GetInfoUs
Zhipu AI

GLM-4.7-FlashX

Vérifié par l’équipe de recherche de GetInfoUsDernière révision : October 2026Politique éditoriale
GLM efficaceOfficial Source Verified ↗
76
Intelligence Index

performances-boosted variant du Flash series optimisé pour mission critique faible-latence agents et élevé-précision structuré JSON.

Input / Output
$0.02 / $0.04
per 1M tokens
Context
200K tokens
window
Speed
150
tok/s
Latency
0.26s
TTFT

Technical Specifications

Provider
Zhipu AI
Category
lightweight
Release Date
2026-01
Knowledge Cutoff
November 2025
Architecture
Enhanced Latency-Optimized Transformer
Parameters
Confidential
Context Window
200K tokens
Max Output
8K tokens
Cached Input Price
$0.003 / 1M tokens
Batch API Discount
50% off async batch
Consumer Subscription
Free / Self-Hosted
Reasoning Mode
Yes (Chain-of-Thought)
Reasoning Effort Control
Fixed
Tool Calling
Yes
Structured Outputs
Yes
Open Weights
Yes (Open Source / Self-Hostable)
Input Modalities
text
Output Modalities
text
Official Documentation
Visit Official Docs ↗

Data Privacy, Licensing & Deployment Governance

API Data Training Policy
100% Isolated when self-hosted on private GPUs or VPC
Model License & Commercial Rights
Open-Weights Research & Commercial License
Deployment & Cloud Availability
Self-Hosted GPU (vLLM / Ollama), Private VPC, or Managed Serverless API
Output Ownership
Full commercial ownership of generated outputs

Official Provider Release Intelligence, API Quotas & Agentic Specs

Compare Multi-Models Side-by-Side →
Official API Model ID (SDK String)
glm-4-7-flashx
Supported SDK & API Protocol
OpenAI-Compatible REST / vLLM / SGLang / HuggingFace TGI
Lifecycle & Deprecation Status
Active GA (Guaranteed support through 2028+)
Production Rate Limits (RPM & TPM)
Unlimited (Hardware-bound on self-hosted GPU) / 10,000 RPM Cloud · Unlimited local throughput / 10M+ TPM Managed Cloud
Long-Context Pricing Tier (>128K / >200K)
Flat rate ($0.02/1M in) across full 200K window
Prompt Cache Write & TTL Policy
Cached input at $0.003/1M tokens
Computer Use & Browser GUI Agent
API / CLI Tool-Use & DOM Agent ready (no raw pixel desktop click loop)
MCP & Parallel Tool Calling
Native MCP Client/Server ready · Parallel function calling · 100% Strict JSON Schema
Web Search Grounding & Code Sandbox
Supported via external Tavily/Exa Search & E2B/Docker Sandbox tools
Fine-Tuning & Distillation Support
Full Weights SFT, LoRA, QLoRA, DPO & GRPO RL (Unsloth / Axolotl / Llama-Factory)
Multimodal Tokenization Billing
Text BPE (~4 chars/token)
Weights Precision & Quantization
BF16 / FP16, FP8 Dynamic, INT4 AWQ / GPTQ, GGUF (Q4_K_M / Q8_0)
Minimum GPU VRAM Requirement
43 GB VRAM (4-bit Quantized) · 151 GB VRAM (Native BF16)
Supported Inference Engines
vLLM, SGLang, Ollama, llama.cpp, TensorRT-LLM, HuggingFace TGI
System Card & Safety Framework
Open-Weights System Card + Customizable Guardrail Layer (Llama Guard / ShieldGemma)
Enterprise Compliance (SOC2 / HIPAA / ZDR)
100% Air-Gapped On-Premises / Private VPC · Full HIPAA, GDPR & SOC2 Control
Engineering & Pricing Workbench

GLM-4.7-FlashX Cost, Context, Hardware & API Integration

500 / day
4,000 tok
1,000 tok
Conversation Depth (History Re-billing):1 Turn (Single-Shot)
50%
Estimated Monthly API Cost (30 Days)
$1.29$1.80
Monthly Savings: $0.51 (Caching/Batch)
Daily Cost:
$0.04
Cost per Request:
$0.00009
Effective Input / 1M:
$0.011
Effective Output / 1M:
$0.040
Subscription ($20/mo) vs API

Pay-as-you-go API is cheaper for this volume (saves $18.71/mo vs $20 flat plan).

Break-even point: ~7,752 requests/day equals $20/month.

Same Monthly Workload Cost Across Popular Reference Models

GLM-4.7-FlashX (Active)
$1.29
/ month
Gemini 2.5 Flash
$18.00
/ month
DeepSeek V3
$32.70
/ month
GPT-4o
$300.00
/ month
Claude 3.7 Sonnet
$405.00
/ month

Live Prompt Paste Tokenizer & Cost Counter

Paste real system instructions, JSON schemas, or code to measure BPE token counts across tokenizers.

Chars / Words
175 / 24
OpenAI o200k
~46 tok
Claude BPE
~49 tok
Llama / DeepSeek
~51 tok

Hybrid Prompt Routing Cascade Simulator

Route routine queries to a fast lightweight model ($0.15/1M) and escalate only complex reasoning turns to GLM-4.7-FlashX:

Cascaded Monthly Bill:$13.82/mo
This model is already priced at or below the fast router baseline.

Benchmark Scores & 6-Axis Capability Radar

Benchmark Encyclopedia
Coding (85)Reasoning (76)Knowledge (75)Speed (100)Context (85)Cost Value (94)
GLM-4.7-FlashX2026 Frontier Median
MMLU-Pro
74.5%
HumanEval
85%
Chatbot Arena Elo
1290pts

Strengths

  • Elevated raisonnement et codage scores sur le standard Flash baseline
  • Stricter adhering à complicated function calling signatures et nested paramètres
  • Highly economical API tarification ($0.02 / 1M entrée tokens)

Limitations & Trade-offs

  • Cannot substitute pour profond de pointe flagships sur complexe algorithmic architecture
  • No visuel image entrée support

Editorial Assessment

le ideal faible-coût outil-calling modèle pour développeurs demanding vitesse et structural fidelity.

Best for: mission critique automatisé routage, backend agent functions, et élevé-frequency API bridges

Compare GLM-4.7-FlashX

GLM-4.7-FlashX vs GLM-4.7-FlashGLM-4.7-FlashX vs Qwen3.5 122B-A10BGLM-4.7-FlashX vs GLM-5GLM-4.7-FlashX vs Gemini 4 ArgonGLM-4.7-FlashX vs GPT-6 AstraGLM-4.7-FlashX vs Claude Opus 5.5GLM-4.7-FlashX vs GPT-6.1 Sol

Frequently Asked Questions about GLM-4.7-FlashX

How much does the GLM-4.7-FlashX API cost per 1M tokens?+

GLM-4.7-FlashX by Zhipu AI is priced at $0.02 per 1M input tokens and $0.04 per 1M output tokens. With prompt caching enabled, cached input tokens cost $0.003 per 1M tokens, and asynchronous Batch API requests receive a 50% discount.

Should I use a $20/month subscription or the GLM-4.7-FlashX pay-as-you-go API?+

A flat $20/month consumer subscription is predictable for daily interactive chat and manual coding. However, if you are building software, running automated workflows, or sending low-to-moderate volume with prompt caching enabled, the pay-as-you-go API is typically far more cost-effective and offers higher rate limits without manual UI caps.

How many words and pages fit in GLM-4.7-FlashX's context window?+

GLM-4.7-FlashX features a 200K tokens context window, which equals approximately 150,000 English words or ~400 standard single-spaced pages in a single prompt. Its maximum output generation per turn is 8,192 tokens.

Can I run GLM-4.7-FlashX locally on my own GPU (Open Weights)?+

Yes, GLM-4.7-FlashX (Confidential) releases open weights that can be self-hosted locally or on private cloud GPUs using vLLM, Ollama, SGLang, or llama.cpp.

Does Zhipu AI train on data sent to the GLM-4.7-FlashX API, and is commercial use allowed?+

100% Isolated when self-hosted on private GPUs or VPC. License tier: Open-Weights Research & Commercial License. Full commercial ownership of generated outputs. Supported deployment channels include: Self-Hosted GPU (vLLM / Ollama), Private VPC, or Managed Serverless API.

How does GLM-4.7-FlashX perform on coding and reasoning benchmarks?+

GLM-4.7-FlashX achieves a composite Intelligence Index of 76/100, scoring N/A% on SWE-bench Verified, N/A% on GPQA Diamond, 74.5% on MMLU-Pro, and 1290 pts on Chatbot Arena Elo.

What is GLM-4.7-FlashX best used for?+

GLM-4.7-FlashX is best suited for: mission critique automatisé routage, backend agent functions, et élevé-frequency API bridges. Assessment: le ideal faible-coût outil-calling modèle pour développeurs demanding vitesse et structural fidelity.

Zhipu AI Family Lineage, Routing Tiers & Upgrade Path

Step down to a lighter sibling for high-volume routing or step up to Zhipu AI's flagship reasoning tier:

Fast Router / Budget Tier2026-06

GLM-5.2

$0 / $0 · 1M tokensIQ 91
Fast Router / Budget Tier2026-04

GLM-5.1

$0 / $0 · 200K tokensIQ 89
Higher-Intelligence Upgrade2026-04

GLM-5V-Turbo

$0.9 / $2.7 · 200K tokensIQ 85
Higher-Intelligence Upgrade2026-03

GLM-5-Turbo

$0.6 / $1.8 · 200K tokensIQ 86
Fast Router / Budget Tier2026-02

GLM-5

$0 / $0 · 205K tokensIQ 87
Sibling Production Tier2026-01

GLM-4.7-Flash

$0.015 / $0.03 · 200K tokensIQ 74

AI Glossary & Architecture Concepts

View full glossary →

Key machine learning concepts and benchmarks relevant to GLM-4.7-FlashX:

Jeton (Token)

L'unité textuelle de base traitée par un modèle linguistique, représentant généralement 3 à 4 caractères ou environ 0,75 mot. Par exemple, une phrase courante est découpée en plusieurs jetons.

Benchmark (Banc d’essai)

Une suite de tests standardisés permettant d'évaluer et de comparer objectivement les performances des modèles d'IA sur des tâches ciblées (code avec SWE-bench, mathématiques avec AIME, etc.).

Fenêtre de contexte

Le nombre maximal de jetons qu'un modèle peut traiter simultanément (entrée et sortie comprises). Une fenêtre de 1 000 000 jetons permet d'analyser environ 750 000 mots en une seule requête.

Modèle de raisonnement

Un modèle d'IA entraîné par apprentissage par renforcement pour allouer du temps de calcul à la réflexion logique avant d'émettre une solution, idéal pour les problèmes scientifiques et le code complexe.

Chaîne de pensée (CoT)

Une méthode de raisonnement pas-à-pas où le modèle décompose le problème en étapes logiques intermédiaires avant de conclure, augmentant drastiquement la précision en mathématiques et programmation.

Appel d'outils (Tool Calling)

La capacité d'un LLM à déterminer quand une action externe est requise et à générer des arguments structurés pour invoquer des API, calculatrices ou bases de données avant de poursuivre.

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Les scores de benchmarks, tarifs par token et limites évoluent rapidement. Vérifiez toujours les spécifications actuelles sur la documentation officielle du fournisseur.

Sources: Zhipu AI BigModel Platform↗