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ModelCap

GLM 4.5

All-versions archive #132Arena #136Official publisher releaseOpen weights

Z.ai·z-ai/glm-4.5

GLM 4.5 is ModelCap archive rank #132 (Measured), from the ModelCap Index as of 22 Sept 2026, 02:49 UTC.

GLM 4.5 listed OpenRouter input price is $0.60 per 1M tokens and listed output price is $2.20 per 1M tokens, from OpenRouter listed prices as of 22 Sept 2026, 02:49 UTC.

GLM 4.5 has a published context limit of 131K tokens in the ModelCap catalogue as of 22 Sept 2026, 02:49 UTC.

GLM 4.5 has 1 published OpenRouter serving endpoint, from OpenRouter as of 22 Sept 2026, 02:49 UTC.

GLM 4.5 weight access is open weights, from ModelCap classification of published repository metadata as of 22 Sept 2026, 02:49 UTC.

Snapshot facts · download the public dataset · methodology

ModelCap Index · All-versions archive
57.0#132
Measured · 63% support · score interval 52.0–62.0
Evidence as of 13 Sept 2026, 00:00 UTC
Market Gravity
42.5Decreased by 0.2
Secondary market signal

Superseded by GLM 5.3. It no longer holds a current-board position; its all-versions archive rank is #132.

Input
$0.60
per 1M tokens
Output
$2.20
per 1M tokens
Context
131K
tokens
Providers
1
endpoint
Gateway spend
latest · Vercel share

Providers

Uptime measured over the last 30 minutes
ProviderInputOutputContextQuantUptime
Z.AIfp8$0.60$2.20131Kfp8100.0%

Reported evaluation leads (2)

Not independent measurement

Structured rows reported in this exact model repository at the pinned revision below. They are the publisher talking about itself: never measured evidence, never a score input on their own. They remain quarantined until dataset revision, harness, configuration and identity pass ModelCap’s independent admission review.

Dataset / taskMetricValueRevisionProvenance
cais/hle
none
8.32
Unpinned
not published
Reported
Quarantined
TIGER-Lab/MMLU-Pro
mmlu_pro
84.6
Unpinned
not published
Reported
Quarantined

Other versions (6)

ModelCap Index · All-versions archive

Methodology
57.0
Measured · 2 public benchmark observations across 2 boards
All-versions archive
#132
Public rank basis
Measured (measured)
Index support
63.0% · strong
Index interval
52.0–62.0
Rank posterior
Not available
Top 5 / Top 10 probability
Not available / Not available
Posterior as of
Snapshot timestamp unavailable
Evidence as of
13 Sept 2026, 00:00 UTC
Identity binding
Exact catalogue product · z-ai/z-ai/glm-4.5 · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata zai-org/GLM-4.5@cbb2c7cfb52fa128a9660cb1a7a78e017899e115 (not the evaluation revision)
Index observations used
2
Qualified Index evidence point
57.0
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
57.0
Evidence status
confirmed · 77% mass
General preference
57.5
Coding
52.8
Agents & tools
Reasoning
Evidence breadth
92%
Evidence coverage
63%
Market and catalogue signals · secondary, never the language Index rank
Usage (OpenRouter popularity)
6.4
Liquidity (providers × uptime)
98.8
Open reach (HF downloads)
88.2
Surface (context / tools / modalities)
70.2
Freshness
19.9
  • · OpenRouter popularity #222
  • · 1 live provider
  • · HF 30d downloads 95635
  • · Catalogue: context 131072, reasoning, tools
  • · First seen 2025-07-25

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
80.1
strong · 94% metadata coverage
Not capability
Artifact reproducibility
85.0
Access & legal clarity
100.0
Deployability
80.0
Evaluation provenance
53.0

Missing: artifactReproducibility.base-lineage, evaluationProvenance.evaluation-dataset-revisions.

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

Market activity

Venue coverage
Market Gravity
42.5
OpenRouter weekly popularity
#222 of 322

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
#136 of 402
Rating
1411.3
95% confidence interval
1406–1416
Votes
24K
Source published at
13 Sept 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%
98.8

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

Open reach15%
88.2

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

Freshness5%
19.9

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

Specification

Context window
131K tokens
Max output
98K tokens
Inputs
Text
Outputs
Text
Tokenizer
Other
Cached input tokens
$0.11 / 1M
First seen on OpenRouter
25 Jul 2025
Knowledge cutoff
2024-12-31

Capabilities

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

Weights & access

Open weights. Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI.

Access
Open weights
Licence
mit
Pinned revision
cbb2c7cfb52f
Parameters
358.3B
Architecture
Glm4MoeForCausalLM
Model type
glm4_moe
Hugging Face downloads (30d)
96K
Downloads (all time)
1.1M
Likes
1K
Repository
zai-org/GLM-4.5
Repository updated
11 Aug 2025, 13:27 UTC

Benchmark leaderboards featuring GLM 4.5

All leaderboards
Public benchmark boards on which GLM 4.5 has a published result
LeaderboardScoreSource rankConfigurationPublished
Arena coding leaderboardArena (LMArena)14551446–1463#137 of 397Default13 Sept 2026
SWE-bench leaderboardSWE-bench (Princeton / SWE-agent team)54.2%#32 of 47Default22 Aug 2025
τ²-Bench Telecom (Artificial Analysis run)Artificial Analysis43.0%#228 of 436tau2:telecom:dual-control:pass-at-1:3-repeats:source-model="GLM-4.5 (Reasoning)":reasoning=true13 Sept 2026
Humanity's Last Exam (Artificial Analysis run)Artificial Analysis13.0%#241 of 615hle:may-2025:text-only-2158:no-tools:pass-at-1:source-model="GLM-4.5 (Reasoning)":reasoning=true13 Sept 2026

GLM 4.5: common questions

How does GLM 4.5 rank among AI models?

GLM 4.5 is a superseded version and is not on the current board as of 22 September 2026. Its archive position, where one exists, is shown on the page; the newer version carries the current rank.

How much does GLM 4.5 cost per 1M tokens?

GLM 4.5 is listed at $0.60 per 1M input tokens and $2.20 per 1M output tokens as of 22 September 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 $2.30 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 4.5?

GLM 4.5 has a published context window of 131K tokens (131,072) and a maximum output of 98K tokens. Individual providers can serve less than the published maximum; the providers table lists each endpoint's own limit.

Is GLM 4.5 open-weight?

Open weights (mit). Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI. The repository is zai-org/GLM-4.5 on Hugging Face.

Which API providers serve GLM 4.5?

One provider serves GLM 4.5 through OpenRouter as of 22 September 2026: Z.AI. Each provider's price, context limit, quantization and measured uptime are in the providers table above.

Which benchmarks has GLM 4.5 been evaluated on?

GLM 4.5 has published results on 4 public boards tracked by ModelCap as of 22 September 2026: Arena coding 1455 (#137 of 397), SWE-bench 54.2% (#32 of 47), AA τ²-Bench Telecom 43.0% (#228 of 436) and AA Humanity's Last Exam 13.0% (#241 of 615). Each board page ranks every tracked model on that benchmark; the ModelCap Index combines them with published uncertainty.

When was GLM 4.5 released?

GLM 4.5 first appeared in the catalogue on 25 Jul 2025, with a published knowledge cutoff of 2024-12-31. It has since been superseded by GLM 5.3. Rank and price movements since then are recorded on the site's changes feed.