GLM-5.3 is a Z.ai open-weight frontier model. CompareLLM Coding Reported rating is 1552. Active context window extends to 1M tokens. Commercial API token pricing is listed at $1.4/1M tok input and $4.4/1M tok output per 1M tokens. Z.ai's open-weight reasoning model for complex software engineering and long-horizon agent work. Numbers below are dated snapshots from empirical benchmark harnesses.
Independent evaluation answering: "Is GLM-5.3 the right model for your workload & budget?"
Open weights still need local hardware; this card does not estimate VRAM.
Dated snapshot metrics aggregated from official evaluators and API providers with visual relative score bars.
Our category lists (Coding, Reasoning, Chat, Agents). Named suites such as SWE-bench Pro are recipe inputs, not this rating.
LMArena, SWE-bench Pro, LiveBench and similar suites appear with a source and as-of date. They are not CompareLLM's rating.
How much of the recipe is present. Missing inputs stay missing; they are never filled with 0 or 50.
Compact streaming class. Exact tok/s stays in the fact sheet, not in compact cells.
Compact class for time-to-first-token. Exact milliseconds stay in the fact sheet.
Commercial API price per 1 Million prompt/output tokens (~750k words).
| Benchmark Metric & Meaning | Reported Score & Capability Fill | CompareLLM Review |
|---|---|---|
Maximum output (tokens) Maximum Response Length | 131k tokens | Source not recorded · Sep 15, 2026Maximum completion tokens for one request on the model author's own endpoint. |
Context window (tokens) Context Window Capacity (tokens) | 1M tokens | Source not recorded · Sep 15, 2026Maximum input context on the model author's own endpoint. |
Input token price Cost to Prompt (Input tokens) | $1.4/1M tok | Source not recorded · Sep 15, 2026Published list input price on the model author's own endpoint. |
Cached input token price Cost to Reuse Cached Input | $0.26/1M tok | Source not recorded · Sep 15, 2026Published cache-read price on the model author's own endpoint. |
Output token price Cost to Generate (Output tokens) | $4.4/1M tok | Source not recorded · Sep 15, 2026Published list output price on the model author's own endpoint. |
Generation speed (tok/s) Writing Speed (tok/s) | <50 tok/s | Source not recorded · Sep 15, 2026 |
Time to first token Waiting Time (before it replies) | 2s+ | Source not recorded · Sep 15, 2026 |
Peers in the same open-weight mid performance tier — not a jump to an unrelated frontier SKU.
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Compare GLM-5.3 against
Test your GPU VRAM, Apple Mac Mini / Studio, or Cloud Cluster across FP16, Q8, Q5, and Q4 quantization tiers with live KV cache calculations.
Models may use different benchmarks and test settings. This is an indicative composite, not a controlled head-to-head comparison or community Elo. Admin-approved sentiment estimates fill categories without accepted benchmark results. Estimates are labelled and do not increase benchmark coverage. Coverage refers to the configured recipe, not confidence.
Release recent-models-2026-09-23-r1 · recipe reported-text-2026-09-11-r1 · method reported-with-estimates-v2 · research through 2026-09-23
Overall benchmark coverage includes missing applicable categories. Estimated categories contribute to the rating but add no benchmark coverage.
Z.ai (vendor-reported) · reported 2026-08-18
Config: Z.ai's own launch table, which reports DeepSWE v1.1 rising from 46.2 on GLM-5.2 to 66.9. Vendor-reported and not independently re-run. · Effort: reported_best
Admin-authored relevance policy, not empirical difficulty calibration. Repository-level work receives the largest share for coding relevance.
Terminal-Bench (third-party report) · reported 2026-09-02
Config: Official tbench.ai Terminal-Bench 4.0 run, not the vendor's own 3.0 figure of 28.3. · Effort: reported_best
Admin-authored relevance policy, not empirical difficulty calibration. Complement repository work with terminal-based tasks.
Missing benchmark families: frontiercode.
Editorial estimate, anchored to the Artificial Analysis Intelligence Index v4.3, on which GLM-5.3 (max) scores 45, and placed mid-range, because this category has too few measured results to define a band. AA's index is a composite of ten evaluations and is not this category's recipe, so this is an ordering anchor rather than a measurement. Any accepted result that clears the evidence thresholds replaces it.
As of 2026-09-23 · review on 2026-12-23 · Editorial estimate (not a benchmark result)
Sentiment source 1 →Missing benchmark families: graduate-science, advanced-mathematics, broad-academic, interactive-abstraction.
Editorial estimate, anchored to the Artificial Analysis Intelligence Index v4.3, on which GLM-5.3 (max) scores 45, and placed mid-range, because this category has too few measured results to define a band. AA's index is a composite of ten evaluations and is not this category's recipe, so this is an ordering anchor rather than a measurement. Any accepted result that clears the evidence thresholds replaces it.
As of 2026-09-23 · review on 2026-12-23 · Editorial estimate (not a benchmark result)
Sentiment source 1 →Missing benchmark families: constrained-story-writing, instruction-compliance.
Editorial estimate, anchored to the Artificial Analysis Intelligence Index v4.3, on which GLM-5.3 (max) scores 45, and placed within the 59-66 band this catalog's measured results occupy for this category. AA's index is a composite of ten evaluations and is not this category's recipe, so this is an ordering anchor rather than a measurement. Any accepted result that clears the evidence thresholds replaces it.
As of 2026-09-23 · review on 2026-12-23 · Editorial estimate (not a benchmark result)
Sentiment source 1 →Missing benchmark families: professional-computer-tasks, desktop-use, workflow-automation, web-research.
Editorial estimate, anchored to the Artificial Analysis Intelligence Index v4.3, on which GLM-5.3 (max) scores 45, and placed mid-range, because this category has too few measured results to define a band. AA's index is a composite of ten evaluations and is not this category's recipe, so this is an ordering anchor rather than a measurement. Any accepted result that clears the evidence thresholds replaces it.
As of 2026-09-23 · review on 2026-12-23 · Editorial estimate (not a benchmark result)
Sentiment source 1 →Missing benchmark families: conversation-quality, support-task-completion, instruction-compliance.
What this model is available as, what it takes to run, and where its identity comes from.
The weights are published for download, so this model can be run on your own hardware.
Published weights — the provider's own download page.
glm-5.3z-ai/glm-5.3Concise empirical overview formatted for citations and prompt context
Claude Opus 4.8 and GLM-5.3 Flash both score 42 on the Artificial Analysis Intelligence Index. They were released 91 days apart. One bills $25.00 per million output tokens and the other bills $0.50.
Two frontier-class models shipped downloadable weights this month at 753B and 552B parameters. Both are genuinely open; neither fits on a consumer GPU. The real numbers.
Plain-English methodology and leaderboard answers
Elo is a crowd vote on which hidden answer people liked more — not a school test. What is preference Elo? · Methodology
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