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Favicon for z-ai

Z.ai: GLM 5.3

z-ai/glm-5.3

Model weights
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GLM-5.3 is a large-scale reasoning model from Z.ai, built for complex software engineering and long-horizon agent tasks. It supports text input and output with a 1M-token context window, and improves on GLM-5.2 in coding and in the balance between performance and token efficiency.

Reasoning is always on and cannot be disabled. Reasoning efforts low, high, and max are supported; max is the default.

Modalities

In / Out Price

$0.8727 / $3.36per 1M

Context

1.3M

Released

Aug 18, 2026

Compare
ProvidersPricingPerformanceUptimeBenchmarksAppsActivityFAQExplore

Providers

Different companies host the same model. OpenRouter routes your request to one of them based on the routing mode you pick — Balanced (price + speed), Nitro (fastest), or Exacto (highest tool-calling accuracy).

Pricing

The average price customers actually pay for this model, next to the prices providers post. Caching and discounts mean the price actually paid is often well below the listed one.

Performance

Throughput is how fast the model writes (tokens per second — higher is better). Latency is total round-trip time (lower is better). TTFT is time-to-first-token — how long before you see anything appear (lower is better).

Uptime

Uptime is the percentage of the past 3 days that at least one provider was responding to requests. Availability is the percentage of time that inference was successfully served. OpenRouter continuously monitors and uses the next-best provider when one returns an error.

Benchmarks

Scores on standardized evaluations. Higher percentages are better — and rank percentile shows where this model lands among all models on OpenRouter.

Apps

Public apps that send the most traffic to this model. Good signal for what real production workloads look like — and a hint at which use cases this model is best suited for.

Activity

Token volume and request traffic to this model over time.

Quick Start

Drop-in code to call this model. OpenRouter's API is OpenAI-compatible — most SDKs work by just swapping the base URL. The only thing that changes between models is the model slug below.

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AI Model RankingsRanking
$0.8727$3.36$0.16390.68s32 tps
98.68%
$1.00$3.41$0.200.97s32 tps
98.63%
14% off
$1.17$1.007$3.96$3.41$0.234$0.20151.20s52 tps
99.39%
22% off
$1.40$1.092$4.40$3.432$0.26$0.20282.47s35 tps
99.91%
20% off
$1.40$1.12$4.40$3.52$0.26$0.2081.21s39 tps
98.10%
20% off
$1.40$1.12$4.40$3.52$0.26$0.2081.02s31 tps
99.09%
15% off
$1.40$1.19$4.40$3.74$0.23$0.19550.83s48 tps
99.48%
$1.19$4.40$0.260.42s75 tps
98.66%
$1.20$4.00$0.121.25s60 tps
97.62%
$1.257$3.951$0.23350.41s48 tps
99.80%
10% off
$1.40$1.26$4.40$3.96$0.26$0.2340.44s54 tps
99.99%
$1.35$4.40$0.230.40s76 tps
97.20%
$1.40$4.40$0.261.32s15 tps
99.71%
$1.40$4.40$0.260.39s48 tps
96.68%
$1.40$4.40$0.260.72s52 tps
99.14%
$1.40$4.40$0.260.50s44 tps
99.44%
$1.40$4.40$0.141.03s83 tps
98.27%
$1.40$4.40$0.260.94s58 tps
99.95%
$1.40$4.40$0.260.94s28 tps
99.53%
$1.40$4.40$0.261.97s14 tps
99.97%
$1.40$4.40$0.262.90s48 tps
99.79%
$1.75$5.50$0.3251.90s45 tps
99.14%
$2.10$6.60$0.210.83s89 tps
99.96%
$0.95$3.40$0.203.53s39 tps
92.59%
10% off
$1.30$1.17$4.40$3.96$0.26$0.2340.78s45 tps
98.63%
$1.40$4.40$0.2614.82s79 tps
97.63%

Throughput

89tok/s

P50, best across providers

Latency

0.39s

P50, best provider

AutoExacto Benchmarks
GPQA DiamondTAU-BenchWafer91.9%78.0%DigitalOcean90.6%78.4%Baseten86.8%79.5%Inceptron86.8%78.4%AtlasCloud86.8%78.0%Baseten86.3%77.0%
+23 more providers
Uptime (3d)The model was reachable. Request routed to a provider.

100.00%

Availability (3d)The model returned inference from any provider. Errors and empty responses count against it.

99.88%

Availability over the last 3 days

Last 72 hours
Availability 99.88%
3 Days Ago2 Days AgoYesterdayNow

Availability over the last 24 hours

OpenRouter Availability
99.90%
Without Routing
89.77%

When an error occurs in an upstream provider, we can recover by routing to another healthy provider, if your request filters allow it. You can access per-provider uptime data programmatically through the Endpoints API. Learn more about our load balancing and customization options.

1.
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549Btokens
2.
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257Btokens
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5.
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229Btokens

Frequently asked questions

GLM-5.3 is a large-scale reasoning model from Z.ai, built for complex software engineering and long-horizon agent tasks. It supports text input and output with a 1M-token context window, and improves on GLM-5.2 in coding and in the balance between performance and token efficiency. Reasoning is always on and cannot be disabled. Reasoning efforts low, high, and max are supported; max is the default.

GLM 5.3 costs $0.8727/M input tokens and $3.36/M output tokens, with separate rates for Cache Read at $0.1639/M tokens.

GLM 5.3 has a 1,310,720 token context window. It supports up to 1,048,576 completion tokens.

Yes. GLM 5.3 accepts tools and tool_choice for function calling. It supports response_format for JSON output, without JSON-schema enforcement.

GLM 5.3 is served by 25 providers on OpenRouter: Inceptron, DigitalOcean, Morph, Reka AI, NovitaAI, Phala, GMICloud, AkashML and 17 more. Requests are routed to the best available provider, with automatic failover to the others, and you can pin or exclude providers with provider routing.

GLM 5.3 was released on August 18, 2026.