Z.ai: GLM 4.7

Public pricingIntelligence 83/100Large memoryRéflexion approfondieOutils

Z.ai: GLM 4.7 est un modèle texte conçu pour raisonnement, planification et automatisation. Il associe une utilisation fiable des outils et des agents et un raisonnement et une planification poussés, un contexte de 203K tokens et un profil à coût équilibré pour un travail fiable sur reasoning, planning, and multi-step automation.

Input

$0.38/1M

Output

$1.74/1M

Cached

$0.11/1M

Batch

$0.30/1M

Calculate your GLM 4.7 bill.

Set your workload — see cost at your exact volume.

What would GLM 4.7 cost you?

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1,00010,00050,000250,0001M10M

Technical specifications

GLM 4.7 at a glance.

Memory

202,752

tokens

Max reply

131,072

tokens

Memory tier

Large

an entire book or large codebase

Tokenizer

—

Released

Dec 2025

Training cutoff

Aug 2025

Availability

Public pricing

Status

active

Benchmarks

Quality benchmarks

Independent evaluations from public leaderboards. Higher is better.

  • aime_2025

    95.7

  • frontiermath_tier_4

    0

  • gpqa_diamond

    85.7

  • livecodebench

    84.9

  • mmlu_pro

    84.3

  • swe_bench_verified

    73.8

What it can do

Capabilities & limits.

  • Understands images
  • Deep step-by-step thinking
  • Uses tools / calls functions
  • Strict JSON output
  • Streams replies
  • Fine-tunable on your data

When to pick GLM 4.7

  • Multi-step reasoning, research agents, or hard math.
  • Agentic workflows that call tools or APIs.
  • Long documents, full codebases, or extensive chat histories.
  • High-volume workloads where unit cost matters.

When to look elsewhere

  • Your workload involves images — pick a vision-capable model instead.

Alternatives

Similar models to compare.

FAQ

GLM 4.7 — the questions we see most.

Pricing, capabilities, alternatives — generated from the same data that powers the calculator above.

Get instant answers from our AI agent

At a typical workload of 50,000 conversations a month with 1,500-token prompts and 800-token replies, GLM 4.7 costs roughly $98 per month. Input is $0.38 /1M tokens and output is $1.74 /1M tokens.
GLM 4.7 has a 202,752-token context window (large memory — an entire book or large codebase). That means you can fit about 38,016 words of input and history in a single call.
Beyond text generation, GLM 4.7 supports deep step-by-step reasoning, calling functions / tools, strict JSON output, fine-tuning on your own data. It streams replies by default.
GLM 4.7 was released in December 2025, with training data cut off around August 2025.
Models in a similar class include GLM 4.6, GLM 4.7 Flash, Kimi K2.5. The "Similar models" section below this FAQ links into each.

Still unsure?

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