Google•Rank #71

Gemini 3 Flash

Proprietarygeneralfastbudget
Leaderboard Score
37.1
Scale: 0 - 100
Throughput Speed
287 tps
Context Window
1M
API Pricing / 1M
$0.40
Parameter Scale
Proprietary
Verified AI Radar & Benchmarks•8 Evaluated Metrics

Capability Radar & Benchmark Scores

Multi-Axis Capability Radar

Comparing Gemini 3 Flash against Frontier Top 10 & Open-Source average

0 - 100 Scale
Gemini 3 Flash
Frontier Top 10 Avg
Open-Source Avg
Performance Vectors

Where Gemini 3 Flash Leads

Coding & SWETop 10: 79.1% • OS: 47.6%
22.9%-56.2% vs Top 10
Reasoning & MathTop 10: 74.6% • OS: 46.6%
38.0%-36.6% vs Top 10
Agent & Tool AutomationTop 10: 71.2% • OS: 31.9%
19.2%-52.0% vs Top 10
Terminal & CLI ExecutionTop 10: 80.4% • OS: 47.6%
22.9%-57.5% vs Top 10
MMLU & Knowledge QATop 10: 50% • OS: 86.7%
46.4%-3.6% vs Top 10
Cyber & Security ExploitsTop 10: 87.8% • OS: 80.6%
35.2%-52.6% vs Top 10

All Verified Benchmark Evaluations

Direct Pass@1 and resolution rates across standardized evaluations.

OverallCodingReasoningAgenticTerminal
Featured Compute Platform

Run Benchmarks on Dedicated AI Clusters

Zero-cold-start inference endpoints with dedicated GPU instances.

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Executive Analysis & Verdict

Gemini 3 Flash by Google is a proprietary Large Language Model ranking #62 globally with an overall benchmark score of 37.1.

Key Strengths & Highlights

  • •High overall benchmark score of 37.1 on frontier evaluation suites
  • •Robust reasoning performance (38) and coding accuracy (22.9)
  • •Generation throughput of 287c/s with 1.0M token context

Limitations & Considerations

  • •Subject to standard provider rate limits and API quota
Recommended Workflows
Enterprise production applications, coding assistance, and advanced reasoning

Architectural Overview & Capability Profile

Gemini 3 Flash is developed by Google DeepMind as an advanced foundation model engineered for production enterprise applications, reasoning workflows, and autonomous problem-solving. On the comprehensive RankLLMs composite evaluation index, Gemini 3 Flash registers an overall benchmark rating of 37.1 / 100.

Operating under a Proprietary license structure, Gemini 3 Flash is served via high-throughput managed API endpoints designed for low-latency production queries.

Benchmark Performance & Real-World Utility

In standardized laboratory and real-world evaluation suites, Gemini 3 Flash demonstrates calibrated proficiency across key performance vectors:

  • SWE-bench Verified Software Engineering (22.9%): Measures multi-file GitHub issue resolution. The model demonstrates practical capability in localizing source code bugs, synthesizing functional patches, and passing rigorous integration test matrices. For evaluation methodology, consult our SWE-bench Pro guide.

  • GPQA Diamond Scientific Reasoning (38%): Assesses graduate-level domain problem solving across physics, chemistry, and biology, minimizing hallucinations in multi-step deductive arguments. See our Humanity’s Last Exam benchmark analysis.

  • MATH-500 Competition Mathematics (38%): Evaluates formal mathematical problem solving and symbolic derivation, providing foundational logic for algorithmic computing.

  • Terminal-Bench Execution (22.9%): Reflects proficiency in interactive command-line environments, shell tool use, and automated DevOps scripting.

  • Code Arena Preference Rating (1655 Elo): Validates human developer satisfaction in blind side-by-side coding evaluations against contemporary alternatives.

Inference Latency & Cost Architecture

  • Token Context Window: 1.0M tokens, allowing large documents, multi-file codebases, and long conversation memories to be processed in a single context window.
  • Inference Speed: Reference throughput clocks at approximately 287 tokens/second, enabling responsive streaming in developer tools and interactive interfaces.
  • Commercial Pricing: API consumption is billed at $0.40 per 1M input tokens and $2.40 per 1M output tokens, offering predictable scaling for high-volume enterprise traffic.

Strengths, Limitations & Ideal Workflows

Primary Strengths

  • High overall benchmark score of 37.1 on frontier evaluation suites
  • Robust reasoning performance (38) and coding accuracy (22.9)
  • Generation throughput of 287c/s with 1.0M token context

Known Considerations

  • Subject to standard provider rate limits and API quota

Enterprise production applications, coding assistance, and advanced reasoning.

Frequently Asked Questions About Gemini 3 Flash

What is Gemini 3 Flash and who developed it?↓
Gemini 3 Flash is a proprietary large language model developed by Google. It ranks #71 on the RankLLMs composite leaderboard, ahead of 18% of the 85 models we track, with an overall score of 37.1 / 100.
Can Gemini 3 Flash handle very long documents and codebases?↓
Gemini 3 Flash supports a 1.0M-token input context window and generates about 287 tps tokens per second in our reference measurements and which is enough to hold entire repositories, long transcripts, or multi-document research sets in a single session..
Why is Gemini 3 Flash priced so far below its peers?↓
Gemini 3 Flash is cheaper than 71% of the priced models we track at $0.40 per 1M tokens, while keeping competitive benchmark scores - which is why it rates well on cost per solved task, not just per token.
What is Gemini 3 Flash best at?↓
Gemini 3 Flash is strongest in High overall benchmark score of 37.1 on frontier evaluation suites; Robust reasoning performance (38) and coding accuracy (22.9); Generation throughput of 287c/s with 1.0M token context. Full pillar-by-pillar numbers are in the benchmark tables above.
What should you watch out for with Gemini 3 Flash?↓
Known trade-offs include: Subject to standard provider rate limits and API quota. Weigh these against the strengths above for your specific workload.