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Claude Opus 4.6 vs Qwen3.8 27B

Compare Claude Opus 4.6 and Qwen3.8 27B side-by-side.

Compare Claude Opus 4.6 vs Qwen3.8 27B live

Run the same image across every model that supports a task and compare their outputs side-by-side.

These models don't share enough common tasks for a side-by-side demo. See the comparison table below for their capabilities.

Models in this comparison

Claude Opus 4.6 vs Qwen3.8 27B Comparison Table

Evals updated August 14, 2026Pricing updated August 15, 2026

PropertyClaude Opus 4.6 Qwen3.8 27B
OrganizationAnthropicQwen
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateFeb 2026Aug 2026
Context Window1.0M262K
Parameters27.78B
LicenseProprietaryApache 2.0
Pricing per 1M tokens
Input $/1M$5.00$0.450
Output $/1M$25.00$3.20
Vision Tasks
CaptioningDemo
Chart Question Answering
ClassificationDemo
Document Question Answering
Image Tagging
Multi-Label Classification
OCRDemo
Vision Language
Visual Question AnsweringDemo
Object DetectionDemo
Model Features
Foundation Vision
LLMs with Vision Capabilities
Multimodal Vision
Vision Evalsground-truth scores across 6 vision tasks, pooled at low effort
OverallNot evaluated
61.2%
Avg cost / sample$0.0018
Avg speed / sample7.33s
By task
Object Detection
54.5%
$0.0036
Counting
41.9%
$0.0005
Identification
78.1%
$0.0005
OCR
81.4%
$0.0019
Data Extraction
79.4%
$0.0005
Reasoning (low)
31.8%
$0.0005
Reasoning (high)
62.3%
$0.0087

Claude Opus 4.6 vs Qwen3.8 27B: 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.

Qwen3.8 27B

Qwen3.8-27B is a dense vision-language model of roughly 27.78 billion parameters from Alibaba's Qwen team, built on the architectural foundation established by the Qwen3.5 generation. It takes interleaved text, image, and video input through an integrated vision encoder and produces text, covering document and chart understanding, visual question answering, front-end code generation from visual references, and agentic computer-use workflows. The decoder is a hybrid stack of 64 layers that repeats a pattern of three Gated DeltaNet linear-attention blocks, each followed by a feed-forward block, then one grouped-query full-attention block, so only a quarter of the layers maintain a conventional key-value cache. Native context length is 262,144 tokens.

Post-training targets long-horizon agentic work, and the model exposes per-request thinking control that lets callers switch reasoning traces on or off and choose a reasoning effort level. Multi-token prediction weights are trained alongside the main network for speculative decoding. Qwen reports improvements over Qwen3.6-27B on agentic and multimodal evaluations including Terminal-Bench 2.1, OSWorld-Verified, and SWE-bench Multimodal, with additional results on MathVision, CharXiv, and an internal Vision2Web suite.

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 Qwen3.8 27B uses Apache 2.0. Licensing often matters more than raw accuracy for commercial deployments, so check the terms against how you plan to ship.