Model profile
z-ai

Z.ai: GLM 4.6V

Z.ai: GLM 4.6V is a budget multimodal generalist from z-ai with a heavy runtime profile, extended context posture, and the clearest fit around long-context research / multimodal.

Best for: Long-context research / MultimodalHeavy latencyExtended contextBudget pricing
Intelligence
17.1

Benchmark blend

Coding
19.7

Dev workflow signal

Context
131K Tokens

Extended

Input Price
$0.30

Budget tier

Decision snapshot
36

Z.ai: GLM 4.6V currently reads as a budget multimodal option with extended context and a heavy runtime profile.

Overall profile
Use-case specific
Best for
Long-context research / Multimodal
Latency tier
Heavy
Price tier
Budget
Source coverage
OpenRouterArtificial AnalysisVision signal

Decision Strip

Decision rail before the raw tables

Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.

Intelligence
17.1
17

General reasoning and benchmark headroom.

Limited
Speed
21 tok/s
8

TTFT 4.01s

Limited
Context
131K Tokens
76

How much prompt and task state can stay in view.

Competitive
Price
$0.30
86

$0.90 output / 1M

Efficient

Editorial Profile

Z.ai: GLM 4.6V in one narrative

Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.

Use-case specificCoding score 20Math score 85Vision enabled

GLM-4.6V is a large multimodal model designed for high-fidelity visual understanding and long-context reasoning across images, documents, and mixed media. It supports up to 128K tokens, processes complex page layouts and charts directly as visual inputs, and integrates native multimodal function calling to connect perception with downstream tool execution. The model also enables interleaved image-text generation and UI reconstruction workflows, including screenshot-to-HTML synthesis and iterative visual editing.

Identity

z-ai multimodal profile

Positioning

Long-context research / Multimodal with extended context and heavy runtime.

Cost posture

Efficient spend profile. More comfortable for sustained prompt volume if the capability fit is right.

Strengths
  • Large context headroom supports repo-wide prompts and long research sessions.

  • Vision-capable routing opens up multimodal review and extraction workflows.

Tradeoffs
  • Budget-friendly input pricing is a strength, but raw capability may vary by workload.

  • Latency profile is better for deliberate runs than rapid back-and-forth chat.

Best fit
  • Image-grounded review, multimodal extraction, and UI audit workflows.

  • Long-context summarization, repo analysis, and policy or document review.

Compare Next

Similar profiles worth opening next

z-ai

Z.ai: GLM 4.7

Intelligence
42.1
Context
203K Tokens
Input Price
$0.60
z-ai

Z.ai: GLM 5

Intelligence
40.6
Context
203K Tokens
Input Price
$1.00
z-ai

Z.ai: GLM 4.6

Intelligence
32.5
Context
205K Tokens
Input Price
$0.57

Benchmarks

Grouped by job-to-be-done

Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.

General intelligence

Broad reasoning, knowledge depth, and flagship benchmark posture.

Intelligence Index
17.1
MMLU Pro
75.2%
GPQA
56.6%
HLE
8.9%
Coding

Software implementation, debugging quality, and coding benchmark signal.

Coding Index
19.7
LiveCodeBench
0.160
SciCode
30.4%
Math

Formal reasoning, structured problem solving, and competition-style math.

Math Index
85.3
AIME 2025
85.3%
Agent / tool use

Long-horizon execution quality and interactive benchmark evidence.

IFBench
30.1%
TAU2
31.6%
TerminalBench Hard
14.4%
LCR
40.3%

Specs & Pricing

Technical snapshot and cost posture

Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.

Technical snapshot
Context Window
131K Tokens
Vision
Enabled
Modalities
text, image, video->text, video
Tokenizer
Other
Max Completion
131072
Moderation
No
Supported Parameters
frequency_penaltyinclude_reasoningmax_tokensmin_ppresence_penaltyreasoningrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_p
Input Modalities
imagetextvideo
Output Modalities
text
Price architecture
Input
per 1M input tokens
$0.30
Output
per 1M output tokens
$0.90
Blended
AA 3:1 mix
$0.45

This model is relatively efficient on price. It is the easier fit when sustained prompt volume matters.

Metadata

Raw source tables at the end

Verification details remain available, but the page no longer forces them ahead of the editorial read.