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gemini-3.6-flash vs gpt-5.3-codex

Side-by-side comparison of gemini-3.6-flash and gpt-5.3-codex: benchmarks, pricing, context window and capabilities. Both are accessible through Requesty's unified API. gemini-3.6-flash outperforms gpt-5.3-codex on 2 of 3 shared benchmarks.

Benchmark comparison

Intelligence Indexreasoning
gemini-3.6-flash40.3%
gpt-5.3-codex36.9%
Coding Indexcoding
gemini-3.6-flash69.2%
gpt-5.3-codexN/A
GPQA Diamondreasoning
gemini-3.6-flash92.8%
gpt-5.3-codex91.5%
Terminal-Bench Hardagentic
gemini-3.6-flashN/A
gpt-5.3-codex53.0%
τ²-Benchagentic
gemini-3.6-flashN/A
gpt-5.3-codex86.0%
SciCodecoding
gemini-3.6-flash53.4%
gpt-5.3-codexN/A
Humanity's Last Examreasoning
gemini-3.6-flash40.8%
gpt-5.3-codex42.5%

Scores sourced from official model cards, Artificial Analysis, and public leaderboards. Benchmarks measure specific skills and don't capture every aspect of model quality.

Pricing & specifications

gemini-3.6-flashgpt-5.3-codex
Input price / 1M$1.50$1.75
Output price / 1M$7.00$14.00
Context window1.0M tokens400K tokens
Max output66K tokens128K tokens
Vision inputYesYes
Tool callingYesYes
ReasoningYesYes
Prompt cachingYesYes
Computer useN/AN/A
ProviderGoogle LLC (Gemini API)OpenAI Responses

Questions people ask

Is gemini-3.6-flash better than gpt-5.3-codex?
gemini-3.6-flash outperforms gpt-5.3-codex on 2 of 3 shared benchmarks. See the benchmark comparison above for specifics: gemini-3.6-flash and gpt-5.3-codex have different strengths across reasoning, coding, math and multimodal tasks.
Which is cheaper, gemini-3.6-flash or gpt-5.3-codex?
gemini-3.6-flash is cheaper. gemini-3.6-flash costs $1.50/$7.00 per 1M input/output tokens, while gpt-5.3-codex costs $1.75/$14.00.
Can I use gemini-3.6-flash and gpt-5.3-codex through the same API?
Yes. Requesty provides a single OpenAI-compatible API that routes to both. Change just the "model" parameter to switch between "google/gemini-3.6-flash" and "openai-responses/gpt-5.3-codex", no other code changes needed.
What are the context windows?
gemini-3.6-flash supports up to 1.0M tokens of context. gpt-5.3-codex supports up to 400K tokens. Longer context means you can feed larger documents or codebases in a single prompt, though quality often degrades past 128K for most models.

Switch between gemini-3.6-flash and gpt-5.3-codex with one line of code

Requesty provides a single OpenAI-compatible API for 600+ models. Change the model parameter, not your code.