Pick Gemini 3.1 Pro for largest mainstream production context (2m) or long video and document analysis. Pick GPT-5.5 for terminal, cli and computer-use automation or long-horizon tool sequencing. On a tight budget at scale, Gemini 3.1 Pro is the value pick.
Gemini 3.1 Pro (Google) and GPT-5.5 (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-5.5 is openAI's first fully retrained base since GPT-4.5 — the terminal and computer-use champion. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences
Price: Gemini 3.1 Pro is about 2.5× cheaper on input ($2/$12 per 1M tokens vs $5/$30 per 1M tokens) — meaningful once you are processing millions of tokens a month.
Context window: Gemini 3.1 Pro holds 2× more — 2M (~3,000 pages) vs 1M (~1,500 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
Recency: GPT-5.5 is the newer model by about 2 months (released April 23, 2026), usually meaning fresher training data and capabilities.
Specifications
Spec
Gemini 3.1 Pro
GPT-5.5
Provider
Google (US)
OpenAI (US)
Released
February 19, 2026
April 23, 2026
Context window
2M (~3,000 pages)
1M (~1,500 pages)
Price (in/out)
$2/$12 per 1M tokens
$5/$30 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, audio, video, code
text, image, 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 — Its 2M window holds about 2× more than GPT-5.5's 1M in a single prompt.
Long video and document analysis: Gemini 3.1 Pro — A 2M-token multimodal workhorse — huge breadth, but recall fades deep in the window — and it runs cheaper at $2/$12 per 1M tokens.
Agentic reasoning (high ARC-AGI-2): Gemini 3.1 Pro — A 2M-token multimodal workhorse — huge breadth, but recall fades deep in the window — and it carries the larger 2M context.
Terminal, CLI and computer-use automation: GPT-5.5 — OpenAI's first fully retrained base since GPT-4.5 — the terminal and computer-use champion — and it is the newer of the two.
Long-horizon tool sequencing: GPT-5.5 — GPT-5.5 lists long-horizon tool sequencing among its strengths; Gemini 3.1 Pro does not.
Strong agentic coding and reasoning: GPT-5.5 — GPT-5.5 lists strong agentic coding and reasoning among its strengths; Gemini 3.1 Pro does not.
Lowest cost at scale: Gemini 3.1 Pro — At $2/$12 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 2× larger than GPT-5.5's 1M, fitting roughly 3,000 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume: Gemini 3.1 Pro — At $2/$12 per 1M tokens it undercuts GPT-5.5, 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 terminal, cli and computer-use automation: GPT-5.5 — 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 19, 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 $2 in / $12 out per million tokens, it sits in the mid price band.
GPT-5.5: where it fits
OpenAI's first fully retrained base since GPT-4.5 — the terminal and computer-use champion. Released April 23, 2026 by OpenAI, it is built for terminal, CLI and computer-use automation, long-horizon tool sequencing, strong agentic coding and reasoning, and browser-driving agents.
Its trade-offs: trails Opus 4.8 on hardest coding benchmarks, and tiered long-context pricing above 272K tokens. At $5 in / $30 out per million tokens, it sits in the premium price band.
The bottom line for this matchup
Gemini 3.1 Pro and GPT-5.5 overlap enough that the right pick depends on your specific job. Gemini 3.1 Pro 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-5.5 for terminal, cli and computer-use automation. 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-5.5 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-5.5 leans toward terminal, cli and computer-use automation, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemini 3.1 Pro or GPT-5.5?
Gemini 3.1 Pro is cheaper — $2/$12 per 1M tokens vs $5/$30 per 1M tokens, roughly 2.5× apart on input.
Which has the bigger context window?
Gemini 3.1 Pro — 2M vs 1M, about 2× 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-5.5 together?
Yes — a multi-model platform like LumiChats gives you Gemini 3.1 Pro, GPT-5.5 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-5.5?
GPT-5.5 — released April 23, 2026, about 2 months after Gemini 3.1 Pro.
Gemini 3.1 Pro vs GPT-5.5
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-5.5 for terminal, cli and computer-use automation or long-horizon tool sequencing. On a tight budget at scale, Gemini 3.1 Pro is the value pick.
Gemini 3.1 Pro (Google) and GPT-5.5 (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-5.5 is openAI's first fully retrained base since GPT-4.5 — the terminal and computer-use champion. They diverge most on price and context window — each quantified below from the models' real specs.
Key differences at a glance
▸Price: Gemini 3.1 Pro is about 2.5× cheaper on input ($2/$12 per 1M tokens vs $5/$30 per 1M tokens) — meaningful once you are processing millions of tokens a month.
▸Context window: Gemini 3.1 Pro holds 2× more — 2M (~3,000 pages) vs 1M (~1,500 pages). But effective recall usually fades long before the advertised ceiling, so the bigger number only helps if the model reasons over it.
▸Recency: GPT-5.5 is the newer model by about 2 months (released April 23, 2026), usually meaning fresher training data and capabilities.
Side-by-side specs
Spec
Gemini 3.1 Pro
GPT-5.5
Provider
Google (US)
OpenAI (US)
Released
February 19, 2026
April 23, 2026
Context window
2M (~3,000 pages)
1M (~1,500 pages)
Price (in/out)
$2/$12 per 1M tokens
$5/$30 per 1M tokens
Open weight?
No — API only
No — API only
Modalities
text, image, audio, video, code
text, image, 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
Its 2M window holds about 2× more than GPT-5.5's 1M in a single prompt.
Long video and document analysis
Gemini 3.1 Pro
A 2M-token multimodal workhorse — huge breadth, but recall fades deep in the window — and it runs cheaper at $2/$12 per 1M tokens.
Agentic reasoning (high ARC-AGI-2)
Gemini 3.1 Pro
A 2M-token multimodal workhorse — huge breadth, but recall fades deep in the window — and it carries the larger 2M context.
Terminal, CLI and computer-use automation
GPT-5.5
OpenAI's first fully retrained base since GPT-4.5 — the terminal and computer-use champion — and it is the newer of the two.
Long-horizon tool sequencing
GPT-5.5
GPT-5.5 lists long-horizon tool sequencing among its strengths; Gemini 3.1 Pro does not.
Strong agentic coding and reasoning
GPT-5.5
GPT-5.5 lists strong agentic coding and reasoning among its strengths; Gemini 3.1 Pro does not.
Lowest cost at scale
Gemini 3.1 Pro
At $2/$12 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 2× larger than GPT-5.5's 1M, fitting roughly 3,000 pages in one prompt.
Which should you pick?
A cost-sensitive startup shipping high volume
→ Gemini 3.1 Pro
At $2/$12 per 1M tokens it undercuts GPT-5.5, 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 terminal, cli and computer-use automation
→ GPT-5.5
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 19, 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 $2 in / $12 out per million tokens, it sits in the mid price band.
GPT-5.5: where it fits
OpenAI's first fully retrained base since GPT-4.5 — the terminal and computer-use champion. Released April 23, 2026 by OpenAI, it is built for terminal, CLI and computer-use automation, long-horizon tool sequencing, strong agentic coding and reasoning, and browser-driving agents.
Its trade-offs: trails Opus 4.8 on hardest coding benchmarks, and tiered long-context pricing above 272K tokens. At $5 in / $30 out per million tokens, it sits in the premium price band.
The bottom line for this matchup
Gemini 3.1 Pro and GPT-5.5 overlap enough that the right pick depends on your specific job. Gemini 3.1 Pro 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-5.5 for terminal, cli and computer-use automation. 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-5.5 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.
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-5.5 leans toward terminal, cli and computer-use automation, and that positioning usually predicts which feels better on your codebase.
Which is cheaper, Gemini 3.1 Pro or GPT-5.5?
Gemini 3.1 Pro is cheaper — $2/$12 per 1M tokens vs $5/$30 per 1M tokens, roughly 2.5× apart on input.
Which has the bigger context window?
Gemini 3.1 Pro — 2M vs 1M, about 2× 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-5.5 together?
Yes — a multi-model platform like LumiChats gives you Gemini 3.1 Pro, GPT-5.5 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-5.5?
GPT-5.5 — released April 23, 2026, about 2 months 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.