: GLM-4.6V benchmark image
Status: active
Retrieved at: 2026-09-08
Methodology: Vendor-reported result. GLM-4.6V column; image labels model scales and comparator settings

Source GLM-4.6V benchmark image

MathVista (Show measurement, test conditions, and source)

Source value: 85.2
Score: 85.2
Metric: percent
Unit: %
Category: multimodal
Direction: Higher is better
Comparison cohort: research:glm-4.6v:8
Source type: vendor-reported
Evaluator: GLM-4.6V benchmark image
Status: active
Retrieved at: 2026-09-08
Methodology: Vendor-reported result. GLM-4.6V column; image labels model scales and comparator settings

Source GLM-4.6V benchmark image

AI2D (Show measurement, test conditions, and source)

Source value: 88.8
Score: 88.8
Metric: percent
Unit: %
Category: multimodal
Direction: Higher is better
Comparison cohort: research:glm-4.6v:9
Source type: vendor-reported
Evaluator: GLM-4.6V benchmark image
Status: active
Retrieved at: 2026-09-08
Methodology: Vendor-reported result. GLM-4.6V column; image labels model scales and comparator settings

Source GLM-4.6V benchmark image

DynaMath (Show measurement, test conditions, and source)

Source value: 54.5
Score: 54.5
Metric: percent
Unit: %
Category: multimodal
Direction: Higher is better
Comparison cohort: research:glm-4.6v:10
Source type: vendor-reported
Evaluator: GLM-4.6V benchmark image
Status: active
Retrieved at: 2026-09-08
Methodology: Vendor-reported result. GLM-4.6V column; image labels model scales and comparator settings

Source GLM-4.6V benchmark image

WeMath (Show measurement, test conditions, and source)

Source value: 69.8
Score: 69.8
Metric: percent
Unit: %
Category: multimodal
Direction: Higher is better
Comparison cohort: research:glm-4.6v:11
Source type: vendor-reported
Evaluator: GLM-4.6V benchmark image
Status: active
Retrieved at: 2026-09-08
Methodology: Vendor-reported result. GLM-4.6V column; image labels model scales and comparator settings

Source GLM-4.6V benchmark image

Our model tests

Community tests you can inspect

Compare how the models respond to the same prompt. Each test shows the first attempt, with no subsequent fixes to the generated code. These results do not contribute to an overall score.

Pelican on a bicycle

A community classic for free-form SVG drawing.

GLM-4.6V

Not tested yet

Prompt and test conditions

Generate an SVG of a pelican riding a bicycle

Token limit including reasoning: 8,192 tokens

Task origin (Simon Willison)

Profile

Specifications and access

Published information about this model. Existing estimates are explicitly labeled.

Weights: Open weightsSource
Access: APISource
Parameters: 106BSource
Active parameters: 12BSource
Context window: 131,072 tokensSource

Additional source observations

Dated documentation and model-card observations. Provider limits, native context and extended context can differ. Configuration notes retain the source wording.

License: MITSource
Architecture: vision-language MoE with native multimodal function callingSource
Parameters: 106 BSource
Active parameters: 12 BSource
Rounded context label: 128kSource
Model configuration context: 131,072 tokens (Native checkpoint context; distinct from the rounded model-card label.)Source
Input: Text, Image, VideoSource
Output: TextSource
Reasoning mode: thinking, non-thinkingSource
Tool calling: YesSource
Maximum output: 16,384 tokensSource
Decoding: top_p 0.6, top_k 2, temperature 0.8, repetition_penalty 1.1Source

Pricing

Published prices

Prices apply to the stated unit. Resolution, output length, and provider can change the cost.

API input: $0.3 per 1M tokensSource
API output: $0.9 per 1M tokensSource

Cost example

100 API requests

$0.075

100 requests with 1,000 input and 500 output tokens each calculate to $0.075. Input accounts for $0.03; output accounts for $0.045.

Input price: $0.3 / 1M tokensBase tier for each request
Output price: $0.9 / 1M tokensBase tier for each request

The calculation uses documented token prices and no cache discount. It excludes extra tools, tax, reasoning tokens, and further hidden output tokens.

Open source

Head-to-head comparisons

Compare this model

Each matchup compares this model with exactly one other model from the same category.

There are no published direct comparisons for this model yet.

More models

Models from the same selection

All AI models

GLM-4.6

Z.ai

GLM-4.5

Z.ai

Evidence

Sources and data date

Every statement links to its underlying documentation or leaderboard.

Speed: Median across serving providers, Non-reasoning. Output speed after the first streaming chunk, not total response time. Classified as deprecated by Artificial Analysis. Artificial Analysis maintains only the default 10K-input workload there. Retrieved September 8, 2026.
Artificial Analysis Methodology
Price: Base API prices without caching or batch discounts. Higher context tiers and other rates are listed under Costs.
Pricing
Input: Documented modalities. Retrieved September 8, 2026.
Model documentation
Output: Documented modalities. Retrieved September 8, 2026.
Model documentation

Research date September 8, 2026. 4 source URLs checked. This documents the inspected sources, not an exhaustive inventory of every publication.

Open evidence questions and research notes (original wording)

Unresolved

release-date. No normalized release-date field.

Model metadataSource
API pricingSource
GLM-4.6V benchmark image (retrieved September 8, 2026)Source
Artificial Analysis (retrieved September 8, 2026)Source
Model metadata (retrieved September 8, 2026)Source
Model metadata (retrieved September 8, 2026)Source
Speed measurement methodologySource