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Zhipu

GLM-5.3 benchmarks & scores

Zhipu Open weights Released Aug 2026 Official website
66.2
Vibe Coding Index · #4 of 115

Independent GLM-5.3 AI coding benchmark results Intelligence 60, Coding 75, Agentic 59, with a Vibe Coding Index of 66.2. Compare its overall rank, token price, context window, and practical agentic workflow strengths below.

Blended price #94/127
$2.15
$/M tokens · 3 to 1 in, out
Context
1M
Window size

Evidence confidence

Medium confidence

100% core coverage

Complete core scores supported by one current verified source.

3/3
Core scores
1
Evidence sources
Aug 19
Last measured
Artificial analysis →

Catalog capabilities

What the model supports

1M context
Include reasoning Max tokens Reasoning Reasoning effort Response format Temperature Tool choice Tools Top k Top p
Input
Text
Output
Text
Knowledge cutoff
Not listed
Cache read price
$0.26 per million tokens

Suite radar

Intelligence Coding Agentic

Suite scores

Intelligence #5/115
General reasoning & knowledge (Intelligence Index)
59.5
Coding #9/141
Code generation & software tasks (Coding Index)
74.8
Agentic #2/116
Multi-step tool use & agentic workflows (Agentic Index)
59.1

Source record

Source. Artificial Analysis (artificialanalysis.ai) via OpenRouter (openrouter.ai/rankings).

Artificial Analysis via OpenRouter OpenRouter model card

TheVibeFather rankings

GLM-5.3 practical agentic coding scorecard

This is our algorithmic assessment of where GLM-5.3 ranks for common vibe coding and agentic engineering workflows. Every stable 0–10 score is calculated consistently from the sourced Intelligence, Coding, and Agentic signals above—never from an unsourced opinion score.

Overall VibeFather rating
6.6 /10
#4 of 115 models
Practical area

Small, well-defined code changes

Precision on scoped edits, fixes, and implementation tasks.

Strong 7.0/10
Field rank #7 / 115

UI and CSS iteration

Front-end implementation with iterative tool-driven refinement.

Strong 7.2/10
Field rank #6 / 116

Routine debugging

Diagnosing failures and turning reasoning into correct code changes.

Strong 6.6/10
Field rank #6 / 115

Repository-wide refactors

Coordinating larger edits across files while preserving intent.

Strong 6.6/10
Field rank #4 / 115

Architecture decisions

Reasoning through tradeoffs, constraints, and system-level choices.

Capable 5.9/10
Field rank #4 / 115

Tool use and workflow execution

Planning and completing multi-step work with tools and feedback loops.

Strong 6.3/10
Field rank #3 / 116

Long autonomous coding tasks

Sustaining coherent progress across longer agentic engineering runs.

Capable 5.9/10
Field rank #2 / 115

Overall VibeFather rating

Our complete Vibe Coding Index, expressed on the same 0–10 practical scale.

Strong 6.6/10
Field rank #4 / 115
1 · Sourced signals

We start with Intelligence, Coding, Agentic benchmark evidence, and preserve missing values as unverified.

2 · Practical lenses

Our code-controlled algorithm blends the native 0–100 signals by workflow and expresses the result on a stable 0–10 scale. Every required input must be present.

3 · Field ranking

Each workflow score is ranked against every model with comparable evidence, so positions update when the benchmark field changes.

The Vibe Coding Index is TheVibeFather’s code-controlled 0–100 composite for practical coding and agentic capability. Price and adoption are reported independently and never alter quality. Exact weighting remains proprietary, inputs, missing-data behavior, and per-category ranks are disclosed here. Read the benchmark methodology →

Recorded score history

How GLM-5.3 has moved

All benchmark history →
69.0 66.5 64.0
Aug 19, 2026 10 AM CT
66.2 rank 4

No material score or rank change.

Aug 19, 2026 9 AM CT
66.2 rank 4

No material score or rank change.

Aug 19, 2026 8 AM CT
66.2 rank 4

Baseline snapshot recorded.

Where GLM-5.3 sits

Its bar stays full-color on each index while the rest of the field recedes. The price scatter below keeps the same highlight.

Intelligence

Artificial Analysis Intelligence Index · Higher is better

63.1 Claude Opus 5 Claude Opus 5 Anthropic #1 of 115 · Intelligence 63.1 Intelligence 63.1 Coding 78 Agentic 59.2 VCI 68.4 62.1 Claude Fable 5 Claude Fable 5 Anthropic #2 of 115 · Intelligence 62.1 Intelligence 62.1 Coding 76.5 Agentic 56.6 VCI 66.7 60.9 Grok 4.6 Grok 4.6 xAI #3 of 115 · Intelligence 60.9 Intelligence 60.9 Coding 76.8 Agentic 58.7 VCI 67.3 59.7 Kimi K3 Kimi K3 Moonshot #4 of 115 · Intelligence 59.7 Intelligence 59.7 Coding 76.2 Agentic 54.3 VCI 65.2 59.5 GLM-5.3 GLM-5.3 Zhipu #5 of 115 · Intelligence 59.5 Intelligence 59.5 Coding 74.8 Agentic 59.1 VCI 66.2 59 GPT-5.6 Sol GPT-5.6 Sol OpenAI #6 of 115 · Intelligence 59 Intelligence 59 Coding 78.3 Agentic 53.6 VCI 65.8 58.1 Qwen3.8 Max Qwen3.8 Max Alibaba #7 of 115 · Intelligence 58.1 Intelligence 58.1 Coding 71.8 Agentic 58.4 VCI 64.4 57.7 Qwen3.8 2.4T A95B Qwen3.8 2.4T A95B Alibaba #8 of 115 · Intelligence 57.7 Intelligence 57.7 Coding 71.9 Agentic 57.1 VCI 63.9 57.3 Claude Opus 4.8 Claude Opus 4.8 Anthropic #9 of 115 · Intelligence 57.3 Intelligence 57.3 Coding 74.3 Agentic 49.4 VCI 62.2 57 Muse Spark 1.2 Muse Spark 1.2 Meta #10 of 115 · Intelligence 57 Intelligence 57 Coding 71.8 Agentic 48.4 VCI 60.7 56.8 Muse Spark 1.2 Muse Spark 1.2 Meta #11 of 115 · Intelligence 56.8 Intelligence 56.8 Coding 72.2 Agentic 49.3 VCI 61.1 56.6 GPT-5.6 Terra GPT-5.6 Terra OpenAI #12 of 115 · Intelligence 56.6 Intelligence 56.6 Coding 76.7 Agentic 50.2 VCI 63.4 56.3 GPT-5.5 GPT-5.5 OpenAI #13 of 115 · Intelligence 56.3 Intelligence 56.3 Coding 74.9 Agentic 47.4 VCI 61.6 56 Gemini 3.7 Flash Gemini 3.7 Flash Google #14 of 115 · Intelligence 56 Intelligence 56 Coding 76.1 Agentic 45.1 VCI 61.2 55.8 Grok 4.5 Grok 4.5 xAI #15 of 115 · Intelligence 55.8 Intelligence 55.8 Coding 72.4 Agentic 48.9 VCI 60.9 55.3 Claude Sonnet 5 Claude Sonnet 5 Anthropic #16 of 115 · Intelligence 55.3 Intelligence 55.3 Coding 71.5 Agentic 49.7 VCI 60.6 55 Claude Opus 4.7 Claude Opus 4.7 Anthropic #17 of 115 · Intelligence 55 Intelligence 55 Coding 73.6 Agentic 46.3 VCI 60.3 53.2 DeepSeek V4 Pro 0813 DeepSeek V4 Pro 0813 DeepSeek #18 of 115 · Intelligence 53.2 Intelligence 53.2 Coding 68.8 Agentic 49.6 VCI 59 53.2 Muse Spark 1.1 Muse Spark 1.1 Meta #19 of 115 · Intelligence 53.2 Intelligence 53.2 Coding 71.3 Agentic 39.7 VCI 56.6 53.1 GPT-5.4 GPT-5.4 OpenAI #20 of 115 · Intelligence 53.1 Intelligence 53.1 Coding 71.1 Agentic 44.2 VCI 58.1 52.6 GLM-5.2 GLM-5.2 Zhipu #21 of 115 · Intelligence 52.6 Intelligence 52.6 Coding 68.8 Agentic 45.7 VCI 57.5 52.3 GPT-5.6 Luna GPT-5.6 Luna OpenAI #22 of 115 · Intelligence 52.3 Intelligence 52.3 Coding 71.4 Agentic 46.9 VCI 59 52 Qwen3.8 27B Qwen3.8 27B Alibaba #23 of 115 · Intelligence 52 Intelligence 52 Coding 68.1 Agentic 50.9 VCI 58.9 52 Gemini 3.5 Flash Gemini 3.5 Flash Google #24 of 115 · Intelligence 52 Intelligence 52 Coding 70.1 Agentic 39.7 VCI 55.8 51.8 DeepSeek V4 Flash 0731 DeepSeek V4 Flash 0731 DeepSeek #25 of 115 · Intelligence 51.8 Intelligence 51.8 Coding 69.1 Agentic 48.4 VCI 58.4 51.6 Gemini 3.6 Flash Gemini 3.6 Flash Google #26 of 115 · Intelligence 51.6 Intelligence 51.6 Coding 69.2 Agentic 40.5 VCI 55.6 48.4 Claude Sonnet 4.6 Claude Sonnet 4.6 Anthropic #27 of 115 · Intelligence 48.4 Intelligence 48.4 Coding 63 Agentic 42.1 VCI 52.8 47.7 Gemini 3.1 Pro Preview Gemini 3.1 Pro Preview Google #28 of 115 · Intelligence 47.7 Intelligence 47.7 Coding 68.8 Agentic 23 VCI 48.6
Reasoning models are marked with a lightbulb Full board →
↖ Best value Premium ↗ ↙ Budget Poor value ↘ 0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 $0.01 $0.03 $0.1 $0.32 $1 $3.16 $10 $31.62 BLENDED COST — $ / 1M TOKENS (LOG) VIBE CODING INDEX #1 Claude Opus 5 #2 Grok 4.6 GLM-5.3 Gemini 3.7 Flash GPT-5.6 Luna DeepSeek V4 Flash Solar Pro 4 Ling-3.0-flash #81 North Mini Code Nemotron 3.5 Lightning
Efficient frontier Dashed guides = field medians 35 model(s) hidden — data not yet verified
Vendor key (25)
Alibaba Anthropic Arcee Ai Cohere DeepSeek Google Inception Inclusionai Kwaipilot Meituan Meta Meta Llama MiniMax Mistral Moonshot NVIDIA Nex Agi OpenAI Stepfun Tencent Thinkingmachines Upstage Xiaomi Zhipu xAI

Model benchmark FAQ

GLM-5.3 for vibe coding and agentic engineering

Answers update from this model’s current sourced scores, practical rankings, and verified pricing.

What is GLM-5.3's Vibe Coding Index?

GLM-5.3 has a Vibe Coding Index of 66.2/100 and is #4 of 115 in the current field. The index is TheVibeFather's stable composite for practical AI coding, combining independently sourced Intelligence, Coding, and Agentic benchmark signals. Price and adoption are compared separately and never inflate the quality score.

How does GLM-5.3 rank for vibe coding?

For vibe coding, GLM-5.3's strongest practical area is UI and CSS iteration at 7.2/10, ranking #6 of 116 models in TheVibeFather rankings.

Is GLM-5.3 good for agentic coding and autonomous tasks?

GLM-5.3 scores 6.3/10 for tool use and workflow execution and 5.9/10 for long autonomous coding tasks. Those categories emphasize the Agentic benchmark signal used for multi-step planning, tool calls, edits, tests, and feedback loops.

What coding benchmark scores does GLM-5.3 have?

The current sourced benchmark profile for GLM-5.3 is Intelligence 60/100, Coding 75/100, Agentic 59/100. TheVibeFather converts those 0–100 signals into consistent practical 0–10 workflow scores so models can be compared for real agentic engineering work.

How much does GLM-5.3 cost for agentic engineering?

The current benchmark uses a 3 to 1 input-to-output blend of $2.15 per million blended tokens. That places it #94 of 127 by price, where a lower rank number means less expensive.

Are vibe coding, agentic coding, and agentic engineering the same?

They describe overlapping AI-assisted software workflows. Vibe coding emphasizes directing software through intent and iteration, agentic coding emphasizes a model planning and executing multi-step work with tools, agentic engineering is the broader discipline of designing, supervising, and validating those workflows. TheVibeFather benchmarks the shared capabilities behind all three terms on every model page, including GLM-5.3.

Compare GLM-5.3 → Back to leaderboard