GLM 5.3 Flash

Z.ai chat

GLM 5.3 Flash is a Z.ai chat model.It supports a 1,048,576-token context windowwith up to 128,000 output tokens.Input is priced at $0.150/M tokens and output at $0.500/M tokens. Capabilities include function calling, vision, reasoning, prompt caching. Route GLM 5.3 Flash via Future AGI's Agent Command Center for unified observability, caching, and 15 routing strategies including cost-optimized fallback.

Pricing source: litellm Last verified: Oct 22, 2026 View source ↗
Cost calculator

Estimate GLM 5.3 Flash spend

Pick a workload, fine-tune the sliders, and see the monthly bill.

~3K in / ~400 out · 5K req/day
3,000
01,048,576
400
0128,000
5,000
01,000,000
cached @ $0.0300/M
Per request
$0.000650
in $0.000450 · out $0.000200
Per day
$3.25
5,000 requests
Per month
$98.92
152,188 requests

Estimate uses $0.1500/M input · $0.5000/M output. Provider pricing changes. Production costs vary with retries, streaming overhead, and tool-call rounds.
Want this for free? Cache + route via Agent Command Center — first 100K requests and 100K cache hits free every month.

Pricing

Per-token rates, expressed in USD per 1M tokens. Verified Oct 22, 2026.

Input $0.150/M
Output $0.500/M
Blended (3:1 in:out) $0.238/M
Cross-model comparable price
Cached input $0.0300/M

Context & limits

Context window
1,048,576 tokens
Max input
1,048,576 tokens
Max output
128,000 tokens
Modalities
vision, text

Capabilities

  • Function calling ✓ supported
  • Parallel tool calls — not advertised
  • Vision input ✓ supported
  • Audio input — not advertised
  • Audio output — not advertised
  • PDF input — not advertised
  • Streaming ✓ supported
  • Structured output — not advertised
  • Prompt caching ✓ supported
  • Reasoning ✓ supported

Strengths & caveats — when to pick GLM 5.3 Flash

Data-driven from GLM 5.3 Flash's percentile within chat peers.

Where it's strong

  • +long-context tasks — context window in the top 2% of peers

Watch out for

  • !strict structured output — no JSON-schema enforcement, expect retry loops

Benchmark scores

Reported public benchmark numbers. Each row links to the source. Faded bar shows 6-peer average for context.

Captured Oct 20, 2026
Captured Oct 19, 2026
Captured Oct 20, 2026
Captured Oct 19, 2026
Try it

Call GLM 5.3 Flash via Agent Command Center

One OpenAI-compatible endpoint. Routing, fallback, semantic caching, guardrails, and cost tracking come along for the ride. First 100K requests + 100K cache hits free every month.

SDK
Native Future AGI client (agentcc / @agentcc/client). Per-call metadata — provider, cost, latency, cache hit, request id — is returned on x-agentcc-* response headers, so any HTTP client can read it.
# GLM 5.3 Flash via the Agent Command Center Python SDK
# pip install agentcc
import os
from agentcc import AgentCC

client = AgentCC(
    api_key=os.environ["AGENTCC_API_KEY"],   # from app.futureagi.com → Settings → API Keys
    base_url="https://gateway.futureagi.com/v1",
)

resp = client.chat.completions.create(
    model="zai/glm-5-3-flash",
    messages=[{"role": "user", "content": "Hello, GLM 5.3 Flash!"}],
)

print(resp.choices[0].message.content)
print(f"Tokens: {resp.usage.total_tokens}")

# Per-call gateway metadata is returned on x-agentcc-* response headers.
# When you need it programmatically, use .with_raw_response to get them:
raw = client.chat.completions.with_raw_response.create(
    model="zai/glm-5-3-flash",
    messages=[{"role": "user", "content": "Same call, but I want the headers."}],
)
print("Provider:", raw.headers.get("x-agentcc-provider"))
print("Latency:", raw.headers.get("x-agentcc-latency-ms"), "ms")
print("Cost:   ", raw.headers.get("x-agentcc-cost"), "USD")
print("Cache:  ", raw.headers.get("x-agentcc-cache"))
Set AGENTCC_API_KEY with a key fromapp.futureagi.com.Gateway docs ↗
Advanced: fallback + cache config (YAML) ▸
strategy: cost-optimized
targets:
  - model: glm-5-3-flash
    provider: zai
    weight: 80
fallbacks:
  - model: gemini-4-argon
    provider: google
  - model: claude-opus-5-5
    provider: azure-ai-foundry
guardrails: [pii, prompt-injection, secrets]
cache: { exact: true, semantic: true }

Explore similar models

Grouped by Chatbot Arena tier (GLM 5.3 Flash sits at 1475 ELO). Side-by-side links appear where a comparison page exists; otherwise, open the model profile.

FAQ

How much does GLM 5.3 Flash cost?

Input is priced at $0.150 per 1M tokens and output at $0.500 per 1M tokens (Z.ai, last verified Oct 22, 2026).

What is the context window of GLM 5.3 Flash?

GLM 5.3 Flash supports a 1,048,576-token context window with up to 128,000 output tokens.

Does GLM 5.3 Flash support function calling?

Yes — GLM 5.3 Flash supports function (tool) calling.

Is GLM 5.3 Flash good for production?

GLM 5.3 Flash is well-suited for long-context tasks — context window in the top 2% of peers. Consider alternatives if you need strict structured output — no JSON-schema enforcement, expect retry loops.

How can I route to GLM 5.3 Flash with fallback?

Use Agent Command Center: a single OpenAI-compatible endpoint that supports cost-optimized routing, latency-aware retries, model fallback, and shadow traffic. Configure once, swap models without app changes.

Useful links for GLM 5.3 Flash

Official sources, independent benchmarks, and pricing aggregators — no random search-engine guesses.