Pick Gemini 3.5 Flash for speed — roughly 4x faster than rivals or cost — about a third the price. Pick GPT-5.3-Codex for dedicated coding agent or cli and ide integration. On a tight budget at scale, Gemini 3.5 Flash is the value pick.
Gemini 3.5 Flash (Google) and GPT-5.3-Codex (OpenAI) are two of the models people most often weigh against each other in 2026. Gemini 3.5 Flash is google's fast, cheap class that now beats last year's premium Pro — the value-and-reach play. GPT-5.3-Codex is openAI's coding-specialized agent model for autonomous software engineering. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: nearly identical — $1.5/$9 per 1M tokens vs $1.75/$14 per 1M tokens. Cost will not be the deciding factor here.
Context window: Gemini 3.5 Flash holds 2.5× more — 1M (~1,500 pages) vs 400K (~600 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: Gemini 3.5 Flash is the newer model by about 3 months (released May 19, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Gemini 3.5 Flash
GPT-5.3-Codex
Provider
Google (US)
OpenAI (US)
Released
May 19, 2026
February 24, 2026
Context window
1M (~1,500 pages)
400K (~600 pages)
Price (in/out)
$1.5/$9 per 1M tokens
$1.75/$14 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, audio, video, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Speed — roughly 4x faster than rivals: Gemini 3.5 Flash — Google's fast, cheap class that now beats last year's premium Pro — the value-and-reach play — and it runs cheaper at $1.5/$9 per 1M tokens.
Cost — about a third the price: Gemini 3.5 Flash — At $1.5/$9 per 1M tokens it undercuts GPT-5.3-Codex ($1.75/$14 per 1M tokens), and that gap compounds at volume.
Default in the Gemini app and Search AI Mode: Gemini 3.5 Flash — Google's fast, cheap class that now beats last year's premium Pro — the value-and-reach play — and it carries the larger 1M context.
Dedicated coding agent: GPT-5.3-Codex — GPT-5.3-Codex lists dedicated coding agent among its strengths; Gemini 3.5 Flash does not.
CLI and IDE integration: GPT-5.3-Codex — GPT-5.3-Codex lists cLI and IDE integration among its strengths; Gemini 3.5 Flash does not.
Autonomous software tasks: GPT-5.3-Codex — GPT-5.3-Codex lists autonomous software tasks among its strengths; Gemini 3.5 Flash does not.
Lowest cost at scale: Gemini 3.5 Flash — At $1.5/$9 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Gemini 3.5 Flash — Its 1M window is about 2.5× larger than GPT-5.3-Codex's 400K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Gemini 3.5 Flash — At $1.5/$9 per 1M tokens it undercuts GPT-5.3-Codex, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Gemini 3.5 Flash — Larger 1M window fits more in one prompt.
Anyone whose priority is speed — roughly 4x faster than rivals: Gemini 3.5 Flash — It is specifically built for that.
Anyone whose priority is dedicated coding agent: GPT-5.3-Codex — That is its strongest area.
Gemini 3.5 Flash: where it fits
Google's fast, cheap class that now beats last year's premium Pro — the value-and-reach play. Released May 19, 2026 by Google, it is built for speed — roughly 4x faster than rivals, cost — about a third the price, default in the Gemini app and Search AI Mode, and high-volume multimodal work.
Its trade-offs are real: flash tier, not the deepest reasoning, and pro-tier 3.5 held back at launch. At $1.5 in / $9 out per million tokens, it sits in the mid price band.
GPT-5.3-Codex: where it fits
OpenAI's coding-specialized agent model for autonomous software engineering. Released February 24, 2026 by OpenAI, it is built for dedicated coding agent, cLI and IDE integration, autonomous software tasks, and tool calling.
Its trade-offs: coding-specialized, narrower general use, and retired in favor of GPT-5.5 Codex. At $1.75 in / $14 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Gemini 3.5 Flash and GPT-5.3-Codex overlap enough that the right pick depends on your specific job. Gemini 3.5 Flash costs less per token; Gemini 3.5 Flash holds the larger context; and each leads in its own area — Gemini 3.5 Flash for speed — roughly 4x faster than rivals, GPT-5.3-Codex for dedicated coding agent. Rather than crowning one, run the same hard task through both once and let the results decide.
Frequently asked questions
Is Gemini 3.5 Flash or GPT-5.3-Codex better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, Gemini 3.5 Flash leans toward speed — roughly 4x faster than rivals while GPT-5.3-Codex leans toward dedicated coding agent, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemini 3.5 Flash or GPT-5.3-Codex?
Gemini 3.5 Flash is cheaper — $1.5/$9 per 1M tokens vs $1.75/$14 per 1M tokens, roughly 1.2× apart on input.
Which has the bigger context window?
Gemini 3.5 Flash — 1M vs 400K, about 2.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Gemini 3.5 Flash and GPT-5.3-Codex together?
Yes — a multi-model platform like LumiChats gives you Gemini 3.5 Flash, GPT-5.3-Codex and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, Gemini 3.5 Flash or GPT-5.3-Codex?
Gemini 3.5 Flash — released May 19, 2026, about 3 months after GPT-5.3-Codex.
Gemini 3.5 Flash vs GPT-5.3-Codex
Google · US | OpenAI · US · Updated June 2026
Quick verdict
Pick Gemini 3.5 Flash for speed — roughly 4x faster than rivals or cost — about a third the price. Pick GPT-5.3-Codex for dedicated coding agent or cli and ide integration. On a tight budget at scale, Gemini 3.5 Flash is the value pick.
Gemini 3.5 Flash (Google) and GPT-5.3-Codex (OpenAI) are two of the models people most often weigh against each other in 2026. Gemini 3.5 Flash is google's fast, cheap class that now beats last year's premium Pro — the value-and-reach play. GPT-5.3-Codex is openAI's coding-specialized agent model for autonomous software engineering. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: nearly identical — $1.5/$9 per 1M tokens vs $1.75/$14 per 1M tokens. Cost will not be the deciding factor here.
▸Context window: Gemini 3.5 Flash holds 2.5× more — 1M (~1,500 pages) vs 400K (~600 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: Gemini 3.5 Flash is the newer model by about 3 months (released May 19, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Gemini 3.5 Flash
GPT-5.3-Codex
Provider
Google (US)
OpenAI (US)
Released
May 19, 2026
February 24, 2026
Context window
1M (~1,500 pages)
400K (~600 pages)
Price (in/out)
$1.5/$9 per 1M tokens
$1.75/$14 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, audio, video, code
text, code
SWE-Bench Verified
Not published
Not published
MRCR v2 @ 1M
Not published
Not published
Who wins what
Speed — roughly 4x faster than rivals
Gemini 3.5 Flash
Google's fast, cheap class that now beats last year's premium Pro — the value-and-reach play — and it runs cheaper at $1.5/$9 per 1M tokens.
Cost — about a third the price
Gemini 3.5 Flash
At $1.5/$9 per 1M tokens it undercuts GPT-5.3-Codex ($1.75/$14 per 1M tokens), and that gap compounds at volume.
Default in the Gemini app and Search AI Mode
Gemini 3.5 Flash
Google's fast, cheap class that now beats last year's premium Pro — the value-and-reach play — and it carries the larger 1M context.
Dedicated coding agent
GPT-5.3-Codex
GPT-5.3-Codex lists dedicated coding agent among its strengths; Gemini 3.5 Flash does not.
CLI and IDE integration
GPT-5.3-Codex
GPT-5.3-Codex lists cLI and IDE integration among its strengths; Gemini 3.5 Flash does not.
Autonomous software tasks
GPT-5.3-Codex
GPT-5.3-Codex lists autonomous software tasks among its strengths; Gemini 3.5 Flash does not.
Lowest cost at scale
Gemini 3.5 Flash
At $1.5/$9 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Gemini 3.5 Flash
Its 1M window is about 2.5× larger than GPT-5.3-Codex's 400K, fitting roughly 1,500 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Gemini 3.5 Flash
At $1.5/$9 per 1M tokens it undercuts GPT-5.3-Codex, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Gemini 3.5 Flash
Larger 1M window fits more in one prompt.
Anyone whose priority is speed — roughly 4x faster than rivals
→ Gemini 3.5 Flash
It is specifically built for that.
Anyone whose priority is dedicated coding agent
→ GPT-5.3-Codex
That is its strongest area.
Gemini 3.5 Flash: where it fits
Google's fast, cheap class that now beats last year's premium Pro — the value-and-reach play. Released May 19, 2026 by Google, it is built for speed — roughly 4x faster than rivals, cost — about a third the price, default in the Gemini app and Search AI Mode, and high-volume multimodal work.
Its trade-offs are real: flash tier, not the deepest reasoning, and pro-tier 3.5 held back at launch. At $1.5 in / $9 out per million tokens, it sits in the mid price band.
GPT-5.3-Codex: where it fits
OpenAI's coding-specialized agent model for autonomous software engineering. Released February 24, 2026 by OpenAI, it is built for dedicated coding agent, cLI and IDE integration, autonomous software tasks, and tool calling.
Its trade-offs: coding-specialized, narrower general use, and retired in favor of GPT-5.5 Codex. At $1.75 in / $14 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Gemini 3.5 Flash and GPT-5.3-Codex overlap enough that the right pick depends on your specific job. Gemini 3.5 Flash costs less per token; Gemini 3.5 Flash holds the larger context; and each leads in its own area — Gemini 3.5 Flash for speed — roughly 4x faster than rivals, GPT-5.3-Codex for dedicated coding agent. Rather than crowning one, run the same hard task through both once and let the results decide.
Want both Gemini 3.5 Flash and GPT-5.3-Codex without two subscriptions? LumiChats gives you these plus 40+ models under one ₹69/day pass (about $1/day) — draft with one, cross-check with the other.
Is Gemini 3.5 Flash or GPT-5.3-Codex better for coding?
Public SWE-Bench figures are not available for either model, so the honest test is your own repository — run an identical real bug through both. By design, Gemini 3.5 Flash leans toward speed — roughly 4x faster than rivals while GPT-5.3-Codex leans toward dedicated coding agent, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemini 3.5 Flash or GPT-5.3-Codex?
Gemini 3.5 Flash is cheaper — $1.5/$9 per 1M tokens vs $1.75/$14 per 1M tokens, roughly 1.2× apart on input.
Which has the bigger context window?
Gemini 3.5 Flash — 1M vs 400K, about 2.5× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Gemini 3.5 Flash and GPT-5.3-Codex together?
Yes — a multi-model platform like LumiChats gives you Gemini 3.5 Flash, GPT-5.3-Codex and 40+ others under one ₹69/day pass (about $1/day), so you can draft with one and cross-check with the other instead of buying two subscriptions.
Which is newer, Gemini 3.5 Flash or GPT-5.3-Codex?
Gemini 3.5 Flash — released May 19, 2026, about 3 months after GPT-5.3-Codex.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.