GLM 4.7 Flash
Z.ai (Zhipu AI)family · GLM4.7huggingface.co/zai-org/GLM-4.7-Flash
As a 30B-class SOTA model, GLM-4.7-Flash offers a new option that balances performance and efficiency. It is further optimized for agentic coding use cases, strengthening coding capabilities, long-horizon task planning,...
Updated 4 h ago · first seen 11 Sept 2026
model_01M294WW6CD6HGDB1WZSBZM6A7
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
- None recordedSeparate entities (checkpoint · quantization · conversion · packaging) pointing to this model through canonical_id.
- Provider deployments
- 2
- API aliases
- glm-4-7-flashglm-4-7-flash-non-reasoningz-ai/glm-4.7-flashIdentifiers under which providers and evaluators refer to this model.
- Folded evaluation variants
- 1Effort / 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 MIT; commercial use allowed; redistribution allowed; derivatives allowed; 4 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
Yes
Redistribution
Yes
Derivatives
Yes
Licence: MIT License (permissive · SPDX MIT · stated as “mit”)
dimensions marked null are unknown, not false
Key facts
- Release date
Source:OpenRouter public model & pricing listingT2observed 14 h agomedium
- Status
Source:Artificial AnalysisT2observed 12 h agomedium
- Model card
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 14 h agomedium
- Openrouter id
Source:OpenRouter public model & pricing listingT2observed 14 h agomedium
Architecture
- Architecture
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 13 h agomedium
- Model type
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 13 h agomedium
- Parameters
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 14 h agomedium
- Weights dtype
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 13 h agomedium
- File size
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 13 h agomedium
- Library name
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 13 h agomedium
- Pipeline tag
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 14 h agomedium
- Hugging Face repo
Source:OpenRouter public model & pricing listingT2observed 14 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
Artificial Analysis · T2
Vision
Unavailable
Audio
Unavailable
Fine-tuning available
Unavailable
- Context window
Source:OpenRouter public model & pricing listingT2observed 14 h agomedium
- Max output
Source:OpenRouter public model & pricing listingT2observed 14 h agomedium
- Languages
Source:Hugging Face Hub (public pages, model cards, papers)T2observed 13 h agomedium
Benchmarks24
Compare with another model →Comparable same task and conditions · Partially comparable same task, conditions differ (effort, temperature, judge) · Not comparable different variant or metric
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. 24 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 & Pricing2
All offers in the price terminal →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
Output price · USD / 1M tokens 2 providers
- Z.ai API
- OpenRouter
- OpenRouterfirst observed $0.4012 Sept 2026
- Z.ai APIfirst observed $0.4011 Sept 2026
Input price · USD / 1M tokens 2 providers
- Z.ai API
- OpenRouter
- OpenRouterfirst observed $0.0612 Sept 2026
- Z.ai APIfirst observed $0.0611 Sept 2026
Hardware fit37
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 →- descendant: cerebras/GLM-4.7-Flash-REAP-23B-A3B
Versions & Artifacts0
Version history
Context windowfirst observation only
11 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
Statusfirst 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 0
No artifact (checkpoint, quantisation, conversion or packaging) points to this model yet.
Papers1
- arXiv:2508.06471Active35
Timeline14
Full timeline →OpenRouter lists GLM 4.7 Flash at $0.0605 in / $0.4 out per 1M tokens
openrouterGLM 4.7 Flash scores 21.97% on Terminal-Bench
artificial_analysisGLM 4.7 Flash scores 98.83% on τ²-bench
artificial_analysisGLM 4.7 Flash scores 60.82% on IFBench
artificial_analysisGLM 4.7 Flash scores 7.6% on Humanity's Last Exam
artificial_analysisGLM 4.7 Flash scores 58.08% on GPQA Diamond
artificial_analysisGLM 4.7 Flash scores 14.87 on Artificial Analysis Intelligence Index
artificial_analysisGLM 4.7 Flash scores 3.79% on Terminal-Bench
artificial_analysisGLM 4.7 Flash scores 91.81% on τ²-bench
artificial_analysisGLM 4.7 Flash scores 46.26% on IFBench
artificial_analysisGLM 4.7 Flash scores 4.96% on Humanity's Last Exam
artificial_analysisGLM 4.7 Flash scores 45.15% on GPQA Diamond
artificial_analysisGLM 4.7 Flash scores 10.56 on Artificial Analysis Intelligence Index
artificial_analysisGLM 4.7 Flash: reasoning changed from false to true
ReasoningNo→Yesartificial_analysis
Change history49
Viewing AI Atlas as of 1 Jul 2026 — attributes exactly as the atlas knew them on that day; later corrections are not shown.
Back to today →GLM 4.7 Flash was not yet in AI Atlas on 1 Jul 2026
Release daterelease_date1
Statusstatus2
Opennessopenness2
Licenselicense1
Architecturearchitecture1
Parametersparameter_count1
Context windowcontext_length2
Max outputmax_output_tokens1
Modalitiesmodalities1
Input modalitiesmodalities_input1
Output modalitiesmodalities_output1
Languageslanguages1
File sizefile_size_gb1
Hugging Face repohf_repo1
Pipeline tagpipeline_tag1
Model cardmodel_card_url1
Downloadsmetric.downloads1
Likesmetric.likes2
Aa context windowaa_context_window1
Aa deprecatedaa_deprecated1
Aa opennessaa_openness1
Commercial use allowedcommercial_use_allowed1
Derivatives allowedderivatives_allowed1
Descriptiondescription1
Gatedgated1
Hf inference providershf_inference_providers1
Last modifiedlast_modified1
Library namelibrary_name1
Aa median output tokens per secondmetric.aa_median_output_tokens_per_second3
Downloads all timemetric.downloads_all_time1
Model typemodel_type1
Openrouter idopenrouter_id1
Openrouter listed atopenrouter_listed_at1
Reasoningreasoning3
Redistribution allowedredistribution_allowed1
Structured outputstructured_output1
Supported parameterssupported_parameters1
Tool callingtool_calling1
Weights availableweights_available1
Weights dtypeweights_dtype1
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
43
Source tiers
T243
Freshest observation
4 h ago
Conflicts
None
Source documents 6
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 →