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Gemini 3 Flash vs MiMo V2.6 Flash

Gemini 3 Flash and MiMo V2.6 Flash score 65.7% vs 49.2% averaged across five Vision Evals tasks (#29 and #57 of 65 models), so Gemini 3 Flash leads overall.

  • Gemini 3 Flash wins all 5 tasks, with its widest lead on reasoning (64.9% vs 33.1%).
  • MiMo V2.6 Flash is about 1/7 of the cost: $0.0003 vs $0.0024 overall average cost per sample.
  • Gemini 3 Flash is faster: 5.8s vs 16.3s per sample.

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GoogleGemini 3 Flash
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MiMo V2.6 Flash
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Gemini 3 Flash vs MiMo V2.6 Flash on Vision Evals

Score by taskGemini 3 FlashMiMo V2.6 Flash
Reasoning
64.9
33.1
Counting
67.6
49.5
Identification
93.8
76.0
OCR
63.9
49.7
Object Detection
38.6
37.8

Roboflow Vision Evals. Full breakdown below.

Gemini 3 Flash vs MiMo V2.6 Flash Comparison Table

Evals updated October 26, 2026Pricing updated November 7, 2026

PropertyGemini 3 FlashMiMo V2.6 Flash
OrganizationGoogleXiaomi
Categoryclosedopen
Modalitymultimodalmultimodal
Release DateDec 2025Sep 2026
Context Window1.0M1.0M
ParametersUnknown309B total, 15B active
LicenseProprietaryMIT
Commercial usecommercial use per vendor termsfree for commercial use
Pricing per 1M tokens
Input $/1M$0.500$0.140
Output $/1M$3.00$0.280
Vision Tasks
Both support 10 more tasks
Model Features
Both support 3 more features
Vision Evalsground-truth scores across 5 vision tasks, pooled at low effort
Overall
65.7%
49.2%
Avg cost / sample$0.0024$0.0003
Avg speed / sample5.83s16.34s
By task
Object Detection (low)
38.6%
$0.0031
37.8%
±1.1, Mean of 3 runs, range 36.4 to 38.7
$0.0004
Object Detection (high)–
45.0%
±2.5, Mean of 3 runs, range 42.2 to 47.1
$0.0009
Counting (low)
67.6%
$0.0012
49.5%
±8.1, Mean of 3 runs, range 41.9 to 58.1
$0.0002
Counting (high)–
64.9%
±1.4, Mean of 3 runs, range 63.5 to 66.2
$0.0003
Identification (low)
93.8%
$0.0009
76.0%
±3.1, Mean of 3 runs, range 71.9 to 78.1
$0.0001
Identification (high)–
82.3%
±4.7, Mean of 3 runs, range 78.1 to 87.5
$0.0003
OCR (low)
63.9%
$0.0024
49.7%
$0.0004
by category
Single value
63.9%
Transcription
90.5%
Structured JSON
80.2%
Text localization
7.6%
Single value
41.7%
Transcription
72.5%
Structured JSON
68.6%
Text localization
9.2%
OCR (high)
73.1%
$0.013
50.4%
$0.0012
by category
Single value
69.1%
Transcription
90.0%
Structured JSON
87.5%
Text localization
36.9%
Single value
42.2%
Transcription
68.9%
Structured JSON
69.2%
Text localization
13.2%
Reasoning (low)
64.9%
$0.0020
33.1%
±2.0, Mean of 3 runs, range 31.1 to 35.1
$0.0002
Reasoning (high)
74.2%
$0.0040
58.5%
±1.3, Mean of 3 runs, range 57.0 to 59.6
$0.0008

Gemini 3 Flash vs MiMo V2.6 Flash: Overview

Gemini 3 Flash

Gemini 3 Flash is a proprietary multimodal large language model developed by Google through Google DeepMind, designed to deliver fast, cost-efficient reasoning across real-time products and developer workflows. Released in December 2025, it is the Flash-tier variant of the Gemini 3 family, balancing low latency with reasoning quality approaching Pro models.

The model supports text, images, audio, and video, with an exceptionally large context window of roughly one million input tokens and outputs up to ~65k tokens. It emphasizes rapid responses for coding, summarization, analysis, and agentic tasks, and exposes configurable “thinking levels” via API to trade speed for deeper reasoning. Today, Gemini 3 Flash positions itself as a high-throughput, production-ready model, serving as the default in the Gemini app and Google Search’s AI Mode, optimized for scalable, interactive AI applications.

MiMo V2.6 Flash

MiMo-V2.6-Flash is the efficiency-oriented checkpoint of Xiaomi's MiMo-V2.6 series, a natively omnimodal foundation model that accepts text, image, video, and audio in a single model and supports a one million token context window. The language backbone is a sparse mixture-of-experts transformer with roughly 309 billion total parameters and 15 billion activated per token, organized as 48 layers with 256 routed experts and top-8 routing. It uses a hybrid attention scheme that interleaves sliding window attention with global attention layers to cut key-value cache cost on long sequences, and pairs the backbone with a vision encoder, an audio encoder, and an audio tokenizer, plus a multi-token prediction module and a draft model for faster decoding.

Training emphasizes large scale reinforcement learning on verifiable, long-horizon tasks, with RL compute, environment diversity, and grader compute scaled together in a single mixed run.

Frequently Asked Questions

On Roboflow's Vision Evals, Gemini 3 Flash performed better. It scores higher on all five vision tasks and averages 65.7% (#29 of 65) against 49.2% (#57 of 65) for MiMo V2.6 Flash. These scores measure vision capabilities only; either model may perform differently on work outside this benchmark's tasks.

Yes. On the Vision Evals Reasoning benchmark at low effort, Gemini 3 Flash leads with 64.9% against 33.1%. This is the widest gap between the two models across the benchmark's tasks.

MiMo V2.6 Flash is cheaper to run. Across Roboflow's Vision Evals task mix it averaged $0.0003 per sample against $0.0024. Gemini 3 Flash is priced at $0.50 per 1M input tokens and $3.00 per 1M output; MiMo V2.6 Flash is priced at $0.14 per 1M input tokens and $0.28 per 1M output. Actual costs depend on your image sizes, prompts, and output length.

Gemini 3 Flash is faster. Across Roboflow's Vision Evals it averaged 5.8s per inference against 16.3s. Latency varies with image size, prompt length, and provider load, so treat these as relative rather than guaranteed figures.

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