GLM-5.3 — Specifications
Compilado por Mustafa Ihsan de la documentación publicada por el proveedor · Última actualización
| Desarrollador | Zhipu AI |
|---|---|
| Tipo | LLM (para programación/agentes, MoE) |
| Modalidad | Texto → Texto |
| Parámetros | 744B total / 40B active (MoE) |
| Ventana de contexto | 1 millón |
| Salida máxima | 128 K |
| Licencia | GLM-5.3 License (open weights) |
| Pesos abiertos | Sí |
| Lanzado | 2026-08 |
| Precio de entrada | $1.40 /1M |
| Precio de salida | $4.40 /1M |
| Proveedores de API | Zhipu (Z.ai), Alibaba Cloud Model Studio, OpenRouter |
Benchmarks
| Z.ai-reported | Terminal Bench 3.0 28.3 (GLM-5.2: 4.6); DeepSWE v1.1 66.9 (GLM-5.2: 46.2); CyberGym 84.5 (GLM-5.2: 77.2). Cached input $0.26 per 1M tokens. |
|---|
What is GLM-5.3?
GLM-5.3 is Zhipu AI’s (Z.ai) latest flagship model, released on 18 August 2026. According to Z.ai, it uses the same base model as GLM-5.2, with every improvement coming from post-training: Z.ai reports a 50% gain over GLM-5.2 on its in-house Z.ai Code Bench and much stronger results at finding and exploiting software vulnerabilities, including 84.5% on CyberGym. It is a 744B-parameter mixture-of-experts with 40B active parameters. It takes text only, with a 1M-token context window and up to 128K output tokens, and it always reasons: effort can be set to low, high or max, but reasoning cannot be switched off.
Z.ai’s API charges $1.40 per million input tokens, $0.26 per million cached input tokens and $4.40 per million output tokens, with cache storage free for a limited time, the same price as GLM-5.2. Alibaba Cloud Model Studio also lists it at $1.40 / $4.40, and it is available to subscribers of Z.ai’s GLM Coding Plan. For cheaper work, GLM-5.3-Flash (320B total, 18B active) costs $0.15 in / $0.50 out.
The weights are on Hugging Face in FP8, a download of about 756 GB, under Z.ai’s GLM-5.3 License rather than the MIT licence of GLM 5.2. The licence is permissive, but Model-as-a-Service companies with more than $10 billion in revenue over 12 months must pass a Z.ai security review before commercial use. At the same price, GLM-5.3 is the natural pick over GLM 5.2 for new projects; compare monthly costs with the Calculadora de costos de API de IA.
GLM-5.3 pricing: API cost per 1M tokens
| Entrada (por cada millón de tokens) | $1.40 |
|---|---|
| Salida (por cada millón de tokens) | $4.40 |
| Relación salida/entrada | 3,1× |
| Combinada (4:1 entrada:salida) | $2.00 por 1 millón de tokens |
What GLM-5.3 costs per month
Gasto mensual real con una mezcla entrada:salida de 4:1, es decir, la proporción que realmente genera una carga de trabajo típica de chat o RAG.
| Carga de trabajo | Tokens/mes | Coste mensual |
|---|---|---|
| Proyecto secundario | 1 millón de tokens de entrada / 0,25 millones de tokens de salida | $2.50 |
| Pequeño equipo | 20 millones de tokens de entrada / 5 millones de tokens de salida | $50 |
| Producción | 200 millones de tokens de entrada / 50 millones de tokens de salida | $500 |
Calcule sus propios números en la Calculadora de costos de API de IA.
Cheaper alternatives to GLM-5.3
| Modelo | Dólares por millón combinados | Usted ahorra |
|---|---|---|
| Llama 3.1 8B abierta | $0.0240 | 99 % más barato |
| Mistral NeMo 12B abierta | $0.0292 | 99 % más barato |
| Gemma 3 4B abierta | $0.0600 | 97% más barato |
Preguntas frecuentes
How much does GLM-5.3 cost per 1M tokens?
GLM-5.3 costs $1.40 per 1M input tokens and $4.40 per 1M output tokens. At a typical 4:1 input-to-output mix that blends to about $2.00 per 1M tokens.
How much does GLM-5.3 cost per month?
A small-team workload of 20M input and 5M output tokens a month costs about $50 on GLM-5.3. A side project (1M in / 0.25M out) costs roughly $2.50.
What is a cheaper alternative to GLM-5.3?
Llama 3.1 8B is the strongest cheaper option in our database at $0.0240 per 1M blended — about 99% less than GLM-5.3. It is also open-weight, so self-hosting is an option.
Can I run GLM-5.3 locally?
Yes. GLM-5.3 is open-weight and needs about a large amount of VRAM at 4-bit quantisation.
Why does GLM-5.3 charge more for output than input?
Output tokens are generated one at a time and cannot be batched the way a prompt can, so they cost the provider more to serve. GLM-5.3 charges 3.1× more for output, which is why prompt-heavy workloads are far cheaper to run than generation-heavy ones.
Los precios corresponden a las tarifas oficiales publicadas para la API principal del modelo y se revisan periódicamente conforme los proveedores los actualicen. No incluyen descuentos por volumen, procesamiento por lotes ni entradas en caché. Compare todos los modelos uno al lado del otro en la Base de datos de modelos de IA o el Clasificación de modelos de lenguaje grande (LLM).