GLM 5.3 Fast

GLM 5.3 Fast is presented as a speed-optimized counterpart to Z.AI's GLM-5.3, with an emphasis on responsive, real-time interaction rather than maximum depth per request. A third-party listing describes it as an agentic coding model built to stay quick under live workloads, while still inheriting the broader GLM-5.3 family's orientation toward software engineering tasks. The variant framing suggests it is meant for interactive assistants, code editors, and other developer tools where latency matters as much as raw capability.

For practical use, the variant targets demanding coding scenarios such as advanced code generation, long-horizon task execution, automated testing, vulnerability discovery, and cybersecurity analysis. These focus areas position it well for coding agents and developer-facing applications that need to keep multiple steps of reasoning and tool use snappy in production. Independent catalog metadata also indicates a very large context window alongside an unusually high output token ceiling, which suits multi-file refactors, extended debugging sessions, and long agent loops without forcing aggressive truncation.

Basetenzai-org/GLM-5.3-Fastglm

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Quick Info

Provider: Baseten
Model key: zai-org/GLM-5.3-Fast
Release date: Aug 14, 2026
Last updated: Aug 14, 2026
Input modalities
Output modalities
Capabilities

Cost

Input token cost: $2.10
Output token cost: $6.60

Limits

Output tokens: 262,144 tokens
Context window: 1,048,576 tokens

Transparent token rates

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Rates are shown per one million tokens. Combined means one million input plus one million output tokens.

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Latest news about GLM 5.3 Fast

Baseten

Coverage

AINews’ Aug. 24, 2026 roundup lists “glm-5.3” among its model tags, but the supplied excerpt does not identify the exact “zai-org/GLM-5.3-Fast” variant or describe a release, update, benchmark, API capability, or other model-level development. It also does not provide Baseten-specific technical evidence about serving t The excerpt instead focuses on Stanford’s AI-native software-engineering curriculum, its first-principles AI-agents course, and discussion of dynamic intelligence allocation. Because the GLM mention is only a tag without substantive model-family or exact-variant details, the item is not technically useful or actionable

Baseten

Coverage

This AINews-derived page centers on Muse Spark 1.3, describing it as a leading model, comparing its reported performance with GPT-5.6-Sol, noting a promised open-weights release, and presenting a training opt-in pricing model. The excerpt also summarizes Stanford agent-engineering course changes. Although the page’s surrounding issue material may include a “glm-5.3” tag, the supplied evidence contains no substantive discussion of the GLM 5.3 model family, no exact mention of zai-org/GLM-5.3-Fast, and no Baseten-specific technical development. Its featured model is a different entity, so it cannot support an acc

Baseten

Coverage

The supplied Latent.Space feed snapshot lists a Sept. 7, 2026 post about Grok Bot and an earlier item discussing OpenClaw 2.0, including browser-based plugin setup and Quick Start reuse of Claude Code or Codex logins. These excerpts describe setup and workflow features in other products. There is no mention of GLM 5.3 Fast, the zai-org model family, or Baseten in the supplied feed evidence, and the visible content provides no release, benchmark, API, or developer-tool update applicable to the subject model. The candidate is therefore unrelated.

Baseten

Coverage

Blackbox’s page markets a gateway that routes requests across more than 300 open and closed models through one OpenAI-compatible endpoint. It claims zero data retention and denied training, along with automatic failover, load balancing, streaming, function calling, JSON mode, and vision support across compatible models The supplied excerpt does not mention GLM 5.3 Fast, Z.ai, or Baseten, and it concerns third-party routing, retention, compatibility, and serving rather than an announcement or technical development for the subject model. Such gateway and inference-provider marketing is out of scope for this model-focused judgment.