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Claude Opus 4.6 vs GLM 5.3 Flash

Compare Claude Opus 4.6 and GLM 5.3 Flash side-by-side. See how these vision models stack up in Open Prompt, OCR, Object Detection, Classification, and Image Captioning.

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AnthropicClaude Opus 4.6
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Z.aiGLM 5.3 Flash
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Models in this comparison

Claude Opus 4.6 vs GLM 5.3 Flash Comparison Table

Evals updated August 26, 2026Pricing updated August 26, 2026

PropertyClaude Opus 4.6 GLM 5.3 Flash
OrganizationAnthropicZ.ai
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateFeb 2026Aug 2026
Context Window1.0M1.0M
Parameters320B total, 18B active
LicenseProprietaryMIT
Pricing per 1M tokens
Input $/1M$5.00
Output $/1M$25.00
Vision Tasks
CaptioningDemoDemo
Chart Question Answering
ClassificationDemoDemo
Document Question Answering
Image Tagging
Multi-Label Classification
Object DetectionDemoDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort
OverallNot evaluated
66.3%
Avg cost / sample$0.0002
Avg speed / sample6.78s
By task
Object Detection
33.1%
$0.0004
Counting
55.4%
$0.0001
Identification
84.4%
$0.0001
OCR
90.6%
$0.0002
Data Extraction
83.5%
$0.0001
Reasoning (low)
51.0%
$0.0001
Reasoning (high)
59.6%
$0.0001

Claude Opus 4.6 vs GLM 5.3 Flash: Overview

Claude Opus 4.6

Claude Opus 4.6 is the flagship large language model from Anthropic, released on 2026-02-05 for advanced reasoning, complex coding, and enterprise agent workflows. It supports text and image inputs via API, offers a 200K-token standard context window with a 1M-token beta option, and enables outputs up to 128K tokens, with adaptive reasoning and context compaction for sustained tasks.

As of 2026-02-17, Anthropic also released Claude Sonnet 4.6, extending the 1M-token context window to a broader tier. Opus remains positioned for maximum depth and benchmark performance, while Sonnet 4.6 brings long-context capability to more cost- and latency-sensitive production use cases.

GLM 5.3 Flash

GLM-5.3-Flash is the first natively multimodal model in Z.ai's GLM-5 series, a mixture-of-experts transformer with roughly 320 billion total parameters and 18 billion activated per token. It routes each token through 8 of 288 experts across 45 language layers that interleave KDA linear attention with sparse multi-head latent attention, and pairs them with a 24-layer vision encoder that handles image and video input. The checkpoint declares a maximum context length of 1,048,576 tokens, ships in native FP8, and includes a multi-token prediction draft layer for speculative decoding. Z.ai reports that the hybrid attention design reduces attention computation by 3.01x and KV cache size by 4.44x relative to GLM-5.3.

The model starts from a newly trained base built on a 30 trillion token multimodal pre-training corpus and adopts Manifold-Constrained Hyper-Connections to improve scaling efficiency. Vision is integrated into the coding and agent loop, so the model can inspect interfaces, rendered output, and images while operating across code, browsers, and graphical user interfaces. Z.ai reports scores of 84.3 on Terminal-Bench 2.1, 63.4 on DeepSWE 1.1, 55.3 on Humanity's Last Exam with tools, and 48.8 on AutomationBench, and the model exposes low, high, and max thinking modes.

Frequently Asked Questions

Claude Opus 4.6 has not yet been evaluated on Roboflow's current Vision Evals, so this comparison shows specs, licensing, and pricing rather than benchmark scores.

Claude Opus 4.6 is released under Proprietary, while GLM 5.3 Flash uses MIT. Licensing often matters more than raw accuracy for commercial deployments, so check the terms against how you plan to ship.

Yes. The comparison demo on this page runs both models on the same image side by side for open prompts and OCR in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.