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GLM 5.3

Z.ai (Zhipu AI)family · GLM5.3huggingface.co/zai-org/GLM-5.3

GLM-5.3 is a large-scale reasoning model from Z.ai, built for complex software engineering and long-horizon agent tasks. It supports text input and output with a 1M-token context window, and improves...

Open in Graph
data quality72

Updated 2 h ago · first seen 11 Sept 2026

model_01M294AJ5462DT6GQKJAGHX7FP

Overview

Identity

Canonical model
Yesidentity confidence: mediumOne row per real model release. Artifacts (checkpoints, quantisations, conversions) and folded evaluation variants point here.
Official checkpoints
official_checkpoints = hf_repo identifiers carried by the model itself; artifacts are separate entities pointing here through canonical_id.
Artifacts
1 quantization0 official · 1 third-partySeparate entities (checkpoint · quantization · conversion · packaging) pointing to this model through canonical_id.
Provider deployments
4
API aliases
fireworks/glm-5p3glm-5-3z-ai/glm-5.3Identifiers under which providers and evaluators refer to this model.
Folded evaluation variants
0Effort / thinking variants (…-high, …-non-reasoning) are result configurations of this model, not separate models. Their old URLs redirect here.

Openness

Open weights— weights downloadable under Other; 7 dimensions unknown.

Weights downloadable under a permissive or Creative Commons licence allowing commercial use; code or data may be missing.

  • Weights

    Yes

  • Inference code

    —

  • Training code

    —

  • Training data

    —

  • Dataset

    —

  • Commercial use

    —

  • Redistribution

    —

  • Derivatives

    —

Licence: Other (unclassified licence) (unknown · stated as “other”)

dimensions marked null are unknown, not false

Key facts

Release date

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 7 h agomedium

Model card
huggingface.co/zai-org/GLM-5.3

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 h agomedium

Openrouter id

Source:OpenRouter public model & pricing listingT2observed 12 h agomedium

Architecture

Architecture

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium

Model type

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium

Parameters

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 h agomedium

Weights dtype

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium

File size

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium

Library name

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium

Pipeline tag

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 12 h agomedium

Hugging Face repo

Source:OpenRouter public model & pricing listingT2observed 12 h agomedium

Capabilities

Modalities

Modalities
text
Input
text
Output
text

Capabilities

  • Tool calling

    Yes

    OpenRouter public model & pricing listing · T2

  • Structured output

    Yes

    OpenRouter public model & pricing listing · T2

  • Reasoning

    Yes

    OpenRouter public model & pricing listing · T2

  • Vision

    Unavailable

  • Audio

    Unavailable

  • Fine-tuning available

    Unavailable

Context window

Source:OpenRouter public model & pricing listingT2observed 9 h agomedium

Max output

Source:OpenRouter public model & pricing listingT2observed 12 h agomedium

Languages

Source:Hugging Face Hub (public pages, model cards, papers)T2observed 11 h agomedium

Benchmarks20

Compare with another model →

Comparable same task and conditions · Partially comparable same task, conditions differ (effort, temperature, judge) · Not comparable different variant or metric

Benchmark results grouped by comparability group
Benchmark · groupBest scoreTrustConfigurationResultsvs leaderEvaluatedSource
Terminal-Benchagentic · accuracy · variant=v2.1 · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisvariantv2.1reasoning_effortmaxconditions differ across rows → partially comparable2non-primary groupobs. 12 Sept 2026artificialanalysis.aiT2
Terminal-Benchagentic · accuracy · variant=v4.0 · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisvariantv4.0reasoning_effortmaxconditions differ across rows → partially comparable2non-primary groupobs. 12 Sept 2026artificialanalysis.aiT2
LiveBench Agentic Codingcoding · average score · variant=Agentic CodingOfficial boardvariantAgentic Codingrelease2026-06-251−16.4 ptvs DeepSeek-V4.1-Flash25 Jun 2026livebench.aiT2
LiveBench Codingcoding · average score · variant=CodingOfficial boardvariantCodingrelease2026-06-251−7.42 ptvs Claude Fable 5.125 Jun 2026livebench.aiT2
SciCodecoding · accuracy · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisreasoning_effortmaxconditions differ across rows → partially comparable2−4.05 ptvs Claude Fable 5.1obs. 12 Sept 2026artificialanalysis.aiT2
Artificial Analysis Intelligence Indexcomposite · indexIndependentreasoning_effortmaxversion4.3conditions differ across rows → partially comparable2−8.51vs Claude Fable 5.1obs. 12 Sept 2026artificialanalysis.aiT2
LiveBenchgeneral · global_averageOfficial boardrelease2026-06-251−7.28 ptvs Claude Fable 5.125 Jun 2026livebench.aiT2
LiveBench Data Analysisgeneral · average score · variant=Data AnalysisOfficial boardvariantData Analysisrelease2026-06-251−12.7 ptvs gpt-6-astra25 Jun 2026livebench.aiT2
LiveBench Languagegeneral · average score · variant=LanguageOfficial boardvariantLanguagerelease2026-06-251−10.8 ptvs Claude Fable 525 Jun 2026livebench.aiT2
LiveBench Instruction Followinginstruction-following · average score · variant=IFOfficial boardvariantIFrelease2026-06-251−12.1 ptvs Gemini 3.8 Flash25 Jun 2026livebench.aiT2
Humanity's Last Examknowledge · accuracy · evaluator=Artificial AnalysisIndependentevaluatorArtificial Analysisreasoning_effortmaxconditions differ across rows → partially comparable2−16.9 ptvs Claude Fable 5.1obs. 12 Sept 2026artificialanalysis.aiT2
LiveBench Mathematicsmath · average score · variant=MathematicsOfficial boardvariantMathematicsrelease2026-06-251−9.11 ptvs Claude Fable 5.125 Jun 2026livebench.aiT2
GPQA Diamondreasoning · accuracy · variant=Diamond · evaluator=Artificial AnalysisIndependentevaluatorArtificial AnalysisvariantDiamondreasoning_effortmaxconditions differ across rows → partially comparable1non-primary groupobs. 12 Sept 2026artificialanalysis.aiT2
GPQA Diamondreasoning · accuracy · variant=GPQA Diamond · evaluator=Artificial AnalysisIndependentevaluatorArtificial AnalysisvariantGPQA Diamond1−4.54 ptvs gpt-6-astraobs. 11 Sept 2026artificialanalysis.aiT2
LiveBench Reasoningreasoning · average score · variant=ReasoningOfficial boardvariantReasoningrelease2026-06-251−6.85 ptvs gpt-6-astra25 Jun 2026livebench.aiT2

Current rows only, grouped by benchmark → canonical metric → comparability group (task configuration). Effort variants folded into this model appear as rows of the same group. 20 current rows in total. “vs leader” compares with the current leader of the benchmark's primary group only; other groups are not directly comparable. Comparability rules →

Providers & Pricing7

All offers in the price terminal →
Provider deployments, cheapest output first
ProviderContextInput / 1MCached inOutput / 1MStatusObservedSource
OpenRoutercheapest outputz-ai/glm-5.3:batch1.05Mout 943.7K$0.13active43 min agosince 12 Sept 2026openrouter.aiT2
Z.ai APIz-ai/glm-5.3:batch1.05Mout 943.7K$0.13active3 h agosince 11 Sept 2026openrouter.aiT2
Fireworks AIfireworks/glm-5p3—$0.26active5 h agosince 11 Sept 2026app.fireworks.aiT1
OpenRouterz-ai/glm-5.31.05Mout 943.7K$0.26active43 min agosince 12 Sept 2026openrouter.aiT2
Together AIglm-5-3—$0.26active10 h agosince 11 Sept 2026together.aiT1
Z.ai APIz-ai/glm-5.31.05Mout 943.7K$0.26active3 h agosince 11 Sept 2026openrouter.aiT2
Fireworks AIfireworks/glm-5p3:fast—$0.39active5 h agosince 12 Sept 2026app.fireworks.aiT1

USD per 1M tokens as published by each provider; native units (per-request fees, flex/priority tiers) are kept verbatim. Rows are append-only — every price change is kept in the history below. Cost of a workload →

Price history

Step lines per provider; amber markers are recorded changes. Click a marker or a row for the evidence behind that price.

Output price · USD / 1M tokens 4 providers

Output price history of GLM 5.3$0$2$4$6$8Sept 26Sept 26Sept 26Sept 26Fireworks AI: first observed → $4.4 · 11 Sept 2026Z.ai API: first observed → $4.4 · 11 Sept 2026Z.ai API: $4.4 → $2.2 · 11 Sept 2026Together AI: first observed → $4.4 · 11 Sept 2026Fireworks AI: $4.4 → $6.6 · 12 Sept 2026OpenRouter: first observed → $4.4 · 12 Sept 2026OpenRouter: $4.4 → $2.2 · 12 Sept 2026
  • Fireworks AI
  • Z.ai API
  • Together AI
  • OpenRouter
  • OpenRouter$4.4 → $2.212 Sept 2026
  • OpenRouterfirst observed $4.412 Sept 2026
  • Fireworks AI$4.4 → $6.612 Sept 2026
  • Together AIfirst observed $4.411 Sept 2026
  • Z.ai API$4.4 → $2.211 Sept 2026
  • Z.ai APIfirst observed $4.411 Sept 2026
  • Fireworks AIfirst observed $4.411 Sept 2026

Input price · USD / 1M tokens 4 providers

Input price history of GLM 5.3$0$0.50$1$1.5$2$2.5Sept 26Sept 26Sept 26Sept 26Fireworks AI: first observed → $1.4 · 11 Sept 2026Z.ai API: first observed → $1.4 · 11 Sept 2026Z.ai API: $1.4 → $0.70 · 11 Sept 2026Together AI: first observed → $1.4 · 11 Sept 2026Fireworks AI: $1.4 → $2.1 · 12 Sept 2026OpenRouter: first observed → $1.4 · 12 Sept 2026OpenRouter: $1.4 → $0.70 · 12 Sept 2026
  • Fireworks AI
  • Z.ai API
  • Together AI
  • OpenRouter
  • OpenRouter$1.4 → $0.7012 Sept 2026
  • OpenRouterfirst observed $1.412 Sept 2026
  • Fireworks AI$1.4 → $2.112 Sept 2026
  • Together AIfirst observed $1.411 Sept 2026
  • Z.ai API$1.4 → $0.7011 Sept 2026
  • Z.ai APIfirst observed $1.411 Sept 2026
  • Fireworks AIfirst observed $1.411 Sept 2026

Hardware fit37

Estimated

3 of 37 device × quantization combinations fit.

Run locally: your machine →
Estimated hardware fit
HardwareQuantizationDevice memoryEst. memoryFits
Apple M3 Ultra4bit—433.7 GB est.Yes
Mac Studio (Apple M5 Ultra)4bit—433.7 GB est.Yes
NVIDIA DGX B2004bit1,440 GB433.7 GB est.Yes
Apple M2 Ultra4bit—433.7 GB est.No
Apple M1 Ultra4bit—433.7 GB est.No
Apple M3 Max4bit—433.7 GB est.No
Apple M4 Max4bit—433.7 GB est.No
Mac Studio (Apple M5 Max)4bit—433.7 GB est.No
MacBook Pro (Apple M5 Max)4bit—433.7 GB est.No
Apple M2 Max4bit—433.7 GB est.No
Apple M1 Max4bit—433.7 GB est.No
Apple M4 Pro4bit—433.7 GB est.No
Mac mini (Apple M5 Pro)4bit—433.7 GB est.No
MacBook Pro (Apple M5 Pro)4bit—433.7 GB est.No
Apple M3 Pro4bit—433.7 GB est.No
Apple M1 Pro4bit—433.7 GB est.No
Apple M2 Pro4bit—433.7 GB est.No
Apple M44bit—433.7 GB est.No
iMac (Apple M4)4bit—433.7 GB est.No
Mac mini (Apple M6)4bit—433.7 GB est.No
MacBook Air (Apple M5)4bit—433.7 GB est.No
MacBook Pro (Apple M5)4bit—433.7 GB est.No
Apple M24bit—433.7 GB est.No
Apple M34bit—433.7 GB est.No
Apple M14bit—433.7 GB est.No
NVIDIA GeForce RTX 30904bit24 GB433.7 GB est.No
NVIDIA GeForce RTX 40904bit24 GB433.7 GB est.No
NVIDIA GeForce RTX 50904bit32 GB433.7 GB est.No
NVIDIA A100 80GB4bit80 GB433.7 GB est.No
NVIDIA H100 SXM4bit80 GB433.7 GB est.No
NVIDIA H100 NVL4bit94 GB433.7 GB est.No
NVIDIA DGX Spark4bit128 GB433.7 GB est.No
NVIDIA H2004bit141 GB433.7 GB est.No
NVIDIA H200 NVL4bit141 GB433.7 GB est.No
NVIDIA B2004bit180 GB433.7 GB est.No
AMD Instinct MI300X4bit192 GB433.7 GB est.No
AMD Instinct MI325X4bit256 GB433.7 GB est.No
Assumptions (7)
  • Estimated, not measured: weights = parameters × bytes/param × 1.15 runtime overhead (or the observed artifact file size when one is recorded).
  • bytes/param: 4bit = 0.5, 8bit = 1.0, fp16 = 2.0 (uniform quantization, no per-layer exceptions).
  • KV cache: 2 × layers × kv_heads × head_dim × 2 bytes × context × batch when the architecture is known; otherwise 0.5 GB per 8 192 tokens (× batch), independent of architecture (GQA/MLA models need less).
  • A model 'fits' when the estimate is at most the device memory minus 2 GB reserved for the OS and framework.
  • Mixture-of-experts models are estimated on total parameters (all experts must be resident); active parameters are ignored.
  • Device memory uses the largest configuration when several are listed (e.g. Apple silicon tiers).
  • Multi-GPU: device memories are summed; interconnect bandwidth, tensor-parallel replication and pipeline bubbles are not modelled.

Lineage

Open in Graph →
Explicit derived_from / fine_tuned_from / distilled_from relations stated by sources; artifacts collapsed by kind.
DESCENDANTS 0 · ARTIFACTS1 quantizationartifacts · collapsed1 quantization — artifacts · collapsedGLM 5.3753.3B params · this modelGLM 5.3 — 753.3B params · this model

    Versions & Artifacts1

    Version history

    Context window2 changes

    11 Sept 2026→11 Sept 2026→12 Sept 2026current

    Licensefirst observation only

    11 Sept 2026current

    Max outputfirst observation only

    11 Sept 2026current

    Opennessfirst observation only

    11 Sept 2026current

    Parametersfirst observation only

    11 Sept 2026current

    Each hop is a claim: click a value for its source, tier and observation time. Nothing is overwritten — a new observation closes the previous claim.

    Artifacts 1

    quantization 1

    Papers1

    Timeline12

    Full timeline →
    • Listed by providerModelGLM 5.3Z.ai (Zhipu AI)

      OpenRouter lists GLM 5.3 at $0.7 in / $2.2 out per 1M tokens

      openrouter
      openrouter.ai
    • Listed by providerModelGLM 5.3Z.ai (Zhipu AI)

      OpenRouter lists GLM 5.3 at $1.4 in / $4.4 out per 1M tokens

      openrouter
      openrouter.ai
    • Benchmark resultModelGLM 5.3Z.ai (Zhipu AI)

      GLM 5.3 scores 83.9% on Terminal-Bench

      artificial_analysis
      artificialanalysis.ai
    • Benchmark resultModelGLM 5.3Z.ai (Zhipu AI)

      GLM 5.3 scores 41.92% on Terminal-Bench

      artificial_analysis
      artificialanalysis.ai
    • Benchmark resultModelGLM 5.3Z.ai (Zhipu AI)

      GLM 5.3 scores 59.03% on SciCode

      artificial_analysis
      artificialanalysis.ai
    • Benchmark resultModelGLM 5.3Z.ai (Zhipu AI)

      GLM 5.3 scores 42.26% on Humanity's Last Exam

      artificial_analysis
      artificialanalysis.ai
    • Benchmark resultModelGLM 5.3Z.ai (Zhipu AI)

      GLM 5.3 scores 91.72% on GPQA Diamond

      artificial_analysis
      artificialanalysis.ai
    • Benchmark resultModelGLM 5.3Z.ai (Zhipu AI)

      GLM 5.3 scores 44.86 on Artificial Analysis Intelligence Index

      artificial_analysis
      artificialanalysis.ai
    • Listed by providerModelGLM 5.3Z.ai (Zhipu AI)

      Fireworks AI lists GLM 5.3 at $2.1 in / $6.6 out per 1M tokens

      fireworks_pricing
      app.fireworks.ai
    • Context window changedModelGLM 5.3Z.ai (Zhipu AI)

      GLM 5.3: context length changed from 1000000 to 1310720

      Context window1M tokens→1.31M tokensopenrouter
      openrouter.ai
    • Release date changedModelGLM 5.3Z.ai (Zhipu AI)

      GLM 5.3: release date changed from 2026-08-25 to 2026-08-18

      Release date25 Aug 2026→18 Aug 2026openrouter
      openrouter.ai
    • Release date changedModelGLM 5.3Z.ai (Zhipu AI)

      GLM 5.3: release date changed from 2026-08-18 to 2026-08-25

      Release date18 Aug 2026→25 Aug 2026huggingface
      huggingface.co

    Change history

    Temporal, append-only claims: a new observation closes the previous claim instead of overwriting it. Rewind the record with the as-of picker.
    1 claims · 1 propertiesShow all properties

    Claims are temporal and append-only: a new observation closes the previous claim (valid_to) instead of overwriting it. Conflicting claims from different sources are kept side by side and flagged — never averaged. Methodology →

    Provenance

    Attributed facts

    42

    Source tiers

    T242

    Freshest observation

    2 h ago

    Conflicts

    None

    Source documents 9

    Source documents
    SourceDocumentTypeTierLast observedSnapshots
    Together AI — pricingtogether.ai/pricing pricingT1· Official40 min ago1
    Fireworks AI — pricingdocs.fireworks.ai/serverless/pricing.md pricingT1· Official2 h ago2
    OpenRouter public model & pricing listingopenrouter.ai/api/v1/models catalogueT2· Quality secondary43 min ago9
    Artificial Analysisartificialanalysis.ai/leaderboards/models leaderboardT2· Quality secondary2 h ago2
    Hugging Face Hub (public pages, model cards, papers)huggingface.co/models?author=zai-org&p=0&sort=downloads listingT2· Quality secondary2 h ago7
    Hugging Face Hub (public pages, model cards, papers)huggingface.co/zai-org/GLM-5.3/raw/main/README.md model_cardT2· Quality secondary5 h ago1
    Hugging Face Hub (public pages, model cards, papers)huggingface.co/zai-org/GLM-5.3 model_pageT2· Quality secondary6 h ago5
    Hugging Face Hub (public pages, model cards, papers)huggingface.co/amd/GLM-5.3-Quark-MXFP4-AttnFP8 model_pageT2· Quality secondary6 h ago5
    LiveBenchlivebench.ai/table_2026_06_25.csv leaderboardT2· Quality secondary10 h ago1

    Tier 1 = official/primary, 2 = quality secondary, 3 = community, 4 = unverified. Every snapshot is archived; see all sources and the methodology.

    Data quality (72/100) measures how well AI Atlas knows this entity — completeness, primary-source ratio, freshness, conflicts — never how good the model is. Methodology →