Gemini 3.5 Flash-LitevsGPT-5.3-Codex
Gemini 3.5 Flash-Lite | GPT-5.3-Codex | |
|---|---|---|
| API pricingUSD per 1M tokens · lower wins | ||
Input priceWhat you pay for everything you send the model — your question, plus any documents or earlier conversation you include with it. | $0.30 | $1.75 |
Output priceWhat you pay for the text the model writes back. It is normally the dearer half: producing an answer costs more than reading one. | $2.50 | $14.00 |
Cached input priceA reduced rate for text you send over and over. If every request starts with the same instructions or the same document, the provider keeps a copy ready and charges less to read it again. | $0.03 | $0.175 |
Cheapest inputLowest input rate across third-party providers, excluding the lab itself. The cheapest endpoint may run a quantised build or a shorter context — see "Available from" on the model page. | — | $1.75Azure |
Cheapest outputLowest output rate across third-party providers, excluding the lab itself. May come from a different provider than the cheapest input. | — | $14.00Azure |
| Benchmarks | ||
BullshitBench v2Nonsense detection — Given a confidently-worded but nonsensical prompt, does the AI spot that it makes no sense and push back — instead of playing along and inventing an answer? The score is how often it clearly called out the nonsense. Higher is better. | 65% | 24% |
OSWorld-VerifiedAgentic computer use — Can the AI actually operate a computer — clicking, typing, and using real apps — to finish tasks on its own? Higher is better. | 74% | 64.7% |
| BenchmarksPublished by one model only | ||
SWE-Bench ProAgentic coding — Can the AI fix real bugs in real software? It's handed actual problems from open-source projects and has to write code that genuinely solves them. Higher is better. | 54.2% | — |
SWE-Bench VerifiedCoding — Real coding tasks pulled from open-source projects — the AI has to find and fix actual bugs. A human-checked version of the original SWE-Bench. Higher is better. | — | 85% |
Next.js EvalsNext.js coding — Vercel's open eval of how well AI coding agents build and migrate real Next.js apps — measured as the share of tasks the agent completes successfully. Higher is better. | — | 81% |
Terminal-Bench 2.1Agentic terminal coding — Can the AI work in a command-line terminal — running commands and finishing technical setup tasks the way a developer would? Higher is better. | 54% | — |
BU BenchBrowser agent — Can the AI drive a real web browser to finish tasks — clicking, filling forms, and navigating sites the way a person would? Run by Browser Use on their BU Bench task set. Higher is better. | 49% | — |
GDPval-AA v2Knowledge work — economically valuable knowledge work (v2, re-based Elo) | 1140 | — |
| Overview | ||
| Company | OpenAI | |
| Release date | Jul 21 2026 | Feb 5 2026 |
| Access | Proprietary | Proprietary |
Other comparisons
Frequently asked questions
Gemini 3.5 Flash-Lite leads GPT-5.3-Codex on 2 of the 2 benchmarks they both report (BullshitBench v2, OSWorld-Verified). Gemini 3.5 Flash-Lite is cheaper on both input and output: $0.30 vs $1.75 per million input tokens, and $2.50 vs $14.00 per million output tokens. GPT-5.3-Codex shipped 166 days before Gemini 3.5 Flash-Lite, so benchmark comparisons should account for the intervening progress.
Published specifications for these two models are limited — see each model page for the latest details.
On BullshitBench v2, Gemini 3.5 Flash-Lite leads at 65% vs GPT-5.3-Codex at 24%. On OSWorld-Verified, Gemini 3.5 Flash-Lite leads at 74% vs GPT-5.3-Codex at 64.7%.
Gemini 3.5 Flash-Lite was released by Google on Jul 21 2026.
GPT-5.3-Codex was released by OpenAI on Feb 5 2026.
Gemini 3.5 Flash-Lite is cheaper on both input and output: $0.30 vs $1.75 per million input tokens, and $2.50 vs $14.00 per million output tokens. Rates are pay-as-you-go API prices verified on August 18, 2026.