Claude Opus 4.6 vs Qwen3.5 122B A10B

Compare Claude Opus 4.6 and Qwen3.5 122B A10B side-by-side. See how these vision models stack up in Open Prompt, OCR, and Image Captioning.

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AnthropicClaude Opus 4.6
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QwenQwen3.5 122B A10B
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Claude Opus 4.6 vs Qwen3.5 122B A10B: 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.

Qwen3.5 122B A10B

Qwen3.5-122B-A10B is a high-capacity multimodal Mixture-of-Experts (MoE) model developed by Alibaba’s Qwen team as part of the Qwen3.5 model family. The architecture contains 122 billion total parameters while activating roughly 10 billion per token through sparse expert routing, allowing the model to balance large-scale reasoning ability with relatively efficient inference compared to dense models of similar size.

The model is designed to process both text and visual inputs within a unified multimodal framework, enabling tasks that require reasoning across images, documents, charts, and natural language. This makes it suitable for applications such as document understanding, diagram interpretation, and complex visual question answering.

Qwen3.5-122B-A10B supports a native context window of approximately 256,000 tokens, which can be extended further through techniques such as YaRN scaling to support very long-context workloads. Released under the Apache 2.0 license, it builds on earlier Qwen multimodal systems and provides developers with an open-weight model capable of handling demanding multimodal reasoning and analysis tasks.

Claude Opus 4.6 vs Qwen3.5 122B A10B Comparison Table

PropertyClaude Opus 4.6 Qwen3.5 122B A10B
OrganizationAnthropicQwen
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateFeb 2026Feb 2026
Context Window1.0M256K
Parameters122B
LicenseProprietaryApache 2.0
Pricing per 1M tokens
Input $/1M$5.00$0.260
Output $/1M$25.00$2.08
Vision Tasks
CaptioningDemoDemo
Object DetectionDemo
OCRDemoDemo
Vision Language
Visual Question AnsweringDemoDemo
ClassificationDemo
Model Features
LLMs with Vision Capabilities
Multimodal Vision
Foundation Vision
Vision Evalspass/fail results · 67 prompts
Score key:≥75%40–74%<40%
Visual Understanding
Overall Score
64.18%
76.12%
Avg Response Time23.35s1.77s
Median input tokensincl. image tokens2.2K1.2K
Median output tokens1307
Est. cost / taskon this benchmark$0.014$0.0003
Defect Detection
73.3%(11/15)
86.7%(13/15)
Document Understanding
77.8%(7/9)
77.8%(7/9)
Object Counting
20%(2/10)
40%(4/10)
Object Understanding
71.4%(10/14)
92.9%(13/14)
Spatial Understanding
68.4%(13/19)
73.7%(14/19)
OCR
Overall Score
82.53%
Avg Response Time5.05s
Median input tokensincl. image tokens736
Median output tokens99
Est. cost / taskon this benchmark$0.0062
Focused Scene OCR
85.9%(85/99)
Handwritten Math
70%(7/10)
License Plate Recognition
90%(27/30)
Text Recognition
80%(24/30)
VQA & Extraction
76.7%(46/60)

Output tokens (incl. reasoning) and est. cost / task are measured on this benchmark from a single low-temperature run, and shown only for models whose run covered at least 90% of prompts. Methodology