Pick Gemini 3.1 Pro for largest mainstream production context (2m) or long video and document analysis. Pick GPT-5.3-Codex for dedicated coding agent or cli and ide integration. On a tight budget at scale, GPT-5.3-Codex is the value pick.
Gemini 3.1 Pro (Google) and GPT-5.3-Codex (OpenAI) are two of the models people most often weigh against each other in 2026. Gemini 3.1 Pro is a 2M-token multimodal workhorse — huge breadth, but recall fades deep in the window. 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: GPT-5.3-Codex is about 8× cheaper on input ($1.5/$10 per 1M tokens vs $12/$18 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
Context window: Gemini 3.1 Pro holds 16× more — 2M (~3,000 pages) vs 128K (~192 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Specifications
Spec
Gemini 3.1 Pro
GPT-5.3-Codex
Provider
Google (US)
OpenAI (US)
Released
February 2026
2026
Context window
2M (~3,000 pages)
128K (~192 pages)
Price (in/out)
$12/$18 per 1M tokens
$1.5/$10 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
26.3%
Not published
Who wins what
Largest mainstream production context (2M): Gemini 3.1 Pro — A core design strength of Gemini 3.1 Pro.
Long video and document analysis: Gemini 3.1 Pro — A core design strength of Gemini 3.1 Pro.
Agentic reasoning (high ARC-AGI-2): Gemini 3.1 Pro — A core design strength of Gemini 3.1 Pro.
Dedicated coding agent: GPT-5.3-Codex — A core design strength of GPT-5.3-Codex.
CLI and IDE integration: GPT-5.3-Codex — A core design strength of GPT-5.3-Codex.
Autonomous software tasks: GPT-5.3-Codex — A core design strength of GPT-5.3-Codex.
Lowest cost at scale: GPT-5.3-Codex — At $1.5/$10 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input: Gemini 3.1 Pro — Its 2M window is about 16× larger, fitting roughly 3,000 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: GPT-5.3-Codex — At $1.5/$10 per 1M tokens it undercuts Gemini 3.1 Pro, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases: Gemini 3.1 Pro — Larger 2M window fits more in one prompt.
Anyone whose priority is largest mainstream production context (2m): Gemini 3.1 Pro — It is specifically built for that.
Anyone whose priority is dedicated coding agent: GPT-5.3-Codex — That is its strongest area.
Gemini 3.1 Pro: where it fits
A 2M-token multimodal workhorse — huge breadth, but recall fades deep in the window. Released February 2026 by Google, it is built for largest mainstream production context (2M), long video and document analysis, agentic reasoning (high ARC-AGI-2), and multimodal understanding.
Its trade-offs are real: long-context recall drops sharply past 256K, and premium price per token. At $12 in / $18 out per million tokens, it sits in the premium price band.
GPT-5.3-Codex: where it fits
OpenAI's coding-specialized agent model for autonomous software engineering. Released 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 $1.5 in / $10 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Gemini 3.1 Pro and GPT-5.3-Codex overlap enough that the right pick depends on your specific job. GPT-5.3-Codex costs less per token; Gemini 3.1 Pro holds the larger context; and each leads in its own area — Gemini 3.1 Pro for largest mainstream production context (2m), 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 3.1 Pro 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 3.1 Pro leans toward largest mainstream production context (2m) 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 3.1 Pro or GPT-5.3-Codex?
GPT-5.3-Codex is cheaper — $12/$18 per 1M tokens vs $1.5/$10 per 1M tokens, roughly 8× apart on input.
Which has the bigger context window?
Gemini 3.1 Pro — 2M vs 128K, about 16× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Gemini 3.1 Pro and GPT-5.3-Codex together?
Yes — a multi-model platform like LumiChats gives you Gemini 3.1 Pro, 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 3.1 Pro or GPT-5.3-Codex?
GPT-5.3-Codex — released 2026, about 14 days after Gemini 3.1 Pro.
Gemini 3.1 Pro vs GPT-5.3-Codex
Google · US | OpenAI · US · Updated June 2026
Quick verdict
Pick Gemini 3.1 Pro for largest mainstream production context (2m) or long video and document analysis. Pick GPT-5.3-Codex for dedicated coding agent or cli and ide integration. On a tight budget at scale, GPT-5.3-Codex is the value pick.
Gemini 3.1 Pro (Google) and GPT-5.3-Codex (OpenAI) are two of the models people most often weigh against each other in 2026. Gemini 3.1 Pro is a 2M-token multimodal workhorse — huge breadth, but recall fades deep in the window. 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: GPT-5.3-Codex is about 8× cheaper on input ($1.5/$10 per 1M tokens vs $12/$18 per 1M tokens) — a large enough gap that at scale it can be the single biggest line item in the decision.
▸Context window: Gemini 3.1 Pro holds 16× more — 2M (~3,000 pages) vs 128K (~192 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Side-by-side specs
Spec
Gemini 3.1 Pro
GPT-5.3-Codex
Provider
Google (US)
OpenAI (US)
Released
February 2026
2026
Context window
2M (~3,000 pages)
128K (~192 pages)
Price (in/out)
$12/$18 per 1M tokens
$1.5/$10 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
26.3%
Not published
Who wins what
Largest mainstream production context (2M)
Gemini 3.1 Pro
A core design strength of Gemini 3.1 Pro.
Long video and document analysis
Gemini 3.1 Pro
A core design strength of Gemini 3.1 Pro.
Agentic reasoning (high ARC-AGI-2)
Gemini 3.1 Pro
A core design strength of Gemini 3.1 Pro.
Dedicated coding agent
GPT-5.3-Codex
A core design strength of GPT-5.3-Codex.
CLI and IDE integration
GPT-5.3-Codex
A core design strength of GPT-5.3-Codex.
Autonomous software tasks
GPT-5.3-Codex
A core design strength of GPT-5.3-Codex.
Lowest cost at scale
GPT-5.3-Codex
At $1.5/$10 per 1M tokens, it is the cheaper of the two — the gap dominates the bill on high-volume workloads.
Largest single-prompt input
Gemini 3.1 Pro
Its 2M window is about 16× larger, fitting roughly 3,000 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ GPT-5.3-Codex
At $1.5/$10 per 1M tokens it undercuts Gemini 3.1 Pro, and on millions of tokens that margin decides the monthly bill.
Someone analysing very long documents or codebases
→ Gemini 3.1 Pro
Larger 2M window fits more in one prompt.
Anyone whose priority is largest mainstream production context (2m)
→ Gemini 3.1 Pro
It is specifically built for that.
Anyone whose priority is dedicated coding agent
→ GPT-5.3-Codex
That is its strongest area.
Gemini 3.1 Pro: where it fits
A 2M-token multimodal workhorse — huge breadth, but recall fades deep in the window. Released February 2026 by Google, it is built for largest mainstream production context (2M), long video and document analysis, agentic reasoning (high ARC-AGI-2), and multimodal understanding.
Its trade-offs are real: long-context recall drops sharply past 256K, and premium price per token. At $12 in / $18 out per million tokens, it sits in the premium price band.
GPT-5.3-Codex: where it fits
OpenAI's coding-specialized agent model for autonomous software engineering. Released 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 $1.5 in / $10 out per million tokens, it sits in the mid price band.
The bottom line for this matchup
Gemini 3.1 Pro and GPT-5.3-Codex overlap enough that the right pick depends on your specific job. GPT-5.3-Codex costs less per token; Gemini 3.1 Pro holds the larger context; and each leads in its own area — Gemini 3.1 Pro for largest mainstream production context (2m), 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 3.1 Pro 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 3.1 Pro 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 3.1 Pro leans toward largest mainstream production context (2m) 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 3.1 Pro or GPT-5.3-Codex?
GPT-5.3-Codex is cheaper — $12/$18 per 1M tokens vs $1.5/$10 per 1M tokens, roughly 8× apart on input.
Which has the bigger context window?
Gemini 3.1 Pro — 2M vs 128K, about 16× larger. Useful only if the model actually reasons over the full window, which not all do.
Can I use both Gemini 3.1 Pro and GPT-5.3-Codex together?
Yes — a multi-model platform like LumiChats gives you Gemini 3.1 Pro, 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 3.1 Pro or GPT-5.3-Codex?
GPT-5.3-Codex — released 2026, about 14 days after Gemini 3.1 Pro.
Specifications and benchmarks reflect publicly reported figures as of June 2026 and may change as providers release updates. Always verify on your own workload.