Unlock exclusive introductory pricing for the newly launched Gemini 3.5 Flash.
Z

GLM 5.1

Wejล›cie:$1.12/M
Wyjล›cie:$3.528/M
Kontekst:20.0k
Maks. wyjล›cie:128,000
Wydano:Apr 15, 2026

TEST GLM-5.1 (released April 2026), purpose-built for long-horizon autonomous tasks. Unlike traditional models optimized for short interactions, GLM-5.1 excels at maintaining goal alignment, reducing strategy drift, and delivering production-grade results over extended periods โ€” up to 8 hours of continuous autonomous work on a single complex task. It represents a major leap in agentic engineering, shifting evaluation from single-turn intelligence to real-world sustained execution.

Nowy
Popularny
Uลผycie komercyjne

Playground dla GLM 5.1

Poznaj Playground GLM 5.1 โ€” interaktywne ล›rodowisko do testowania modeli i uruchamiania zapytaล„ w czasie rzeczywistym. Wyprรณbuj prompty, dostosuj parametry i iteruj natychmiast, aby przyspieszyฤ‡ rozwรณj i zweryfikowaฤ‡ przypadki uลผycia.

Technical Specifications of GLM-5.1

SpecificationDetails
DeveloperZ.ai (Zhipu AI)
Model VersionGLM-5.1 (post-training refinement of GLM-5)
ArchitectureMixture-of-Experts (MoE); ~744โ€“754 billion total parameters, ~40 billion active per token; incorporates Multi-head Latent Attention and DeepSeek Sparse Attention for long-context efficiency
Context Length200Kโ€“203K tokens (up to 202,752โ€“204.8K in some configurations)
Maximum Output Tokens128K tokens
ModalitiesText-only (input/output); no native vision or audio support
Key CapabilitiesThinking modes, streaming output, function calling/tool use (MCP integration), context caching, structured JSON output
LicenseMIT (fully open-source weights)
Deployment OptionsOfficial API, local inference (vLLM, SGLang), Hugging Face / ModelScope
Training HardwareHuawei Ascend chips (no Nvidia dependency)

What is GLM-5.1

GLM-5.1 is Z.aiโ€™s frontier-class language model optimized for long-horizon autonomous tasks. Unlike traditional LLMs that excel at short, single-turn interactions, it is engineered for sustained execution loopsโ€”planning, coding, testing, benchmarking, debugging, and iterative optimizationโ€”over extended periods without human intervention.

Key Features of GLM-5.1

1. Long-Horizon Autonomous Work

8-Hour Sustained Execution: GLM-5.1 is Z.AIโ€™s latest flagship model for long-horizon tasks, and the official docs say it can work continuously and autonomously on a single task for up to 8 hours. It is positioned to handle the full loop from planning and execution to iterative optimization and final delivery.

Closed-Loop Optimization: A core feature of GLM-5.1 is its ability to keep iterating through an โ€œexperiment โ†’ analyze โ†’ optimizeโ€ cycle, rather than stopping at one-shot output. Z.AI describes this as a major step toward autonomous engineering and long-horizon coding agents.

2. Strong Coding and Reasoning Ability

Broad Capability Balance: GLM-5.1 is broadly aligned with Claude Opus 4.6 in general capability and coding performance, and that it shows a balanced profile across reasoning, coding, agents, tool use, and browsing benchmarks.

Advanced Engineering Workflows: GLM-5.1 is designed for real-world development workflows, including complex engineering optimization, debugging, and production-grade delivery. Z.AI positions it as a foundation for autonomous agents and long-horizon coding agents.

3. Better Support for Complex Tasks

Larger Context and Output: The migration guide lists GLM-5.1โ€™s maximum context length as 200K and maximum output as 128K, which makes it more suitable for large tasks and extended sessions.

Deep Thinking and Tool Streaming: GLM-5.1 supports deep thinking mode, and Z.AI also adds streaming output during tool calls with tool_stream=true, which helps expose tool-call parameters in real time.

4. Built for Agentic Engineering

From Code Generation to Autonomous Delivery: Z.AIโ€™s positioning for GLM-5.1 is not just โ€œgenerate code,โ€ but โ€œdeliver engineering work.โ€ The docs describe it as a new-generation flagship model for โ€œAgentic Engineering,โ€ emphasizing planning, execution, optimization, and delivery in one workflow.

Stronger Stability Over Long Tasks: The release notes say GLM-5.1 improves stability, consistency, and tool use over extended tasks, supported by multi-turn SFT, RL, and process-quality evaluation.

GLM-5.1 vs Other Models

GLM-5.1 stands out as one of the strongest open-source options and a direct competitor to closed frontier models in coding and agentic scenarios:

  • vs. Claude Opus 4.6: ~94โ€“100% of coding performance on SWE-Bench Pro (58.4 vs. 57.3); superior long-horizon autonomy and lower cost via open weights/aggregators.
  • vs. GPT-5.4: Outperforms on SWE-Bench Pro (58.4 vs. 57.7); competitive or slightly behind in some pure reasoning tasks.
  • vs. GLM-5 (predecessor): 28% coding uplift and dramatically better sustained execution.
  • vs. Llama 3.1 / Qwen / DeepSeek: Stronger agentic and long-horizon results; open MIT license provides greater customization freedom than many alternatives.

Its primary advantages are open-source accessibility, cost efficiency at scale, and specialized optimization for real-world engineering agents.

Use Cases

GLM-5.1 excels wherever long-running, iterative intelligence is required:

  • Autonomous Software Engineering: Full-stack feature development, code migration, large-scale refactoring, and end-to-end testing with minimal oversight.
  • Performance Optimization: Kernel-level improvements, database tuning, and multi-iteration benchmarking (e.g., 6.9ร— vector query speedup).
  • Agentic Workflows: Integration into coding agents (Claude Code, OpenClaw) for repository-scale tasks or complex system building.
  • Enterprise Productivity: Long-document analysis, report generation, and structured office artifacts.
  • Research & Prototyping: Rapid iteration on ambiguous problems requiring hundreds of self-correcting steps.

How to Access GLM-5.1 via CometAPI

CometAPI, a unified AI model aggregator, provides immediate, OpenAI-compatible access to GLM-5.1 (and GLM-5) alongside 500+ other models. Developers simply sign up at cometapi.com, obtain an API key, and route requests to the GLM-5.1 endpoint(glm-5.1) using standard OpenAI SDKs or Chat Completions. No infrastructure setup is requiredโ€”CometAPI handles inference routing, load balancing, and failover.

Current CometAPI Pricing (approximate, as of mid-April 2026):

  • Input: $0.8 per million tokens
  • Output: $3.2 per million tokens

This is significantly lower than Z.aiโ€™s direct rates (~$1.4 / $4.4) and a fraction of equivalent Western frontier models.

FAQ

Cennik dla GLM 5.1

Poznaj konkurencyjne ceny dla GLM 5.1, zaprojektowane tak, aby pasowaล‚y do rรณลผnych budลผetรณw i potrzeb uลผytkowania. Nasze elastyczne plany zapewniajฤ…, ลผe pล‚acisz tylko za to, czego uลผywasz, co uล‚atwia skalowanie w miarฤ™ wzrostu Twoich wymagaล„. Odkryj, jak GLM 5.1 moลผe ulepszyฤ‡ Twoje projekty przy jednoczesnym utrzymaniu kosztรณw na rozsฤ…dnym poziomie.

Comet Price (USD / M Tokens)Official Price (USD / M Tokens)Discount
Wejล›cie:$1.12/M
Wyjล›cie:$3.528/M
Wejล›cie:$1.4/M
Wyjล›cie:$4.41/M
-20%

Przykล‚adowy kod i API dla GLM 5.1

Uzyskaj dostฤ™p do kompleksowego przykล‚adowego kodu i zasobรณw API dla GLM 5.1, aby usprawniฤ‡ proces integracji. Nasza szczegรณล‚owa dokumentacja zapewnia wskazรณwki krok po kroku, pomagajฤ…c wykorzystaฤ‡ peล‚ny potencjaล‚ GLM 5.1 w Twoich projektach.

#!/bin/bash

# Get your CometAPI key from https://www.cometapi.com/console/token
# Export it as: export COMETAPI_KEY="your-key-here"

response=$(curl -s https://api.cometapi.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $COMETAPI_KEY" \
  -d '{
    "model": "glm-5.1",
    "messages": [
      {
        "role": "user",
        "content": "Hello! Tell me a short joke."
      }
    ]
  }')

printf '%s
' "$response" | python -c 'import json, sys; print(json.load(sys.stdin)["choices"][0]["message"]["content"])'

cURL Code Example

#!/bin/bash

# Get your CometAPI key from https://www.cometapi.com/console/token
# Export it as: export COMETAPI_KEY="your-key-here"

response=$(curl -s https://api.cometapi.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $COMETAPI_KEY" \
  -d '{
    "model": "glm-5.1",
    "messages": [
      {
        "role": "user",
        "content": "Hello! Tell me a short joke."
      }
    ]
  }')

printf '%s\n' "$response" | python -c 'import json, sys; print(json.load(sys.stdin)["choices"][0]["message"]["content"])'

Python Code Example

from openai import OpenAI
import os

# Get your CometAPI key from https://www.cometapi.com/console/token
COMETAPI_KEY = os.environ.get("COMETAPI_KEY") or "<YOUR_COMETAPI_KEY>"
BASE_URL = "https://api.cometapi.com/v1"

client = OpenAI(base_url=BASE_URL, api_key=COMETAPI_KEY)

completion = client.chat.completions.create(
    model="glm-5.1",
    messages=[{"role": "user", "content": "Hello! Tell me a short joke."}],
)

print(completion.choices[0].message.content)

JavaScript Code Example

import OpenAI from "openai";

// Get your CometAPI key from https://www.cometapi.com/console/token
const COMETAPI_KEY = process.env.COMETAPI_KEY || "<YOUR_COMETAPI_KEY>";
const BASE_URL = "https://api.cometapi.com/v1";

const client = new OpenAI({
  apiKey: COMETAPI_KEY,
  baseURL: BASE_URL,
});

const completion = await client.chat.completions.create({
  model: "glm-5.1",
  messages: [{ role: "user", content: "Hello! Tell me a short joke." }],
});

console.log(completion.choices[0].message.content);

Uptime

Wskaลบnik sukcesu ลผฤ…daล„ z ostatnich 30 dni, odzwierciedlajฤ…cy niezawodnoล›ฤ‡ kaลผdego dostawcy modelu. CometAPI monitoruje wszystkich podล‚ฤ…czonych dostawcรณw w czasie rzeczywistym przez caล‚ฤ… dobฤ™.

RespondLIVE
3363msAvg. Response
UptimeLIVE
100.0%Avg. Uptime