Capability
Unranked
field median 58.3
Not eligible for a public rank
GLM-5.3-Flash
Released Aug 26, 2026 — see all recent releases
Decision reading
GLM-5.3-Flash is tracked, but not publicly ranked yet. The profile exposes 13 sourced benchmark rows and leaves unsupported fields blank until a published record exists.
Data as of August 26, 2026 · How the score is built
Strongest published evidence
Multimodal & Grounded ranks #9. Particularly strong for screenshots, documents, charts, and grounded multimodal workflows.
Validate before choosing
13 published rows leave some tracked benchmark slots empty. No comparable first-party API token rate is published.
Decision snapshot
Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.
Price
Self-hosted; infrastructure cost varies
input median $1
No comparable first-party hosted token rate
Speed
Not measured
field median 97 tok/s
Time to first token not measured
Context
1Mtokens
field median 203,000
Maximum output length is tracked separately
How much of this is verified
Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.
- Agentic5/5 verified
- Coding3/3 verified
- ReasoningNot measured
- KnowledgeNot measured
- MathNot measured
- MultilingualNot measured
- Multimodal5/5 verified
- Inst. FollowingNot measured
Verified sourceProvisionalNot measured
Spec sheet
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
- API model ID
- glm-5.3-flashGLM-5.3-Flash model card
- Context window
- 1MGLM-5.3-Flash model card
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- Not sourced yet
- Output modalities
- Not sourced yet
- Parameters
- Not sourced yet
- Availability
- Z.AI publishes the FP8 GLM-5.3-Flash checkpoint on Hugging Face under MIT and documents local serving with SGLang, vLLM, TokenSpeed, and KTransformers. The launch post says the exact glm-5.3-flash API model is available to GLM Coding Plan users and through Z.AI API services, but the public pricing table does not yet list a standalone per-token rate for this SKU.
- Cloud regions
- Not tracked yet
- Lifecycle
- Current
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Not documented in the pricing recordGLM-5.3-Flash model card
- Self-host
- Open weights available; hardware estimate not sourced
- Rate limits
- Not tracked yet
Deployment options
Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.
Published weights are available, but BenchLM does not yet have a sourced parameter and VRAM profile for this exact model. Hardware cost estimates stay unavailable until that sizing record is complete.
Estimate VRAM from known parametersCategory score record
Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticWeight 22%5 benchmarksVerified | Score pending | Not ranked | Not available | 22% | 5 benchmarks | Verified |
| CodingWeight 20%3 benchmarksVerified | Score pending | Not ranked | Not available | 20% | 3 benchmarks | Verified |
| ReasoningWeight 17%0 benchmarksNot measured | Not measured | Not ranked | Not available | 17% | 0 benchmarks | Not measured |
| KnowledgeWeight 12%0 benchmarksNot measured | Not measured | Not ranked | Not available | 12% | 0 benchmarks | Not measured |
| MathWeight 5%0 benchmarksNot measured | Not measured | Not ranked | Not available | 5% | 0 benchmarks | Not measured |
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | Not ranked | Not available | 7% | 0 benchmarks | Not measured |
| MultimodalRank #9 of 35Percentile 76thWeight 12%5 benchmarksVerified | 80.5 | #9 of 35 | 76th | 12% | 5 benchmarks | Verified |
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | Not ranked | Not available | 5% | 0 benchmarks | Not measured |
Benchmark ledger
Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.
Coding3 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Terminal-Bench 2.1Terminal-Bench 2.1 (provider run) | Score84.3% | Versus best verified row Best verified: GLM-5.3 · 88.2% | Gap3.9 behind | WeightDisplay only | Provider exact |
| deepSwe | Score63.4% | Versus best verified row Best verified: GPT-5.6 Sol · 72.7% | Gap9.3 behind | WeightDisplay only | Provider exact |
| NL2Repo | Score56.3% | Versus best verified row Best verified: DeepSeek V4 Pro 0813 · 61.5% | Gap5.2 behind | WeightDisplay only | Provider exact |
Agentic5 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Terminal-Bench 2.1Terminal-Bench 2.1 (provider run) | Score84.3% | Versus best verified row Best verified: GLM-5.3 · 88.2% | Gap3.9 behind | WeightDisplay only | Provider exact |
| Toolathlon-Verified | Score78.4% | Versus best verified row Best verified: Claude Opus 5 · 80.6% | Gap2.2 behind | WeightDisplay only | Provider exact |
| AutomationBench | Score48.8% | Versus best verified row Best verified: GLM-5.3-Flash · 48.8% | GapBest verified | WeightDisplay only | Provider exact |
| Agents' Last Exam | Score26.3% | Versus best verified row Best verified: Qwen3.8 Max · 52.4% | Gap26.1 behind | WeightDisplay only | Provider exact |
| HLE w/ toolsHumanity's Last Exam with tools | Score55.3% | Versus best verified row Best verified: Claude Opus 5 · 64.7% | Gap9.4 behind | WeightDisplay only | Provider exact |
Multimodal5 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| OfficeQA Pro | Score62.4% | Versus best verified row Best verified: Claude Opus 5 · 66.9% | Gap4.5 behind | WeightWeighted 30% | Provider exact |
| CharXivCharXiv Reasoning | Score89.4% | Versus best verified row Best verified: Claude Mythos 5 · 93.5% | Gap4.1 behind | WeightWeighted 25% | Provider exact |
| Chartography (tools)Chartography with image and code tools | Score78.0% | Versus best verified row Best verified: Claude Opus 5 · 83.0% | Gap5 behind | WeightDisplay only | Provider exact |
| BabyVision | Score53.4% | Versus best verified row Best verified: Qwen3.8 Max · 82.0% | Gap28.6 behind | WeightDisplay only | Provider exact |
| MMVUMultimodal Multi-disciplinary Video Understanding | Score80.5% | Versus best verified row Best verified: Qwen3.8 Max · 82.4% | Gap1.9 behind | WeightDisplay only | Provider exact |
Lineage
The sequence follows explicit supersedes links. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Oct 1, 2025
GLM-4.7-FlashNot publicly ranked · Price not listed
Aug 26, 2026 · you are here
GLM-5.3-FlashNot publicly ranked · Price not listed
flash · 5.3 Flash
How to read this profile
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
We track GLM-5.3-Flash, but the public leaderboard excludes this profile until enough non-generated benchmark coverage is available. Only published rows appear above.
GLM-5.3-Flash is a open weight model with a 1M context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.
Z.AI publishes the FP8 GLM-5.3-Flash checkpoint on Hugging Face under MIT and documents local serving with SGLang, vLLM, TokenSpeed, and KTransformers. The launch post says the exact glm-5.3-flash API model is available to GLM Coding Plan users and through Z.AI API services, but the public pricing table does not yet list a standalone per-token rate for this SKU.
GLM-5.3-Flash sits in the GLM-5 family with GLM-5, GLM-5.2, GLM-5.1, GLM-5.3, GLM-5 (Reasoning), GLM-5-Turbo, GLM-5V-Turbo. Its explicit predecessor is GLM-4.7-Flash. 13 of 406 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Multimodal & Grounded at #9. particularly strong for screenshots, documents, charts, and grounded multimodal workflows.
Radar
Full release historyGLM-5.3-Flash release history
GLM-5.3-Flash released
Z.AI · Model release
Source confirmed
Frequently asked questions
How does GLM-5.3-Flash perform overall in AI benchmarks?
GLM-5.3-Flash has 13 source-displayable benchmark rows, but it does not qualify for a public overall rank. The available rows remain visible by category without being converted into a site-wide score. Missing evidence stays blank instead of being estimated from an earlier model.
Is GLM-5.3-Flash good for coding and programming?
GLM-5.3-Flash has source-displayable benchmark coverage for coding and programming, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is GLM-5.3-Flash good for agentic tool use and computer tasks?
GLM-5.3-Flash has source-displayable benchmark coverage for agentic tool use and computer tasks, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Is GLM-5.3-Flash good for multimodal and grounded tasks?
GLM-5.3-Flash ranks #9 out of 35 eligible models for multimodal and grounded tasks, with a public category score of 80.5/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.
Is GLM-5.3-Flash open source?
GLM-5.3-Flash is an open-weight model from Z.AI. Its weights can be downloaded for local or hosted deployment, subject to the published license. Open weight does not automatically mean open source: training data and training code may remain private, and commercial restrictions can still apply.
Which sibling models are related to GLM-5.3-Flash?
GLM-5.3-Flash belongs to the GLM-5 family. Related tracked variants include GLM-5, GLM-5.2, GLM-5.1, plus 4 more. A sibling link indicates shared lineage or a documented configuration relationship; it does not mean the variants have identical pricing, context limits, benchmark evidence, or deployment behavior. Compare before switching.
Does GLM-5.3-Flash have full benchmark coverage on BenchLM?
No. GLM-5.3-Flash currently has 14 source-displayable rows across 406 tracked benchmark slots. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.
What is the context window size of GLM-5.3-Flash?
GLM-5.3-Flash has a documented context window of 1M. That figure is the maximum combined prompt and retained-conversation space reported for this exact model; it is not the maximum output length. The profile keeps output limits separate because providers often publish those limits independently.
Compare GLM-5.3-Flash with every tracked model396 comparisons
Last updated August 26, 2026. Runtime fields remain blank until a sourced snapshot exists.
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