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Google · budget

Is Gemini 3.1 Flash Lite Preview good?

Gemini 3.1 Flash Lite Preview has been tested across 1 task areas. It's strongest at coding. It's a budget-friendly option ($1.75/1M tokens).

Top-3 finishes
1/22
Task areas tested
$1.75
Per 1M tokens
Slow
Typical speed

Our take

Google: Gemini 3.1 Flash Lite Preview is a budget-tier model that we tested across 2 task areas. It performs best at Coding.

Strengths

Review quality Explanation Security safety Minimality scope Explanation quality Correctness

Weak spots

Edge case handling Test quality

How Gemini 3.1 Flash Lite Preview ranks, task by task

Rank is the position in each field; Rating is the absolute quality bar. A model can be rated "Excellent" yet sit mid-table when the whole field is strong — and vice-versa.

Task area Rank
Coding #29 of 52

Industry benchmarks

Standardized third-party scores, shown for context — these are independent of our real-task tests.

Artificial Analysis indices

25
Intelligence
34.7
Coding
6.2
Agentic

Design Arena — human preference (avg Elo 1126)

3d 1127 svg 1110 dataviz 1089 gamedev 1098 website 1125 asciiart 1214 uicomponent 1126 codecategories 1122

Headline vs. real-world

Gemini 3.1 Flash Lite Preview punches above its headline benchmarks — it ranks higher on our real-world tasks than its Intelligence Index would suggest.

Source: Artificial Analysis (artificialanalysis.ai) via OpenRouter (openrouter.ai/rankings). (2026-06-29) · Source: Design Arena (www.designarena.ai) via OpenRouter (openrouter.ai/rankings). (2026-06-29)

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Frequently asked

Is Gemini 3.1 Flash Lite Preview any good?

Gemini 3.1 Flash Lite Preview places top-3 in 0 of 1 task areas we benchmarked. It performs best at Coding.

What is Gemini 3.1 Flash Lite Preview best at?

Its strongest task areas are Coding.

Is there a cheaper alternative to Gemini 3.1 Flash Lite Preview?

DeepSeek V3.2 is 67% cheaper and stays competitive on quality across our benchmarks.

How we test & rank

Each model is scored on real tasks across 1 task areas by an LLM judge with deterministic checks. "Percentile" is this model's standing within each area's field; the cross-area figures are rank-based so quality and Elo scores are never mixed.

This page is Spring Prompt, running

We just did this for every model. Do it for your prompt.

The rankings above come from running real tasks through real models and scoring every output. Spring Prompt is that same engine — pointed at your prompt, your test cases, and your definition of good.

  • Generate test cases from your prompt — no eval set required to start.
  • Compare models side by side with quality, cost and latency in one matrix.
  • Optimise the winner until the scores say it's ready to ship.
Experiment · Cold outreach email

Prompt × model results

12 test cases · 3 evals
Claude Opus
GPT-5
Gemini
v1
7.1
6.8
7.4
v2
8.3
7.9
8.0
v3
9.2
8.6
8.4
Best combo: v3 × Claude Opus
9.2 quality · $0.004/run · 1.8s