Roboflow

Claude Sonnet 4.6 vs MiMo V2.6 Pro

Compare Claude Sonnet 4.6 and MiMo V2.6 Pro side-by-side. See how these vision models stack up in Image Captioning, Classification, Open Prompt, Object Detection, and OCR.

Compare Claude Sonnet 4.6 vs MiMo V2.6 Pro live

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

Detect and compare bounding boxes across models on the same image.

Open Object Detection in the full playground
AnthropicClaude Sonnet 4.6
Run to compare this model.
MiMo V2.6 Pro
Run to compare this model.

Models in this comparison

Claude Sonnet 4.6 vs MiMo V2.6 Pro Comparison Table

Evals updated October 8, 2026Pricing updated October 9, 2026

PropertyClaude Sonnet 4.6MiMo V2.6 Pro
OrganizationAnthropicXiaomi
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateFeb 2026Sep 2026
Context Window1.0M1.0M
ParametersUnknown1.02T total, 42B active
LicenseProprietaryMIT
Pricing per 1M tokens
Input $/1M$3.00$0.435
Output $/1M$15.00$0.870
Vision Tasks
CaptioningDemoDemo
Chart Question AnsweringSupportedSupported
ClassificationDemoDemo
Document Question AnsweringSupportedSupported
Image TaggingSupportedSupported
Multi-Label ClassificationSupportedSupported
Object DetectionDemoDemo
OCRDemoDemo
Vision LanguageSupportedSupported
Visual Question AnsweringDemoDemo
Model Features
Foundation VisionSupportedSupported
LLMs with Vision CapabilitiesSupportedSupported
Multimodal VisionSupportedSupported
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort
OverallNot evaluated
50.3%
Avg cost / sample–$0.0011
Avg speed / sample–9.45s
By task
Object Detection (low)–
42.0%
±1.1, Mean of 3 runs, range 40.9 to 43.1
$0.0014
Object Detection (high)–
46.7%
±0.8, Mean of 3 runs, range 45.7 to 47.3
$0.0030
Counting (low)–
50.0%
±2.0, Mean of 3 runs, range 48.6 to 52.7
$0.0005
Counting (high)–
59.0%
±5.4, Mean of 3 runs, range 52.7 to 63.5
$0.0016
Identification (low)–
76.0%
±1.6, Mean of 3 runs, range 75.0 to 78.1
$0.0004
Identification (high)–
78.1%
±4.7, Mean of 3 runs, range 71.9 to 81.3
$0.0012
OCR (low)–
48.6%
$0.0012
by category
Single value
37.0%
Transcription
68.2%
Structured JSON
67.7%
Text localization
18.7%
OCR (high)–
49.9%
$0.0034
by category
Single value
40.4%
Transcription
59.9%
Structured JSON
70.2%
Text localization
16.8%
Reasoning (low)–
35.1%
±2.6, Mean of 3 runs, range 32.5 to 37.8
$0.0005
Reasoning (high)–
55.9%
±2.3, Mean of 3 runs, range 54.3 to 58.9
$0.0026

Claude Sonnet 4.6 vs MiMo V2.6 Pro: Overview

Claude Sonnet 4.6

Claude Sonnet 4.6 is Anthropic's mid-tier large language model, released February 17, 2026, designed to balance performance, cost, and versatility for professional and developer use. It supports text and vision-based tasks with advanced reasoning, agentic capabilities, and Adaptive Thinking — a mode where the model dynamically scales its internal reasoning depth. A beta context window of up to 1,000,000 tokens (200K standard) enables processing of entire codebases or document collections in a single request. Parameters are undisclosed.

Optimized for coding, computer use, long-context reasoning, agent planning, and knowledge work, Sonnet 4.6 delivers a full generational upgrade over Sonnet 4.5 and approaches Opus 4.5-level performance across many benchmarks at a fraction of the cost. It is the default model on Claude.ai, Claude Cowork, and is available via API and major cloud platforms — making it well suited for production workloads requiring strong reasoning without flagship pricing.

MiMo V2.6 Pro

MiMo V2.6 Pro is the flagship omni-modal foundation model in Xiaomi's MiMo V2.6 series, released as open weights alongside a Flash variant and a 9B distillation of Qwen3.5. It uses a sparse mixture-of-experts transformer with 1.02 trillion total parameters and roughly 42 billion activated per token, paired with a hybrid attention design that interleaves sliding-window and global attention layers to support a context window of about one million tokens. Dedicated encoders handle non-text inputs, including a vision encoder of roughly 681 million parameters and an audio tokenizer stack, so the model accepts text, images, video, and audio and returns text.

Post-training centers on large-scale reinforcement learning across thousands of interactive environments, combined with agentic grading, self-correction cold start, and a multi-prefix multi-teacher on-policy distillation stage that extends behavior to tasks that are hard to verify automatically. The resulting model targets long-horizon agentic work such as software engineering, terminal and computer-use operation, tool calling, cybersecurity analysis, and visual coding, and it reports gains over the prior MiMo generation on SWE-bench Verified, Terminal Bench, and internal visual coding and cyber benchmarks.

Frequently Asked Questions

Claude Sonnet 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 Sonnet 4.6 is released under Proprietary, while MiMo V2.6 Pro 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 image captioning and image classification in the free Roboflow Playground. You can try it instantly, and a free account unlocks unlimited runs.