Model profile
Z AI
New in 2026

Z.ai: GLM 5

Z.ai: GLM 5 is a budget-priced text-first model from Z AI with balanced runtime profile, standard context posture, and the clearest fit around long-context research / agent workflows.

Best for: Long-context research / Agent workflowsBalanced latencyStandard contextBudget pricing
Intelligence
40.6

Benchmark blend

Coding
39.0

Dev workflow signal

Context
80K Tokens

Standard

Input Price
$1.00

Budget tier

Decision snapshot
54

Z.ai: GLM 5 currently reads as a budget text-first option with standard context and a balanced runtime profile.

Overall profile
Use-case specific
Best for
Long-context research / Agent workflows
Latency tier
Balanced
Price tier
Budget
Source coverage
OpenRouterArtificial Analysis

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
40.6
41

General reasoning and benchmark headroom.

Limited
Speed
50 tok/s
55

TTFT 1.31s

Situational
Context
80K Tokens
64

How much prompt and task state can stay in view.

Competitive
Price
$1.00
86

$3.20 output / 1M

Efficient

Editorial Profile

Z.ai: GLM 5 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 39Math score N/A

GLM-5 is Z.ai’s flagship open-source foundation model engineered for complex systems design and long-horizon agent workflows. Built for expert developers, it delivers production-grade performance on large-scale programming tasks, rivaling leading...

Identity

Z AI text-first profile

Positioning

Long-context research / Agent workflows with standard context and balanced runtime.

Cost posture

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

Strengths
  • The available source data suggests a balanced profile rather than one dominant edge.

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

  • Latency is balanced rather than ultra-fast, which is fine for most workflows but not the snappiest tier.

  • Current metadata points to a text-first profile rather than a broad multimodal one.

  • Context window is more comfortable for focused tasks than extremely long sessions.

Best fit
  • Focused chat, retrieval-augmented flows, and narrower production tasks.

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Context
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Input Price
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Intelligence
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Context
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Input Price
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Z.ai: GLM 5 Turbo

Intelligence
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Context
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Input Price
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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
40.6
GPQA
66.6%
HLE
7.2%
Coding

Software implementation, debugging quality, and coding benchmark signal.

Coding Index
39.0
SciCode
38.3%
Agent / tool use

Long-horizon execution quality and interactive benchmark evidence.

IFBench
55.2%
TAU2
97.4%
TerminalBench Hard
39.4%
LCR
37.0%

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
80K Tokens
Vision
Text-first
Modalities
text
Tokenizer
Other
Max Completion
131072
Moderation
No
Supported Parameters
frequency_penaltyinclude_reasoninglogit_biaslogprobsmax_tokensmin_ppresence_penaltyreasoningrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_logprobstop_p
Input Modalities
text
Output Modalities
text
Price architecture
Input
per 1M input tokens
$1.00
Output
per 1M output tokens
$3.20
Blended
AA 3:1 mix
$1.55

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.