💰 Unit Cost Winner Gemini 3.5 Flash-Lite $0.075/1M in · $0.30/1M out
⚡ Latency & Speed Winner Gemini 3.5 Flash-Lite 78ms TTFT · 265 tok/s
💻 Coding (SWE) Winner Gemini 3.5 Flash-Lite 55.4% SWE-bench · 91% HumanEval
🧠 STEM Reasoning Winner o1 78% GPQA · 96.4% MATH-500

Which model is better: Gemini 3.5 Flash-Lite or o1?

Gemini 3.5 Flash-Lite is 99.5% cheaper for input tokens ($0.07 vs. $15.00 per 1M tokens) and $0.30 vs. $60.00 for output tokens (200.0x cost advantage). In terms of operational performance, Gemini 3.5 Flash-Lite delivers lower response latency at 78ms TTFT (2522ms faster than o1) with 265 vs. 48 tok/s throughput. Gemini 3.5 Flash-Lite leads coding evaluations at 55.4% SWE-bench Verified vs. 48.9% for o1 and 68.4% vs. 78.0% on GPQA Diamond.
Verified daily via automated API latency tests and official documentation.

Verified Performance & Unit Economics Delta (12 Dimensions)

Daily synchronized metrics across token pricing, prompt cache economics, latency, throughput, and 5 capability benchmarks.

Metric / Dimension Gemini 3.5 Flash-Lite o1 Net Delta / Advantage
Input Cost / 1M Tokens $0.07 $15.00 Gemini 3.5 Flash-Lite is 200.0x cheaper
Output Cost / 1M Tokens $0.30 $60.00 Gemini 3.5 Flash-Lite (99.5% lower)
Prompt Cache Read / 1M $0.015 $7.500 Gemini 3.5 Flash-Lite is 500.0x cheaper
Prompt Cache Write / 1M $0.07 $15.00 Gemini 3.5 Flash-Lite is 200.0x cheaper
Context Window (Max Output) 1,049k (33k out) 205k (100k out) Gemini 3.5 Flash-Lite (5.1x larger context)
Avg TTFT Response Latency 78ms 2600ms Gemini 3.5 Flash-Lite (2522ms faster)
Generation Speed (Throughput) 265 tok/s 48 tok/s Gemini 3.5 Flash-Lite (+217 tok/s faster)
SWE-bench Verified (Coding) 55.4% 48.9% Gemini 3.5 Flash-Lite (+6.5% lead)
GPQA Diamond (PhD STEM) 68.4% 78% o1 (+9.6% lead)
MMLU-Pro (Multi-Discipline) 80.1% 83.3% o1 (+3.2% lead)
MATH-500 (Quantitative Logic) 90.2% 96.4% o1 (+6.2% lead)
Inference Value Score (IVR) 81.5 / 100 37.2 / 100 Gemini 3.5 Flash-Lite (+44.3 pts)

Interactive Monthly Token Economics & ROI Forecaster

Model production workloads across prompt, completion, and cached context tokens, or switch models on the fly.

25.0M Tokens
500K 50M 250M 500M+
5.0M Tokens
100K 25M 75M 150M+
50% Cached
0% (Uncached) 25% 50% (Typical Agent) 95% Max

Estimated Monthly Spend

Gemini 3.5 Flash-Lite $2.63

$0.07/1M in · $0.30/1M out

Prompt Cache: $0.015/1M read · $0.07/1M write

o1 $581.25

$15.00/1M in · $60.00/1M out

Prompt Cache: $7.500/1M read · $15.00/1M write

Projected Monthly Cost Reduction
$578.63 / mo
(99.5% lower cost with Gemini 3.5 Flash-Lite)
Open Full Matchup Analysis →
A

When to Choose Gemini 3.5 Flash-Lite

Choose Gemini 3.5 Flash-Lite (Google) for high-frequency data pipelines, real-time routing, large-scale document tagging, and ultra-low-cost conversational assistants — offering a 1,048k context window, 78ms TTFT, and $0.07/1M input pricing ($0.015/1M cached reads).

B

When to Choose o1

Choose o1 (OpenAI) for legacy reasoning benchmarks, scientific literature review, and complex mathematical proofs — offering a 204k context window, 2600ms TTFT, and $15.00/1M input pricing ($7.500/1M cached reads).

Related Questions & Decision Factors

Which is cheaper: Gemini 3.5 Flash-Lite or o1?

Gemini 3.5 Flash-Lite is cheaper at $0.075/1M input tokens ($0.30/1M output) compared to $15.00/1M input ($60.00/1M output) for o1.

Which model has lower TTFT latency and higher tok/s throughput: Gemini 3.5 Flash-Lite or o1?

Gemini 3.5 Flash-Lite delivers faster first-token latency at 78ms TTFT (265 tok/s throughput) compared to 2600ms TTFT (48 tok/s) for o1.

How do Gemini 3.5 Flash-Lite and o1 compare on SWE-bench coding and GPQA Diamond reasoning?

On SWE-bench Verified software engineering, Gemini 3.5 Flash-Lite scores 55.4% versus 48.9% for o1. On GPQA Diamond graduate-level STEM reasoning, Gemini 3.5 Flash-Lite scores 68.4% versus 78% for o1 (and 90.2% vs 96.4% on MATH-500).

When should you choose Gemini 3.5 Flash-Lite?

Choose Gemini 3.5 Flash-Lite (Google) for high-frequency data pipelines, real-time routing, large-scale document tagging, and ultra-low-cost conversational assistants — offering a 1,048k context window, 78ms TTFT, and $0.07/1M input pricing ($0.015/1M cached reads).

When should you choose o1?

Choose o1 (OpenAI) for legacy reasoning benchmarks, scientific literature review, and complex mathematical proofs — offering a 204k context window, 2600ms TTFT, and $15.00/1M input pricing ($7.500/1M cached reads).

Explore High-Priority Related Model Matchups